").append(res.responseText.replac= e(//g,"")).find(selector):res.responseText);self.= each(callback,[res.responseText,status,res]);}});return = this;},serialize:function(){return = jQuery.param(this.serializeArray());},serializeArray:function(){return = this.map(function(){return = jQuery.nodeName(this,"form")?jQuery.makeArray(this.elements):this;}).filt= er(function(){return = this.name&&!this.disabled&&(this.checked||/select|textarea/i.test(this.no= deName)||/text|hidden|password/i.test(this.type));}).map(function(i,elem)= {var val=3DjQuery(this).val();return = val=3D=3Dnull?null:val.constructor=3D=3DArray?jQuery.map(val,function(val= ,i){return{name:elem.name,value:val};}):{name:elem.name,value:val};}).get= ();}});jQuery.each("ajaxStart,ajaxStop,ajaxComplete,ajaxError,ajaxSuccess= ,ajaxSend".split(","),function(i,o){jQuery.fn[o]=3Dfunction(f){return = this.bind(o,f);};});var = jsc=3Dnow();jQuery.extend({get:function(url,data,callback,type){if(jQuery= .isFunction(data)){callback=3Ddata;data=3Dnull;}return = jQuery.ajax({type:"GET",url:url,data:data,success:callback,dataType:type}= );},getScript:function(url,callback){return = jQuery.get(url,null,callback,"script");},getJSON:function(url,data,callba= ck){return = jQuery.get(url,data,callback,"json");},post:function(url,data,callback,ty= pe){if(jQuery.isFunction(data)){callback=3Ddata;data=3D{};}return = jQuery.ajax({type:"POST",url:url,data:data,success:callback,dataType:type= });},ajaxSetup:function(settings){jQuery.extend(jQuery.ajaxSettings,setti= ngs);},ajaxSettings:{url:location.href,global:true,type:"GET",timeout:0,c= ontentType:"application/x-www-form-urlencoded",processData:true,async:tru= e,data:null,username:null,password:null,accepts:{xml:"application/xml, = text/xml",html:"text/html",script:"text/javascript, = application/javascript",json:"application/json, = text/javascript",text:"text/plain",_default:"*/*"}},lastModified:{},ajax:= function(s){s=3DjQuery.extend(true,s,jQuery.extend(true,{},jQuery.ajaxSet= tings,s));var = jsonp,jsre=3D/=3D\?(&|$)/g,status,data,type=3Ds.type.toUpperCase();if(s.d= ata&&s.processData&&typeof = s.data!=3D"string")s.data=3DjQuery.param(s.data);if(s.dataType=3D=3D"json= p"){if(type=3D=3D"GET"){if(!s.url.match(jsre))s.url+=3D(s.url.match(/\?/)= ?"&":"?")+(s.jsonp||"callback")+"=3D?";}else = if(!s.data||!s.data.match(jsre))s.data=3D(s.data?s.data+"&":"")+(s.jsonp|= |"callback")+"=3D?";s.dataType=3D"json";}if(s.dataType=3D=3D"json"&&(s.da= ta&&s.data.match(jsre)||s.url.match(jsre))){jsonp=3D"jsonp"+jsc++;if(s.da= ta)s.data=3D(s.data+"").replace(jsre,"=3D"+jsonp+"$1");s.url=3Ds.url.repl= ace(jsre,"=3D"+jsonp+"$1");s.dataType=3D"script";window[jsonp]=3Dfunction= (tmp){data=3Dtmp;success();complete();window[jsonp]=3Dundefined;try{delet= e = window[jsonp];}catch(e){}if(head)head.removeChild(script);};}if(s.dataTyp= e=3D=3D"script"&&s.cache=3D=3Dnull)s.cache=3Dfalse;if(s.cache=3D=3D=3Dfal= se&&type=3D=3D"GET"){var ts=3Dnow();var = ret=3Ds.url.replace(/(\?|&)_=3D.*?(&|$)/,"$1_=3D"+ts+"$2");s.url=3Dret+((= ret=3D=3Ds.url)?(s.url.match(/\?/)?"&":"?")+"_=3D"+ts:"");}if(s.data&&typ= e=3D=3D"GET"){s.url+=3D(s.url.match(/\?/)?"&":"?")+s.data;s.data=3Dnull;}= if(s.global&&!jQuery.active++)jQuery.event.trigger("ajaxStart");var = remote=3D/^(?:\w+:)?\/\/([^\/?#]+)/;if(s.dataType=3D=3D"script"&&type=3D=3D= "GET"&&remote.test(s.url)&&remote.exec(s.url)[1]!=3Dlocation.host){var = head=3Ddocument.getElementsByTagName("head")[0];var = script=3Ddocument.createElement("script");script.src=3Ds.url;if(s.scriptC= harset)script.charset=3Ds.scriptCharset;if(!jsonp){var = done=3Dfalse;script.onload=3Dscript.onreadystatechange=3Dfunction(){if(!d= one&&(!this.readyState||this.readyState=3D=3D"loaded"||this.readyState=3D= =3D"complete")){done=3Dtrue;success();complete();head.removeChild(script)= ;}};}head.appendChild(script);return undefined;}var = requestDone=3Dfalse;var xhr=3Dwindow.ActiveXObject?new = ActiveXObject("Microsoft.XMLHTTP"):new = XMLHttpRequest();if(s.username)xhr.open(type,s.url,s.async,s.username,s.p= assword);else=0A= xhr.open(type,s.url,s.async);try{if(s.data)xhr.setRequestHeader("Content-= Type",s.contentType);if(s.ifModified)xhr.setRequestHeader("If-Modified-Si= nce",jQuery.lastModified[s.url]||"Thu, 01 Jan 1970 00:00:00 = GMT");xhr.setRequestHeader("X-Requested-With","XMLHttpRequest");xhr.setRe= questHeader("Accept",s.dataType&&s.accepts[s.dataType]?s.accepts[s.dataTy= pe]+", = */*":s.accepts._default);}catch(e){}if(s.beforeSend&&s.beforeSend(xhr,s)=3D= =3D=3Dfalse){s.global&&jQuery.active--;xhr.abort();return = false;}if(s.global)jQuery.event.trigger("ajaxSend",[xhr,s]);var = onreadystatechange=3Dfunction(isTimeout){if(!requestDone&&xhr&&(xhr.ready= State=3D=3D4||isTimeout=3D=3D"timeout")){requestDone=3Dtrue;if(ival){clea= rInterval(ival);ival=3Dnull;}status=3DisTimeout=3D=3D"timeout"&&"timeout"= ||!jQuery.httpSuccess(xhr)&&"error"||s.ifModified&&jQuery.httpNotModified= (xhr,s.url)&&"notmodified"||"success";if(status=3D=3D"success"){try{data=3D= jQuery.httpData(xhr,s.dataType,s.dataFilter);}catch(e){status=3D"parserer= ror";}}if(status=3D=3D"success"){var = modRes;try{modRes=3Dxhr.getResponseHeader("Last-Modified");}catch(e){}if(= s.ifModified&&modRes)jQuery.lastModified[s.url]=3DmodRes;if(!jsonp)succes= s();}else=0A= jQuery.handleError(s,xhr,status);complete();if(s.async)xhr=3Dnull;}};if(s= .async){var = ival=3DsetInterval(onreadystatechange,13);if(s.timeout>0)setTimeout(funct= ion(){if(xhr){xhr.abort();if(!requestDone)onreadystatechange("timeout");}= },s.timeout);}try{xhr.send(s.data);}catch(e){jQuery.handleError(s,xhr,nul= l,e);}if(!s.async)onreadystatechange();function = success(){if(s.success)s.success(data,status);if(s.global)jQuery.event.tr= igger("ajaxSuccess",[xhr,s]);}function = complete(){if(s.complete)s.complete(xhr,status);if(s.global)jQuery.event.= trigger("ajaxComplete",[xhr,s]);if(s.global&&!--jQuery.active)jQuery.even= t.trigger("ajaxStop");}return = xhr;},handleError:function(s,xhr,status,e){if(s.error)s.error(xhr,status,= e);if(s.global)jQuery.event.trigger("ajaxError",[xhr,s,e]);},active:0,htt= pSuccess:function(xhr){try{return!xhr.status&&location.protocol=3D=3D"fil= e:"||(xhr.status>=3D200&&xhr.status<300)||xhr.status=3D=3D304||xhr.status= =3D=3D1223||jQuery.browser.safari&&xhr.status=3D=3Dundefined;}catch(e){}r= eturn false;},httpNotModified:function(xhr,url){try{var = xhrRes=3Dxhr.getResponseHeader("Last-Modified");return = xhr.status=3D=3D304||xhrRes=3D=3DjQuery.lastModified[url]||jQuery.browser= .safari&&xhr.status=3D=3Dundefined;}catch(e){}return = false;},httpData:function(xhr,type,filter){var = ct=3Dxhr.getResponseHeader("content-type"),xml=3Dtype=3D=3D"xml"||!type&&= ct&&ct.indexOf("xml")>=3D0,data=3Dxml?xhr.responseXML:xhr.responseText;if= (xml&&data.documentElement.tagName=3D=3D"parsererror")throw"parsererror";= if(filter)data=3Dfilter(data,type);if(type=3D=3D"script")jQuery.globalEva= l(data);if(type=3D=3D"json")data=3Deval("("+data+")");return = data;},param:function(a){var = s=3D[];if(a.constructor=3D=3DArray||a.jquery)jQuery.each(a,function(){s.p= ush(encodeURIComponent(this.name)+"=3D"+encodeURIComponent(this.value));}= );else=0A= for(var j in = a)if(a[j]&&a[j].constructor=3D=3DArray)jQuery.each(a[j],function(){s.push= (encodeURIComponent(j)+"=3D"+encodeURIComponent(this));});else=0A= s.push(encodeURIComponent(j)+"=3D"+encodeURIComponent(jQuery.isFunction(a= [j])?a[j]():a[j]));return = s.join("&").replace(/%20/g,"+");}});jQuery.fn.extend({show:function(speed= ,callback){return = speed?this.animate({height:"show",width:"show",opacity:"show"},speed,call= back):this.filter(":hidden").each(function(){this.style.display=3Dthis.ol= dblock||"";if(jQuery.css(this,"display")=3D=3D"none"){var = elem=3DjQuery("<"+this.tagName+" = />").appendTo("body");this.style.display=3Delem.css("display");if(this.st= yle.display=3D=3D"none")this.style.display=3D"block";elem.remove();}}).en= d();},hide:function(speed,callback){return = speed?this.animate({height:"hide",width:"hide",opacity:"hide"},speed,call= back):this.filter(":visible").each(function(){this.oldblock=3Dthis.oldblo= ck||jQuery.css(this,"display");this.style.display=3D"none";}).end();},_to= ggle:jQuery.fn.toggle,toggle:function(fn,fn2){return = jQuery.isFunction(fn)&&jQuery.isFunction(fn2)?this._toggle.apply(this,arg= uments):fn?this.animate({height:"toggle",width:"toggle",opacity:"toggle"}= ,fn,fn2):this.each(function(){jQuery(this)[jQuery(this).is(":hidden")?"sh= ow":"hide"]();});},slideDown:function(speed,callback){return = this.animate({height:"show"},speed,callback);},slideUp:function(speed,cal= lback){return = this.animate({height:"hide"},speed,callback);},slideToggle:function(speed= ,callback){return = this.animate({height:"toggle"},speed,callback);},fadeIn:function(speed,ca= llback){return = this.animate({opacity:"show"},speed,callback);},fadeOut:function(speed,ca= llback){return = this.animate({opacity:"hide"},speed,callback);},fadeTo:function(speed,to,= callback){return = this.animate({opacity:to},speed,callback);},animate:function(prop,speed,e= asing,callback){var optall=3DjQuery.speed(speed,easing,callback);return = this[optall.queue=3D=3D=3Dfalse?"each":"queue"](function(){if(this.nodeTy= pe!=3D1)return false;var = opt=3DjQuery.extend({},optall),p,hidden=3DjQuery(this).is(":hidden"),self= =3Dthis;for(p in = prop){if(prop[p]=3D=3D"hide"&&hidden||prop[p]=3D=3D"show"&&!hidden)return= = opt.complete.call(this);if(p=3D=3D"height"||p=3D=3D"width"){opt.display=3D= jQuery.css(this,"display");opt.overflow=3Dthis.style.overflow;}}if(opt.ov= erflow!=3Dnull)this.style.overflow=3D"hidden";opt.curAnim=3DjQuery.extend= ({},prop);jQuery.each(prop,function(name,val){var e=3Dnew = jQuery.fx(self,opt,name);if(/toggle|show|hide/.test(val))e[val=3D=3D"togg= le"?hidden?"show":"hide":val](prop);else{var = parts=3Dval.toString().match(/^([+-]=3D)?([\d+-.]+)(.*)$/),start=3De.cur(= true)||0;if(parts){var = end=3DparseFloat(parts[2]),unit=3Dparts[3]||"px";if(unit!=3D"px"){self.st= yle[name]=3D(end||1)+unit;start=3D((end||1)/e.cur(true))*start;self.style= [name]=3Dstart+unit;}if(parts[1])end=3D((parts[1]=3D=3D"-=3D"?-1:1)*end)+= start;e.custom(start,end,unit);}else=0A= e.custom(start,val,"");}});return = true;});},queue:function(type,fn){if(jQuery.isFunction(type)||(type&&type= .constructor=3D=3DArray)){fn=3Dtype;type=3D"fx";}if(!type||(typeof = type=3D=3D"string"&&!fn))return queue(this[0],type);return = this.each(function(){if(fn.constructor=3D=3DArray)queue(this,type,fn);els= e{queue(this,type).push(fn);if(queue(this,type).length=3D=3D1)fn.call(thi= s);}});},stop:function(clearQueue,gotoEnd){var = timers=3DjQuery.timers;if(clearQueue)this.queue([]);this.each(function(){= for(var = i=3Dtimers.length-1;i>=3D0;i--)if(timers[i].elem=3D=3Dthis){if(gotoEnd)ti= mers[i](true);timers.splice(i,1);}});if(!gotoEnd)this.dequeue();return = this;}});var = queue=3Dfunction(elem,type,array){if(elem){type=3Dtype||"fx";var = q=3DjQuery.data(elem,type+"queue");if(!q||array)q=3DjQuery.data(elem,type= +"queue",jQuery.makeArray(array));}return = q;};jQuery.fn.dequeue=3Dfunction(type){type=3Dtype||"fx";return = this.each(function(){var = q=3Dqueue(this,type);q.shift();if(q.length)q[0].call(this);});};jQuery.ex= tend({speed:function(speed,easing,fn){var = opt=3Dspeed&&speed.constructor=3D=3DObject?speed:{complete:fn||!fn&&easin= g||jQuery.isFunction(speed)&&speed,duration:speed,easing:fn&&easing||easi= ng&&easing.constructor!=3DFunction&&easing};opt.duration=3D(opt.duration&= &opt.duration.constructor=3D=3DNumber?opt.duration:jQuery.fx.speeds[opt.d= uration])||jQuery.fx.speeds.def;opt.old=3Dopt.complete;opt.complete=3Dfun= ction(){if(opt.queue!=3D=3Dfalse)jQuery(this).dequeue();if(jQuery.isFunct= ion(opt.old))opt.old.call(this);};return = opt;},easing:{linear:function(p,n,firstNum,diff){return = firstNum+diff*p;},swing:function(p,n,firstNum,diff){return((-Math.cos(p*M= ath.PI)/2)+0.5)*diff+firstNum;}},timers:[],timerId:null,fx:function(elem,= options,prop){this.options=3Doptions;this.elem=3Delem;this.prop=3Dprop;if= (!options.orig)options.orig=3D{};}});jQuery.fx.prototype=3D{update:functi= on(){if(this.options.step)this.options.step.call(this.elem,this.now,this)= ;(jQuery.fx.step[this.prop]||jQuery.fx.step._default)(this);if(this.prop=3D= =3D"height"||this.prop=3D=3D"width")this.elem.style.display=3D"block";},c= ur:function(force){if(this.elem[this.prop]!=3Dnull&&this.elem.style[this.= prop]=3D=3Dnull)return this.elem[this.prop];var = r=3DparseFloat(jQuery.css(this.elem,this.prop,force));return = r&&r>-10000?r:parseFloat(jQuery.curCSS(this.elem,this.prop))||0;},custom:= function(from,to,unit){this.startTime=3Dnow();this.start=3Dfrom;this.end=3D= to;this.unit=3Dunit||this.unit||"px";this.now=3Dthis.start;this.pos=3Dthi= s.state=3D0;this.update();var self=3Dthis;function t(gotoEnd){return = self.step(gotoEnd);}t.elem=3Dthis.elem;jQuery.timers.push(t);if(jQuery.ti= merId=3D=3Dnull){jQuery.timerId=3DsetInterval(function(){var = timers=3DjQuery.timers;for(var = i=3D0;ithis.options.duration+this.startTime){this.now=3D= this.end;this.pos=3Dthis.state=3D1;this.update();this.options.curAnim[thi= s.prop]=3Dtrue;var done=3Dtrue;for(var i in = this.options.curAnim)if(this.options.curAnim[i]!=3D=3Dtrue)done=3Dfalse;i= f(done){if(this.options.display!=3Dnull){this.elem.style.overflow=3Dthis.= options.overflow;this.elem.style.display=3Dthis.options.display;if(jQuery= .css(this.elem,"display")=3D=3D"none")this.elem.style.display=3D"block";}= if(this.options.hide)this.elem.style.display=3D"none";if(this.options.hid= e||this.options.show)for(var p in = this.options.curAnim)jQuery.attr(this.elem.style,p,this.options.orig[p]);= }if(done)this.options.complete.call(this.elem);return false;}else{var = n=3Dt-this.startTime;this.state=3Dn/this.options.duration;this.pos=3DjQue= ry.easing[this.options.easing||(jQuery.easing.swing?"swing":"linear")](th= is.state,n,0,1,this.options.duration);this.now=3Dthis.start+((this.end-th= is.start)*this.pos);this.update();}return = true;}};jQuery.extend(jQuery.fx,{speeds:{slow:600,fast:200,def:400},step:= {scrollLeft:function(fx){fx.elem.scrollLeft=3Dfx.now;},scrollTop:function= (fx){fx.elem.scrollTop=3Dfx.now;},opacity:function(fx){jQuery.attr(fx.ele= m.style,"opacity",fx.now);},_default:function(fx){fx.elem.style[fx.prop]=3D= fx.now+fx.unit;}}});jQuery.fn.offset=3Dfunction(){var = left=3D0,top=3D0,elem=3Dthis[0],results;if(elem)with(jQuery.browser){var = parent=3Delem.parentNode,offsetChild=3Delem,offsetParent=3Delem.offsetPar= ent,doc=3Delem.ownerDocument,safari2=3Dsafari&&parseInt(version)<522&&!/a= dobeair/i.test(userAgent),css=3DjQuery.curCSS,fixed=3Dcss(elem,"position"= )=3D=3D"fixed";if(elem.getBoundingClientRect){var = box=3Delem.getBoundingClientRect();add(box.left+Math.max(doc.documentElem= ent.scrollLeft,doc.body.scrollLeft),box.top+Math.max(doc.documentElement.= scrollTop,doc.body.scrollTop));add(-doc.documentElement.clientLeft,-doc.d= ocumentElement.clientTop);}else{add(elem.offsetLeft,elem.offsetTop);while= (offsetParent){add(offsetParent.offsetLeft,offsetParent.offsetTop);if(moz= illa&&!/^t(able|d|h)$/i.test(offsetParent.tagName)||safari&&!safari2)bord= er(offsetParent);if(!fixed&&css(offsetParent,"position")=3D=3D"fixed")fix= ed=3Dtrue;offsetChild=3D/^body$/i.test(offsetParent.tagName)?offsetChild:= offsetParent;offsetParent=3DoffsetParent.offsetParent;}while(parent&&pare= nt.tagName&&!/^body|html$/i.test(parent.tagName)){if(!/^inline|table.*$/i= .test(css(parent,"display")))add(-parent.scrollLeft,-parent.scrollTop);if= (mozilla&&css(parent,"overflow")!=3D"visible")border(parent);parent=3Dpar= ent.parentNode;}if((safari2&&(fixed||css(offsetChild,"position")=3D=3D"ab= solute"))||(mozilla&&css(offsetChild,"position")!=3D"absolute"))add(-doc.= body.offsetLeft,-doc.body.offsetTop);if(fixed)add(Math.max(doc.documentEl= ement.scrollLeft,doc.body.scrollLeft),Math.max(doc.documentElement.scroll= Top,doc.body.scrollTop));}results=3D{top:top,left:left};}function = border(elem){add(jQuery.curCSS(elem,"borderLeftWidth",true),jQuery.curCSS= (elem,"borderTopWidth",true));}function = add(l,t){left+=3DparseInt(l,10)||0;top+=3DparseInt(t,10)||0;}return = results;};jQuery.fn.extend({position:function(){var = left=3D0,top=3D0,results;if(this[0]){var = offsetParent=3Dthis.offsetParent(),offset=3Dthis.offset(),parentOffset=3D= /^body|html$/i.test(offsetParent[0].tagName)?{top:0,left:0}:offsetParent.= offset();offset.top-=3Dnum(this,'marginTop');offset.left-=3Dnum(this,'mar= ginLeft');parentOffset.top+=3Dnum(offsetParent,'borderTopWidth');parentOf= fset.left+=3Dnum(offsetParent,'borderLeftWidth');results=3D{top:offset.to= p-parentOffset.top,left:offset.left-parentOffset.left};}return = results;},offsetParent:function(){var = offsetParent=3Dthis[0].offsetParent;while(offsetParent&&(!/^body|html$/i.= test(offsetParent.tagName)&&jQuery.css(offsetParent,'position')=3D=3D'sta= tic'))offsetParent=3DoffsetParent.offsetParent;return = jQuery(offsetParent);}});jQuery.each(['Left','Top'],function(i,name){var = method=3D'scroll'+name;jQuery.fn[method]=3Dfunction(val){if(!this[0])retu= rn;return = val!=3Dundefined?this.each(function(){this=3D=3Dwindow||this=3D=3Ddocumen= t?window.scrollTo(!i?val:jQuery(window).scrollLeft(),i?val:jQuery(window)= .scrollTop()):this[method]=3Dval;}):this[0]=3D=3Dwindow||this[0]=3D=3Ddoc= ument?self[i?'pageYOffset':'pageXOffset']||jQuery.boxModel&&document.docu= mentElement[method]||document.body[method]:this[0][method];};});jQuery.ea= ch(["Height","Width"],function(i,name){var = tl=3Di?"Left":"Top",br=3Di?"Right":"Bottom";jQuery.fn["inner"+name]=3Dfun= ction(){return = this[name.toLowerCase()]()+num(this,"padding"+tl)+num(this,"padding"+br);= };jQuery.fn["outer"+name]=3Dfunction(margin){return = this["inner"+name]()+num(this,"border"+tl+"Width")+num(this,"border"+br+"= Width")+(margin?num(this,"margin"+tl)+num(this,"margin"+br):0);};});})(); ------=_NextPart_000_0000_01CD97FF.95565490 Content-Type: application/octet-stream Content-Transfer-Encoding: quoted-printable Content-Location: http://www.google-analytics.com/urchin.js //-- Google Analytics Urchin Module=0A= //-- Copyright 2007 Google, All Rights Reserved.=0A= =0A= //-- Urchin On Demand Settings ONLY=0A= var _uacct=3D""; // set up the Urchin Account=0A= var _userv=3D1; // service mode (0=3Dlocal,1=3Dremote,2=3Dboth)=0A= =0A= //-- UTM User Settings=0A= var _ufsc=3D1; // set client info flag (1=3Don|0=3Doff)=0A= var _udn=3D"auto"; // (auto|none|domain) set the domain name for cookies=0A= var _uhash=3D"on"; // (on|off) unique domain hash for cookies=0A= var _utimeout=3D"1800"; // set the inactive session timeout in seconds=0A= var _ugifpath=3D"/__utm.gif"; // set the web path to the __utm.gif file=0A= var _utsp=3D"|"; // transaction field separator=0A= var _uflash=3D1; // set flash version detect option (1=3Don|0=3Doff)=0A= var _utitle=3D1; // set the document title detect option = (1=3Don|0=3Doff)=0A= var _ulink=3D0; // enable linker functionality (1=3Don|0=3Doff)=0A= var _uanchor=3D0; // enable use of anchors for campaign = (1=3Don|0=3Doff)=0A= var _utcp=3D"/"; // the cookie path for tracking=0A= var _usample=3D100; // The sampling % of visitors to track (1-100).=0A= =0A= //-- UTM Campaign Tracking Settings=0A= var _uctm=3D1; // set campaign tracking module (1=3Don|0=3Doff)=0A= var _ucto=3D"15768000"; // set timeout in seconds (6 month default)=0A= var _uccn=3D"utm_campaign"; // name=0A= var _ucmd=3D"utm_medium"; // medium (cpc|cpm|link|email|organic)=0A= var _ucsr=3D"utm_source"; // source=0A= var _uctr=3D"utm_term"; // term/keyword=0A= var _ucct=3D"utm_content"; // content=0A= var _ucid=3D"utm_id"; // id number=0A= var _ucno=3D"utm_nooverride"; // don't override=0A= =0A= //-- Auto/Organic Sources and Keywords=0A= var _uOsr=3Dnew Array();=0A= var _uOkw=3Dnew Array();=0A= _uOsr[0]=3D"google"; _uOkw[0]=3D"q";=0A= _uOsr[1]=3D"yahoo"; _uOkw[1]=3D"p";=0A= _uOsr[2]=3D"msn"; _uOkw[2]=3D"q";=0A= _uOsr[3]=3D"aol"; _uOkw[3]=3D"query";=0A= _uOsr[4]=3D"aol"; _uOkw[4]=3D"encquery";=0A= _uOsr[5]=3D"lycos"; _uOkw[5]=3D"query";=0A= _uOsr[6]=3D"ask"; _uOkw[6]=3D"q";=0A= _uOsr[7]=3D"altavista"; _uOkw[7]=3D"q";=0A= _uOsr[8]=3D"netscape"; _uOkw[8]=3D"query";=0A= _uOsr[9]=3D"cnn"; _uOkw[9]=3D"query";=0A= _uOsr[10]=3D"looksmart"; _uOkw[10]=3D"qt";=0A= _uOsr[11]=3D"about"; _uOkw[11]=3D"terms";=0A= _uOsr[12]=3D"mamma"; _uOkw[12]=3D"query";=0A= _uOsr[13]=3D"alltheweb"; _uOkw[13]=3D"q";=0A= _uOsr[14]=3D"gigablast"; _uOkw[14]=3D"q";=0A= _uOsr[15]=3D"voila"; _uOkw[15]=3D"rdata";=0A= _uOsr[16]=3D"virgilio"; _uOkw[16]=3D"qs";=0A= _uOsr[17]=3D"live"; _uOkw[17]=3D"q";=0A= _uOsr[18]=3D"baidu"; _uOkw[18]=3D"wd";=0A= _uOsr[19]=3D"alice"; _uOkw[19]=3D"qs";=0A= _uOsr[20]=3D"yandex"; _uOkw[20]=3D"text";=0A= _uOsr[21]=3D"najdi"; _uOkw[21]=3D"q";=0A= _uOsr[22]=3D"aol"; _uOkw[22]=3D"q";=0A= _uOsr[23]=3D"club-internet"; _uOkw[23]=3D"query";=0A= _uOsr[24]=3D"mama"; _uOkw[24]=3D"query";=0A= _uOsr[25]=3D"seznam"; _uOkw[25]=3D"q";=0A= _uOsr[26]=3D"search"; _uOkw[26]=3D"q";=0A= _uOsr[27]=3D"wp"; _uOkw[27]=3D"szukaj";=0A= _uOsr[28]=3D"onet"; _uOkw[28]=3D"qt";=0A= _uOsr[29]=3D"netsprint"; _uOkw[29]=3D"q";=0A= _uOsr[30]=3D"google.interia"; _uOkw[30]=3D"q";=0A= _uOsr[31]=3D"szukacz"; _uOkw[31]=3D"q";=0A= _uOsr[32]=3D"yam"; _uOkw[32]=3D"k";=0A= _uOsr[33]=3D"pchome"; _uOkw[33]=3D"q";=0A= _uOsr[34]=3D"kvasir"; _uOkw[34]=3D"searchExpr";=0A= _uOsr[35]=3D"sesam"; _uOkw[35]=3D"q";=0A= _uOsr[36]=3D"ozu"; _uOkw[36]=3D"q";=0A= _uOsr[37]=3D"terra"; _uOkw[37]=3D"query";=0A= _uOsr[38]=3D"nostrum"; _uOkw[38]=3D"query";=0A= _uOsr[39]=3D"mynet"; _uOkw[39]=3D"q";=0A= _uOsr[40]=3D"ekolay"; _uOkw[40]=3D"q";=0A= _uOsr[41]=3D"search.ilse"; _uOkw[41]=3D"search_for";=0A= _uOsr[42]=3D"bing"; _uOkw[42]=3D"q";=0A= =0A= //-- Auto/Organic Keywords to Ignore=0A= var _uOno=3Dnew Array();=0A= //_uOno[0]=3D"urchin";=0A= //_uOno[1]=3D"urchin.com";=0A= //_uOno[2]=3D"www.urchin.com";=0A= =0A= //-- Referral domains to Ignore=0A= var _uRno=3Dnew Array();=0A= //_uRno[0]=3D".urchin.com";=0A= =0A= //-- **** Don't modify below this point ***=0A= var = _uff,_udh,_udt,_ubl=3D0,_udo=3D"",_uu,_ufns=3D0,_uns=3D0,_ur=3D"-",_ufno=3D= 0,_ust=3D0,_ubd=3Ddocument,_udl=3D_ubd.location,_udlh=3D"",_uwv=3D"1.4";=0A= var _ugifpath2=3D"http://www.google-analytics.com/__utm.gif";=0A= if (_udl.hash) _udlh=3D_udl.href.substring(_udl.href.indexOf('#'));=0A= if (_udl.protocol=3D=3D"https:") = _ugifpath2=3D"https://ssl.google-analytics.com/__utm.gif";=0A= if (!_utcp || _utcp=3D=3D"") _utcp=3D"/";=0A= function urchinTracker(page) {=0A= if (_udl.protocol=3D=3D"file:") return;=0A= if (_uff && (!page || page=3D=3D"")) return;=0A= var a,b,c,xx,v,z,k,x=3D"",s=3D"",f=3D0,nv=3D0;=0A= var nx=3D" expires=3D"+_uNx()+";";=0A= var dc=3D_ubd.cookie;=0A= _udh=3D_uDomain();=0A= if (!_uVG()) return;=0A= _uu=3DMath.round(Math.random()*2147483647);=0A= _udt=3Dnew Date();=0A= _ust=3DMath.round(_udt.getTime()/1000);=0A= a=3Ddc.indexOf("__utma=3D"+_udh+".");=0A= b=3Ddc.indexOf("__utmb=3D"+_udh);=0A= c=3Ddc.indexOf("__utmc=3D"+_udh);=0A= if (_udn && _udn!=3D"") { _udo=3D" domain=3D"+_udn+";"; }=0A= if (_utimeout && _utimeout!=3D"") {=0A= x=3Dnew Date(_udt.getTime()+(_utimeout*1000));=0A= x=3D" expires=3D"+x.toGMTString()+";";=0A= }=0A= if (_ulink) {=0A= if (_uanchor && _udlh && _udlh!=3D"") s=3D_udlh+"&";=0A= s+=3D_udl.search;=0A= if(s && s!=3D"" && s.indexOf("__utma=3D")>=3D0) {=0A= if (!(_uIN(a=3D_uGC(s,"__utma=3D","&")))) a=3D"-";=0A= if (!(_uIN(b=3D_uGC(s,"__utmb=3D","&")))) b=3D"-";=0A= if (!(_uIN(c=3D_uGC(s,"__utmc=3D","&")))) c=3D"-";=0A= v=3D_uGC(s,"__utmv=3D","&");=0A= z=3D_uGC(s,"__utmz=3D","&");=0A= k=3D_uGC(s,"__utmk=3D","&");=0A= xx=3D_uGC(s,"__utmx=3D","&");=0A= if ((k*1) !=3D ((_uHash(a+b+c+xx+z+v)*1)+(_udh*1))) = {_ubl=3D1;a=3D"-";b=3D"-";c=3D"-";xx=3D"-";z=3D"-";v=3D"-";}=0A= if (a!=3D"-" && b!=3D"-" && c!=3D"-") f=3D1;=0A= else if(a!=3D"-") f=3D2;=0A= }=0A= }=0A= if(f=3D=3D1) {=0A= _ubd.cookie=3D"__utma=3D"+a+"; path=3D"+_utcp+";"+nx+_udo;=0A= _ubd.cookie=3D"__utmb=3D"+b+"; path=3D"+_utcp+";"+x+_udo;=0A= _ubd.cookie=3D"__utmc=3D"+c+"; path=3D"+_utcp+";"+_udo;=0A= } else if (f=3D=3D2) {=0A= a=3D_uFixA(s,"&",_ust);=0A= _ubd.cookie=3D"__utma=3D"+a+"; path=3D"+_utcp+";"+nx+_udo;=0A= _ubd.cookie=3D"__utmb=3D"+_udh+"; path=3D"+_utcp+";"+x+_udo;=0A= _ubd.cookie=3D"__utmc=3D"+_udh+"; path=3D"+_utcp+";"+_udo;=0A= _ufns=3D1;=0A= } else if (a>=3D0 && b>=3D0 && c>=3D0) {=0A= b =3D _uGC(dc,"__utmb=3D"+_udh,";");=0A= b =3D ("-" =3D=3D b) ? _udh : b; =0A= _ubd.cookie=3D"__utmb=3D"+b+"; path=3D"+_utcp+";"+x+_udo;=0A= } else {=0A= if (a>=3D0) a=3D_uFixA(_ubd.cookie,";",_ust);=0A= else {=0A= a=3D_udh+"."+_uu+"."+_ust+"."+_ust+"."+_ust+".1";=0A= nv=3D1;=0A= }=0A= _ubd.cookie=3D"__utma=3D"+a+"; path=3D"+_utcp+";"+nx+_udo;=0A= _ubd.cookie=3D"__utmb=3D"+_udh+"; path=3D"+_utcp+";"+x+_udo;=0A= _ubd.cookie=3D"__utmc=3D"+_udh+"; path=3D"+_utcp+";"+_udo;=0A= _ufns=3D1;=0A= }=0A= if (_ulink && xx && xx!=3D"" && xx!=3D"-") {=0A= xx=3D_uUES(xx);=0A= if (xx.indexOf(";")=3D=3D-1) _ubd.cookie=3D"__utmx=3D"+xx+"; = path=3D"+_utcp+";"+nx+_udo;=0A= }=0A= if (_ulink && v && v!=3D"" && v!=3D"-") {=0A= v=3D_uUES(v);=0A= if (v.indexOf(";")=3D=3D-1) _ubd.cookie=3D"__utmv=3D"+v+"; = path=3D"+_utcp+";"+nx+_udo;=0A= }=0A= var wc=3Dwindow;=0A= var c=3D_ubd.cookie;=0A= if(wc && wc.gaGlobal && wc.gaGlobal.dh=3D=3D_udh){=0A= var g=3Dwc.gaGlobal;=0A= var ua=3Dc.split("__utma=3D"+_udh+".")[1].split(";")[0].split(".");=0A= if(g.sid)ua[3]=3Dg.sid;=0A= if(nv>0){=0A= ua[2]=3Dua[3];=0A= if(g.vid){=0A= var v=3Dg.vid.split(".");=0A= ua[0]=3Dv[0];=0A= ua[1]=3Dv[1];=0A= }=0A= }=0A= _ubd.cookie=3D"__utma=3D"+_udh+"."+ua.join(".")+"; = path=3D"+_utcp+";"+nx+_udo;=0A= }=0A= _uInfo(page);=0A= _ufns=3D0;=0A= _ufno=3D0;=0A= if (!page || page=3D=3D"") _uff=3D1;=0A= }=0A= function _uGH() {=0A= var hid;=0A= var wc=3Dwindow;=0A= if (wc && wc.gaGlobal && wc.gaGlobal.hid) {=0A= hid=3Dwc.gaGlobal.hid;=0A= } else {=0A= hid=3DMath.round(Math.random()*0x7fffffff);=0A= if (!wc.gaGlobal) wc.gaGlobal=3D{};=0A= wc.gaGlobal.hid=3Dhid;=0A= }=0A= return hid;=0A= }=0A= function _uInfo(page) {=0A= var p,s=3D"",dm=3D"",pg=3D_udl.pathname+_udl.search;=0A= if (page && page!=3D"") pg=3D_uES(page,1);=0A= _ur=3D_ubd.referrer;=0A= if (!_ur || _ur=3D=3D"") { _ur=3D"-"; }=0A= else {=0A= dm=3D_ubd.domain;=0A= if(_utcp && _utcp!=3D"/") dm+=3D_utcp;=0A= p=3D_ur.indexOf(dm);=0A= if ((p>=3D0) && (p<=3D8)) { _ur=3D"0"; }=0A= if (_ur.indexOf("[")=3D=3D0 && = _ur.lastIndexOf("]")=3D=3D(_ur.length-1)) { _ur=3D"-"; }=0A= }=0A= s+=3D"&utmn=3D"+_uu;=0A= if (_ufsc) s+=3D_uBInfo();=0A= if (_uctm) s+=3D_uCInfo();=0A= if (_utitle && _ubd.title && _ubd.title!=3D"") = s+=3D"&utmdt=3D"+_uES(_ubd.title);=0A= if (_udl.hostname && _udl.hostname!=3D"") = s+=3D"&utmhn=3D"+_uES(_udl.hostname);=0A= if (_usample && _usample !=3D 100) s+=3D"&utmsp=3D"+_uES(_usample);=0A= s+=3D"&utmhid=3D"+_uGH();=0A= s+=3D"&utmr=3D"+_ur;=0A= s+=3D"&utmp=3D"+pg;=0A= if ((_userv=3D=3D0 || _userv=3D=3D2) && _uSP()) {=0A= var i=3Dnew Image(1,1);=0A= i.src=3D_ugifpath+"?"+"utmwv=3D"+_uwv+s;=0A= i.onload=3Dfunction() { _uVoid(); }=0A= }=0A= if ((_userv=3D=3D1 || _userv=3D=3D2) && _uSP()) {=0A= var i2=3Dnew Image(1,1);=0A= = i2.src=3D_ugifpath2+"?"+"utmwv=3D"+_uwv+s+"&utmac=3D"+_uacct+"&utmcc=3D"+= _uGCS();=0A= i2.onload=3Dfunction() { _uVoid(); }=0A= }=0A= return;=0A= }=0A= function _uVoid() { return; }=0A= function _uCInfo() {=0A= if (!_ucto || _ucto=3D=3D"") { _ucto=3D"15768000"; }=0A= if (!_uVG()) return;=0A= var = c=3D"",t=3D"-",t2=3D"-",t3=3D"-",o=3D0,cs=3D0,cn=3D0,i=3D0,z=3D"-",s=3D""= ;=0A= if (_uanchor && _udlh && _udlh!=3D"") s=3D_udlh+"&";=0A= s+=3D_udl.search;=0A= var x=3Dnew Date(_udt.getTime()+(_ucto*1000));=0A= var dc=3D_ubd.cookie;=0A= x=3D" expires=3D"+x.toGMTString()+";";=0A= if (_ulink && !_ubl) {=0A= z=3D_uUES(_uGC(s,"__utmz=3D","&"));=0A= if (z!=3D"-" && z.indexOf(";")=3D=3D-1) { = _ubd.cookie=3D"__utmz=3D"+z+"; path=3D"+_utcp+";"+x+_udo; return ""; }=0A= }=0A= z=3Ddc.indexOf("__utmz=3D"+_udh+".");=0A= if (z>-1) { z=3D_uGC(dc,"__utmz=3D"+_udh+".",";"); }=0A= else { z=3D"-"; }=0A= t=3D_uGC(s,_ucid+"=3D","&");=0A= t2=3D_uGC(s,_ucsr+"=3D","&");=0A= t3=3D_uGC(s,"gclid=3D","&");=0A= if ((t!=3D"-" && t!=3D"") || (t2!=3D"-" && t2!=3D"") || (t3!=3D"-" && = t3!=3D"")) {=0A= if (t!=3D"-" && t!=3D"") c+=3D"utmcid=3D"+_uEC(t);=0A= if (t2!=3D"-" && t2!=3D"") { if (c !=3D "") c+=3D"|"; = c+=3D"utmcsr=3D"+_uEC(t2); }=0A= if (t3!=3D"-" && t3!=3D"") { if (c !=3D "") c+=3D"|"; = c+=3D"utmgclid=3D"+_uEC(t3); }=0A= t=3D_uGC(s,_uccn+"=3D","&");=0A= if (t!=3D"-" && t!=3D"") c+=3D"|utmccn=3D"+_uEC(t);=0A= else c+=3D"|utmccn=3D(not+set)";=0A= t=3D_uGC(s,_ucmd+"=3D","&");=0A= if (t!=3D"-" && t!=3D"") c+=3D"|utmcmd=3D"+_uEC(t);=0A= else c+=3D"|utmcmd=3D(not+set)";=0A= t=3D_uGC(s,_uctr+"=3D","&");=0A= if (t!=3D"-" && t!=3D"") c+=3D"|utmctr=3D"+_uEC(t);=0A= else { t=3D_uOrg(1); if (t!=3D"-" && t!=3D"") = c+=3D"|utmctr=3D"+_uEC(t); }=0A= t=3D_uGC(s,_ucct+"=3D","&");=0A= if (t!=3D"-" && t!=3D"") c+=3D"|utmcct=3D"+_uEC(t);=0A= t=3D_uGC(s,_ucno+"=3D","&");=0A= if (t=3D=3D"1") o=3D1;=0A= if (z!=3D"-" && o=3D=3D1) return "";=0A= }=0A= if (c=3D=3D"-" || c=3D=3D"") { c=3D_uOrg(); if (z!=3D"-" && = _ufno=3D=3D1) return ""; }=0A= if (c=3D=3D"-" || c=3D=3D"") { if (_ufns=3D=3D1) c=3D_uRef(); if = (z!=3D"-" && _ufno=3D=3D1) return ""; }=0A= if (c=3D=3D"-" || c=3D=3D"") {=0A= if (z=3D=3D"-" && _ufns=3D=3D1) { = c=3D"utmccn=3D(direct)|utmcsr=3D(direct)|utmcmd=3D(none)"; }=0A= if (c=3D=3D"-" || c=3D=3D"") return "";=0A= }=0A= if (z!=3D"-") {=0A= i=3Dz.indexOf(".");=0A= if (i>-1) i=3Dz.indexOf(".",i+1);=0A= if (i>-1) i=3Dz.indexOf(".",i+1);=0A= if (i>-1) i=3Dz.indexOf(".",i+1);=0A= t=3Dz.substring(i+1,z.length);=0A= if (t.toLowerCase()=3D=3Dc.toLowerCase()) cs=3D1;=0A= t=3Dz.substring(0,i);=0A= if ((i=3Dt.lastIndexOf(".")) > -1) {=0A= t=3Dt.substring(i+1,t.length);=0A= cn=3D(t*1);=0A= }=0A= }=0A= if (cs=3D=3D0 || _ufns=3D=3D1) {=0A= t=3D_uGC(dc,"__utma=3D"+_udh+".",";");=0A= if ((i=3Dt.lastIndexOf(".")) > 9) {=0A= _uns=3Dt.substring(i+1,t.length);=0A= _uns=3D(_uns*1);=0A= }=0A= cn++;=0A= if (_uns=3D=3D0) _uns=3D1;=0A= _ubd.cookie=3D"__utmz=3D"+_udh+"."+_ust+"."+_uns+"."+cn+"."+c+"; = path=3D"+_utcp+"; "+x+_udo;=0A= }=0A= if (cs=3D=3D0 || _ufns=3D=3D1) return "&utmcn=3D1";=0A= else return "&utmcr=3D1";=0A= }=0A= function _uRef() {=0A= if (_ur=3D=3D"0" || _ur=3D=3D"" || _ur=3D=3D"-") return "";=0A= var i=3D0,h,k,n;=0A= if ((i=3D_ur.indexOf("://"))<0 || _uGCse()) return "";=0A= h=3D_ur.substring(i+3,_ur.length);=0A= if (h.indexOf("/") > -1) {=0A= k=3Dh.substring(h.indexOf("/"),h.length);=0A= if (k.indexOf("?") > -1) k=3Dk.substring(0,k.indexOf("?"));=0A= h=3Dh.substring(0,h.indexOf("/"));=0A= }=0A= h=3Dh.toLowerCase();=0A= n=3Dh;=0A= if ((i=3Dn.indexOf(":")) > -1) n=3Dn.substring(0,i);=0A= for (var ii=3D0;ii<_uRno.length;ii++) {=0A= if ((i=3Dn.indexOf(_uRno[ii].toLowerCase())) > -1 && = n.length=3D=3D(i+_uRno[ii].length)) { _ufno=3D1; break; }=0A= }=0A= if (h.indexOf("www.")=3D=3D0) h=3Dh.substring(4,h.length);=0A= return = "utmccn=3D(referral)|utmcsr=3D"+_uEC(h)+"|"+"utmcct=3D"+_uEC(k)+"|utmcmd=3D= referral";=0A= }=0A= function _uOrg(t) {=0A= if (_ur=3D=3D"0" || _ur=3D=3D"" || _ur=3D=3D"-") return "";=0A= var i=3D0,h,k;=0A= if ((i=3D_ur.indexOf("://"))<0 || _uGCse()) return "";=0A= h=3D_ur.substring(i+3,_ur.length);=0A= if (h.indexOf("/") > -1) {=0A= h=3Dh.substring(0,h.indexOf("/"));=0A= }=0A= for (var ii=3D0;ii<_uOsr.length;ii++) {=0A= if (h.toLowerCase().indexOf(_uOsr[ii].toLowerCase()) > -1) {=0A= if ((i=3D_ur.indexOf("?"+_uOkw[ii]+"=3D")) > -1 || = (i=3D_ur.indexOf("&"+_uOkw[ii]+"=3D")) > -1) {=0A= k=3D_ur.substring(i+_uOkw[ii].length+2,_ur.length);=0A= if ((i=3Dk.indexOf("&")) > -1) k=3Dk.substring(0,i);=0A= for (var yy=3D0;yy<_uOno.length;yy++) {=0A= if (_uOno[yy].toLowerCase()=3D=3Dk.toLowerCase()) { _ufno=3D1; = break; }=0A= }=0A= if (t) return _uEC(k);=0A= else return = "utmccn=3D(organic)|utmcsr=3D"+_uEC(_uOsr[ii])+"|"+"utmctr=3D"+_uEC(k)+"|= utmcmd=3Dorganic";=0A= }=0A= }=0A= }=0A= return "";=0A= }=0A= function _uGCse() {=0A= var h,p;=0A= h=3Dp=3D_ur.split("://")[1];=0A= if(h.indexOf("/")>-1) {=0A= h=3Dh.split("/")[0];=0A= p=3Dp.substring(p.indexOf("/")+1,p.length);=0A= }=0A= if(p.indexOf("?")>-1) {=0A= p=3Dp.split("?")[0];=0A= }=0A= if(h.toLowerCase().indexOf("google")>-1) {=0A= if(_ur.indexOf("?q=3D")>-1 || _ur.indexOf("&q=3D")>-1) {=0A= if (p.toLowerCase().indexOf("cse")>-1) {=0A= return true;=0A= }=0A= }=0A= }=0A= }=0A= function _uBInfo() {=0A= var sr=3D"-",sc=3D"-",ul=3D"-",fl=3D"-",cs=3D"-",je=3D1;=0A= var n=3Dnavigator;=0A= if (self.screen) {=0A= sr=3Dscreen.width+"x"+screen.height;=0A= sc=3Dscreen.colorDepth+"-bit";=0A= } else if (self.java) {=0A= var j=3Djava.awt.Toolkit.getDefaultToolkit();=0A= var s=3Dj.getScreenSize();=0A= sr=3Ds.width+"x"+s.height;=0A= }=0A= if (n.language) { ul=3Dn.language.toLowerCase(); }=0A= else if (n.browserLanguage) { ul=3Dn.browserLanguage.toLowerCase(); }=0A= je=3Dn.javaEnabled()?1:0;=0A= if (_uflash) fl=3D_uFlash();=0A= if (_ubd.characterSet) cs=3D_uES(_ubd.characterSet);=0A= else if (_ubd.charset) cs=3D_uES(_ubd.charset);=0A= return = "&utmcs=3D"+cs+"&utmsr=3D"+sr+"&utmsc=3D"+sc+"&utmul=3D"+ul+"&utmje=3D"+j= e+"&utmfl=3D"+fl;=0A= }=0A= function __utmSetTrans() {=0A= var e;=0A= if (_ubd.getElementById) e=3D_ubd.getElementById("utmtrans");=0A= else if (_ubd.utmform && _ubd.utmform.utmtrans) = e=3D_ubd.utmform.utmtrans;=0A= if (!e) return;=0A= var l=3De.value.split("UTM:");=0A= var i,i2,c;=0A= if (_userv=3D=3D0 || _userv=3D=3D2) i=3Dnew Array();=0A= if (_userv=3D=3D1 || _userv=3D=3D2) { i2=3Dnew Array(); c=3D_uGCS(); }=0A= =0A= for (var ii=3D0;ii-1) return;=0A= if (h) { url=3Dl+"#"+p; }=0A= else {=0A= if (iq=3D=3D-1 && ih=3D=3D-1) url=3Dl+"?"+p;=0A= else if (ih=3D=3D-1) url=3Dl+"&"+p;=0A= else if (iq=3D=3D-1) url=3Dl.substring(0,ih-1)+"?"+p+l.substring(ih);=0A= else url=3Dl.substring(0,ih-1)+"&"+p+l.substring(ih);=0A= }=0A= }=0A= return url;=0A= }=0A= function __utmLinker(l,h) {=0A= if (!_ulink || !l || l=3D=3D"") return;=0A= _udl.href=3D__utmLinkerUrl(l,h);=0A= }=0A= function __utmLinkPost(f,h) {=0A= if (!_ulink || !f || !f.action) return;=0A= f.action=3D__utmLinkerUrl(f.action, h);=0A= return;=0A= }=0A= function __utmSetVar(v) {=0A= if (!v || v=3D=3D"") return;=0A= if (!_udo || _udo =3D=3D "") {=0A= _udh=3D_uDomain();=0A= if (_udn && _udn!=3D"") { _udo=3D" domain=3D"+_udn+";"; }=0A= }=0A= if (!_uVG()) return;=0A= var r=3DMath.round(Math.random() * 2147483647);=0A= _ubd.cookie=3D"__utmv=3D"+_udh+"."+_uES(v)+"; path=3D"+_utcp+"; = expires=3D"+_uNx()+";"+_udo;=0A= var s=3D"&utmt=3Dvar&utmn=3D"+r;=0A= if (_usample && _usample !=3D 100) s+=3D"&utmsp=3D"+_uES(_usample);=0A= if ((_userv=3D=3D0 || _userv=3D=3D2) && _uSP()) {=0A= var i=3Dnew Image(1,1);=0A= i.src=3D_ugifpath+"?"+"utmwv=3D"+_uwv+s;=0A= i.onload=3Dfunction() { _uVoid(); }=0A= }=0A= if ((_userv=3D=3D1 || _userv=3D=3D2) && _uSP()) {=0A= var i2=3Dnew Image(1,1);=0A= = i2.src=3D_ugifpath2+"?"+"utmwv=3D"+_uwv+s+"&utmac=3D"+_uacct+"&utmcc=3D"+= _uGCS();=0A= i2.onload=3Dfunction() { _uVoid(); }=0A= }=0A= }=0A= function _uGCS() {=0A= var t,c=3D"",dc=3D_ubd.cookie;=0A= if ((t=3D_uGC(dc,"__utma=3D"+_udh+".",";"))!=3D"-") = c+=3D_uES("__utma=3D"+t+";+");=0A= if ((t=3D_uGC(dc,"__utmx=3D"+_udh,";"))!=3D"-") = c+=3D_uES("__utmx=3D"+t+";+");=0A= if ((t=3D_uGC(dc,"__utmz=3D"+_udh+".",";"))!=3D"-") = c+=3D_uES("__utmz=3D"+t+";+");=0A= if ((t=3D_uGC(dc,"__utmv=3D"+_udh+".",";"))!=3D"-") = c+=3D_uES("__utmv=3D"+t+";");=0A= if (c.charAt(c.length-1)=3D=3D"+") c=3Dc.substring(0,c.length-1);=0A= return c;=0A= }=0A= function _uGC(l,n,s) {=0A= if (!l || l=3D=3D"" || !n || n=3D=3D"" || !s || s=3D=3D"") return "-";=0A= var i,i2,i3,c=3D"-";=0A= i=3Dl.indexOf(n);=0A= i3=3Dn.indexOf("=3D")+1;=0A= if (i > -1) {=0A= i2=3Dl.indexOf(s,i); if (i2 < 0) { i2=3Dl.length; }=0A= c=3Dl.substring((i+i3),i2);=0A= }=0A= return c;=0A= }=0A= function _uDomain() {=0A= if (!_udn || _udn=3D=3D"" || _udn=3D=3D"none") { _udn=3D""; return 1; }=0A= if (_udn=3D=3D"auto") {=0A= var d=3D_ubd.domain;=0A= if (d.substring(0,4)=3D=3D"www.") {=0A= d=3Dd.substring(4,d.length);=0A= }=0A= _udn=3Dd;=0A= }=0A= _udn =3D _udn.toLowerCase(); =0A= if (_uhash=3D=3D"off") return 1;=0A= return _uHash(_udn);=0A= }=0A= function _uHash(d) {=0A= if (!d || d=3D=3D"") return 1;=0A= var h=3D0,g=3D0;=0A= for (var i=3Dd.length-1;i>=3D0;i--) {=0A= var c=3DparseInt(d.charCodeAt(i));=0A= h=3D((h << 6) & 0xfffffff) + c + (c << 14);=0A= if ((g=3Dh & 0xfe00000)!=3D0) h=3D(h ^ (g >> 21));=0A= }=0A= return h;=0A= }=0A= function _uFixA(c,s,t) {=0A= if (!c || c=3D=3D"" || !s || s=3D=3D"" || !t || t=3D=3D"") return "-";=0A= var a=3D_uGC(c,"__utma=3D"+_udh+".",s);=0A= var lt=3D0,i=3D0;=0A= if ((i=3Da.lastIndexOf(".")) > 9) {=0A= _uns=3Da.substring(i+1,a.length);=0A= _uns=3D(_uns*1)+1;=0A= a=3Da.substring(0,i);=0A= if ((i=3Da.lastIndexOf(".")) > 7) {=0A= lt=3Da.substring(i+1,a.length);=0A= a=3Da.substring(0,i);=0A= }=0A= if ((i=3Da.lastIndexOf(".")) > 5) {=0A= a=3Da.substring(0,i);=0A= }=0A= a+=3D"."+lt+"."+t+"."+_uns;=0A= }=0A= return a;=0A= }=0A= function _uTrim(s) {=0A= if (!s || s=3D=3D"") return "";=0A= while ((s.charAt(0)=3D=3D' ') || (s.charAt(0)=3D=3D'\n') || = (s.charAt(0,1)=3D=3D'\r')) s=3Ds.substring(1,s.length);=0A= while ((s.charAt(s.length-1)=3D=3D' ') || = (s.charAt(s.length-1)=3D=3D'\n') || (s.charAt(s.length-1)=3D=3D'\r')) = s=3Ds.substring(0,s.length-1);=0A= return s;=0A= }=0A= function _uEC(s) {=0A= var n=3D"";=0A= if (!s || s=3D=3D"") return "";=0A= for (var i=3D0;i0) r=3Da.substring(i+1,i2); else return = ""; =0A= if ((i=3Da.indexOf(".",i2+1))>0) t=3Da.substring(i2+1,i); else return = ""; =0A= if (f) {=0A= return r;=0A= } else {=0A= var c=3Dnew = Array('A','B','C','D','E','F','G','H','J','K','L','M','N','P','R','S','T'= ,'U','V','W','X','Y','Z','1','2','3','4','5','6','7','8','9');=0A= return = c[r>>28&m]+c[r>>23&m]+c[r>>18&m]+c[r>>13&m]+"-"+c[r>>8&m]+c[r>>3&m]+c[((r= &7)<<2)+(t>>30&3)]+c[t>>25&m]+c[t>>20&m]+"-"+c[t>>15&m]+c[t>>10&m]+c[t>>5= &m]+c[t&m];=0A= }=0A= }=0A= function _uIN(n) {=0A= if (!n) return false;=0A= for (var i=3D0;i"9") && (c!=3D".")) return false;=0A= }=0A= return true;=0A= }=0A= function _uES(s,u) {=0A= if (typeof(encodeURIComponent) =3D=3D 'function') {=0A= if (u) return encodeURI(s);=0A= else return encodeURIComponent(s);=0A= } else {=0A= return escape(s);=0A= }=0A= }=0A= function _uUES(s) {=0A= if (typeof(decodeURIComponent) =3D=3D 'function') {=0A= return decodeURIComponent(s);=0A= } else {=0A= return unescape(s);=0A= }=0A= }=0A= function _uVG() {=0A= if((_udn.indexOf("www.google.") =3D=3D 0 || _udn.indexOf(".google.") = =3D=3D 0 || _udn.indexOf("google.") =3D=3D 0) && _utcp=3D=3D'/' && = _udn.indexOf("google.org")=3D=3D-1) {=0A= return false;=0A= }=0A= return true;=0A= }=0A= function _uSP() {=0A= var s=3D100;=0A= if (_usample) s=3D_usample;=0A= if(s>=3D100 || s<=3D0) return true;=0A= return ((__utmVisitorCode(1)%10000)<(s*100));=0A= }=0A= function urchinPathCopy(p){=0A= var d=3Ddocument,nx,tx,sx,i,c,cs,t,h,o;=0A= cs=3Dnew Array("a","b","c","v","x","z");=0A= h=3D_uDomain(); if (_udn && _udn!=3D"") o=3D" domain=3D"+_udn+";";=0A= nx=3D_uNx()+";";=0A= tx=3Dnew Date(); tx.setTime(tx.getTime()+(_utimeout*1000));=0A= tx=3Dtx.toGMTString()+";";=0A= sx=3Dnew Date(); sx.setTime(sx.getTime()+(_ucto*1000));=0A= sx=3Dsx.toGMTString()+";";=0A= for (i=3D0;i<6;i++){=0A= t=3D" expires=3D";=0A= if (i=3D=3D1) t+=3Dtx; else if (i=3D=3D2) t=3D""; else if (i=3D=3D5) = t+=3Dsx; else t+=3Dnx;=0A= c=3D_uGC(d.cookie,"__utm"+cs[i]+"=3D"+h,";");=0A= if (c!=3D"-") d.cookie=3D"__utm"+cs[i]+"=3D"+c+"; path=3D"+p+";"+t+o;=0A= }=0A= }=0A= function _uCO() {=0A= if (!_utk || _utk=3D=3D"" || _utk.length<10) return;=0A= var d=3D'www.google.com';=0A= if (_utk.charAt(0)=3D=3D'!') d=3D'analytics.corp.google.com';=0A= _ubd.cookie=3D"GASO=3D"+_utk+"; path=3D"+_utcp+";"+_udo;=0A= var sc=3Ddocument.createElement('script');=0A= sc.type=3D'text/javascript';=0A= sc.id=3D"_gasojs";=0A= = sc.src=3D'https://'+d+'/analytics/reporting/overlay_js?gaso=3D'+_utk+'&'+= Math.random();=0A= document.getElementsByTagName('head')[0].appendChild(sc); =0A= }=0A= function _uGT() {=0A= var h=3Dlocation.hash, a;=0A= if (h && h!=3D"" && h.indexOf("#gaso=3D")=3D=3D0) {=0A= a=3D_uGC(h,"gaso=3D","&");=0A= } else {=0A= a=3D_uGC(_ubd.cookie,"GASO=3D",";");=0A= }=0A= return a;=0A= }=0A= var _utk=3D_uGT();=0A= if (_utk && _utk!=3D"" && _utk.length>10 && _utk.indexOf("=3D")=3D=3D-1) = {=0A= if (window.addEventListener) {=0A= window.addEventListener('load', _uCO, false); =0A= } else if (window.attachEvent) { =0A= window.attachEvent('onload', _uCO);=0A= }=0A= }=0A= =0A= function _uNx() {=0A= return (new Date((new Date()).getTime()+63072000000)).toGMTString();=0A= }=0A= ------=_NextPart_000_0000_01CD97FF.95565490 Content-Type: multipart/alternative; boundary="----=_NextPart_001_004B_01CD97FF.955D8080" ------=_NextPart_001_004B_01CD97FF.955D8080 Content-Type: text/html; charset="utf-8" Content-Transfer-Encoding: quoted-printable Content-Location: http://journals.tdl.org/jodi/article/view/5917/5892 =EF=BB=BF Ball ------=_NextPart_001_004B_01CD97FF.955D8080 Content-Type: application/octet-stream Content-Transfer-Encoding: quoted-printable Content-Location: http://journals.tdl.org/jodi/article/viewArticle/5917/5892 =EF=BB=BF Visualizing = Research Data Records for their Better Management | Ball | Journal of = Digital Information

Journal of Digital Information, Vol 13, No 1 (2012)

Home > Vol 13, No 1=20 (2012) > Ball

Font Size: =20 =20 =20

=EF=BB=BF=20

Visuali= zing=20 Research Data Records for their Better Management

Alexander Ball
UKOLN, University of Bath=20
a.ball@ukoln.ac.uk

Mansur Darlington
IdMRC, University of = Bath=20
m.j.darlington@bath.ac.uk

Thomas Howard
Department of Management = Engineering,=20 Technical University of Denmark
thow@man.dtu.dk

Chris McMahon
IdMRC, University of Bath =
c.a.mcmahon@bath.ac.uk

Steve Culley
IdMRC, University of Bath=20
s.j.culley@bath.ac.uk

Abstract

As academia in general, and research funders in particular, place = ever=20 greater importance on data as an output of research, so the value of = good=20 research data management practices becomes ever more apparent. In = response to=20 this, the Innovative Design and Manufacturing Research Centre = (IdMRC)=20 at the University of Bath, UK, with funding from the JISC, ran a project = to draw=20 up a data management planning regime. In carrying out this task, the = ERIM=20 (Engineering Research Information Management) Project devised a visual = method of=20 mapping out the data records produced in the course of research, along = with the=20 associations between them. This method, called Research Activity = Information=20 Development (RAID) Modelling, is based on the Unified Modelling Language = (UML)=20 for portability. It is offered to the wider research community as an = intuitive=20 way for researchers both to keep track of their own data and to = communicate this=20 understanding to others who may wish to validate the findings or re-use = the=20 data.

1. Introduction

Recent years have seen a change in attitude within academia towards = research=20 data. It may be characterized as a shift along the spectrum away from = data as a=20 disposable commodity or private concern and towards data as a = first-class=20 product of research, though attitudes have always varied widely across=20 disciplines (Wilson=20 et al. 2010; Jones=20 2009). The transition from analogue to digital data, and concurrent = advances=20 in information and communication technology, have certainly assisted = this shift=20 by making it more practical to access and re-use datasets, but many = other=20 drivers can be identified. There is the quality argument, that=20 publishing data drives up the quality of research not just because it = makes the=20 results easier to verify and (where applicable) reproduce, but also = because it=20 makes the entire research process more transparent and accountable. If=20 researchers know their data will be made public, this provides a strong=20 incentive to ensure all aspects of its generation and processing can be=20 justified (Stodden=20 2009; RIN=20 and NESTA 2010). There is the opportunity argument, that=20 interdisciplinary studies, metastudies and 'Citizen Science' are = providing more=20 opportunities than ever before to re-use and re-process data in novel = ways and=20 contexts. Besides which, within disciplines such as astronomy (STScI=20 2011) and bioinformatics (Edwards=20 et al. 2009), there is ample evidence of significant = quantities of=20 research based on secondary uses of data. This argument forms the basis = for the=20 economic argument, that by publishing data and allowing its = reuse, the=20 return on the investment made to create it is increased. There are,=20 additionally, efficiency savings to be gained from the non-duplication = of effort=20 in generating data. Further arguments can be made on how publishing data = increases its academic, social and economic impact (Pienta=20 et al. 2010; Piwowar,=20 Day and Fridsma 2007).

Providing access to research data is in itself no small thing. If = personal or=20 otherwise sensitive information is involved, the data can only be = released if=20 appropriate permissions have been granted, and only then if the = conditions of=20 the agreement (e.g. anonymization, embargo periods, restricted access) = are met.=20 Equally there may be intellectual property issues to resolve. But if the = above=20 benefits are to be realized, mere access is not enough. It must be = possible to=20 find the data, whether by means of citations or search services, and = most=20 especially of all the data must be in a fit state for other researchers = to=20 re-use and re-purpose them. This has plenty of implications for how the = data are=20 managed throughout the course of the research. For integrability it is = helpful=20 if the data are generated and collected using common, respected methods = and=20 models. For interoperability it is helpful if they are stored in = well-supported=20 file formats. In order to remain explicable they must be fully = documented and=20 contextualized. In order to remain part of the research record, they = must be=20 preserved at the bit level and adapted over time in response to changes = in=20 prevalent software, data models and semantics. This level of management = cannot=20 be left to happen by chance: it must be properly planned and resourced. =

This being so, research funders are becoming more forthright in their = requirements that researchers plan their data sharing and data = management=20 activities. In the US, both the National Institutes of Health and, since = January=20 2011, the National Science Foundation require that all applications for = funding=20 should include a data management plan (NIH=20 2003; NSF=20 2011, Chapter II.C.2.j). In the UK, the Wellcome Trust and five out = of the=20 seven Research Councils require some form of data management plan to be=20 submitted as part of research proposals (Jones=20 2009). In May 2011, the major funder for engineering research, the=20 Engineering and Physical Sciences Research Council (EPSRC), introduced = new data=20 management requirements for institutions that receive its funding (EPSRC=20 2011), but stopped short of a requirement to submit data management = plans=20 with funding proposals; this, and the fact that there is no tradition of = data=20 sharing within the discipline, means there is little other than generic = guidance=20 or experience for researchers to draw on when planning the management of = their=20 data. In response to this need, the Engineering Research Information = Management=20 (ERIM) Project has developed a data management planning regime for a = research=20 centre at the University of Bath, using an approach that may be re-used = by other=20 engineering research centres. This project is introduced in greater = depth in=20 Section 2.

In the course of the project's work, a technique has been developed = for=20 visualizing the context of research data records for the purposes of = better=20 management. This paper describes the modelling technique. Section 3 = introduces=20 the terminology and metamodel used in the technique, while Section 4 = shows how=20 the records and processes used in the research are visualized. Section 5 = places=20 this modelling technique in the wider data management context, and = finally some=20 conclusions are presented in section 6.

2. The ERIM Project

In 2009, the Joint Information System Committee (JISC) of the UK = further and=20 higher education funding councils initiated a programme of research = entitled=20 Managing Research Data (Down=20 2010). One of the strands in this programme comprised a set of = projects=20 providing detailed case studies of data management planning within = different=20 disciplines, with each case study drawn from the research interests of a = different major UK funding body. These projects all aimed to illuminate = the most=20 pressing data management issues for their disciplines, and illustrate = how they=20 might be overcome by producing exemplar data management plans.

The EPSRC as a funding body and engineering as a discipline were = represented=20 in this programme strand by the ERIM Project. ERIM was an eighteen-month = collaboration between the Innovative Design and Manufacturing Research = Centre=20 (IdMRC) at the University of Bath and the UK Digital Curation = Centre,=20 specifically its constituent partner at the University of Bath, UKOLN. = The=20 project had several broad aims:

to specify in practical terms how data management may most = effectively be=20 performed within the IdMRC's research projects and, by = extension,=20 similar projects undertaken elsewhere;
to explore the opportunities for and barriers to the re-use of = engineering=20 information, including the results of research conducted using highly=20 sensitive industrial data and information;
to identify the information required to ensure that research = datasets are=20 re-usable, either by the original researchers or others.

These aims translated into a set of objectives that included:

a report into the state of the art of the digital curation of = research=20 data (Ball=20 2010);
a set of six case studies intended to exhibit the gamut of data = types,=20 working practices, challenges and re-use opportunities in evidence = within=20 engineering research (Howard=20 et al. 2010);
a data management regime for use within the IdMRC that = could be=20 adapted by other similar centres.

The case studies in the second objective were selected from among = research=20 activities within the IdMRC itself and within a recent, major = research=20 project in which the IdMRC was the lead partner (Ball=20 et al. 2006). In order to achieve the widest possible = variety=20 between the six cases eventually chosen, the research activities were = classified=20 according to factors such as: whether they relied on pre-existing data; = the=20 variety or otherwise of data types used; whether the research described = an=20 existing practice or sought a new or improved one; and whether the = activity=20 focused on the real world or a simulation of it.

Having selected the case studies, the question arose of how best to = analyse=20 them, both to uncover the pressing management issues and to suggest = mitigating=20 policies and procedures. Existing models such as the OAIS Reference = Model (CCSDS=20 2002) and the DCC Curation Lifecycle Model (Higgins=20 2008) did not provide sufficient detail for stages prior to data = being=20 ingested into a repository, and while the I2S2 Idealised Scientific = Research=20 Activity Lifecycle Model (Patel=20 2010, p. 24) was more relevant it did not go down to the required = level of=20 granularity. The authors therefore embarked on course of theoretical = work to=20 model in detail the trail of data objects left behind by research = activities,=20 the validity of which model would be tested in the analysis of the case = studies.=20 This theoretical work, quite unexpectedly, became a major output of the = ERIM=20 Project.

When characterizing engineering research data during this project, = two very=20 important findings emerged that are worthy of mention here. The first is = that,=20 as it turns out, engineering research data are very diverse. From the = samples=20 taken, every conceivable type of research data might reasonably be = encountered=20 as a result of engineering research. It follows that methods for the = more=20 effective management of engineering research data will be usefully = applicable to=20 many data in general. The second finding, in hindsight unsurprising, is = that to=20 understand the data output of a research activity after the event, such = that the=20 data may usefully be used again in some way, requires that the context = in which=20 the data was generated be understood too, and that the relationship = between=20 individual elements of information (at the file level at least; see = below) be=20 known. This implies that it is not just research data that must be = preserved=20 after a research activity, but that contextualizing information be = gathered and=20 stored with that data, such that its future use can be assured. = Furthermore, in=20 order to ensure interpretability of research data by those unfamiliar = with it,=20 is necessary to make explicit the association between research data and = between=20 research data and its explicating information.

It is the realization of the second point that is the chief = motivation for=20 the modelling approach developed during the ERIM Project, and = recognition of the=20 first point that makes the ERIM theoretical work and modelling approach = of=20 interest outside the bounds of engineering research data management = alone.

3. Terminology

Fundamental to the ERIM model of research activity was a Data = Management=20 Terminology, full details of which may be found in Darlington=20 (2011a). In order to clarify discussions on how data, once created, = might be=20 used, the following terms were defined.

Data Use. Using research data for the current = research=20 purpose/activity to infer new knowledge about the research = subject.
Data Re-use. Using research data for a research=20 purpose/activity other than that for which it was intended.
Data Purposing. Making research data available = and fit=20 for the current research activity.
Data Re-purposing. Making existing research data=20 available and fit for a future known research=20 activity.
Supporting Data Re-use. Managing existing = research data=20 such that it will be available for a future = unknown=20 research activity. Unfortunately, no apposite verb could be found = for=20 this activity, hence the slight circumlocution; however it overlaps=20 significantly with certain definitions of archiving, preservation and=20 curation.

The data management performed in the course of a project can be seen = as=20 primarily serving the needs of data purposing, while the needs of data=20 re-purposing are usually served, if at all, at the point of project = completion=20 when working up data for archiving. Supporting data re-use predominantly = happens=20 after ingest into a repository. Put into these terms, the vision for the = new=20 data management regime was to adapt the processes that served data = purposing so=20 that they also served data re-purposing and supporting data re-use. In = this way,=20 either the same effort on the part of the researcher would result in = more=20 re-usable data, or the same amount of re-usable data could be achieved = with less=20 effort. Realising this vision would entail some analysis of existing = processes=20 and the resulting data assets, hence the direction of the theoretical = work.

When it came to describing the data associated with research = activities,=20 there was some concern over the granularity with which they were = modelled (Darlington=20 et al. 2008). The notion of being able to track the = provenance of=20 each individual datum in a published dataset back to its point of = creation was=20 attractive, and indeed there are efforts in some disciplines to move in = this=20 direction (Groth,=20 Gibson and Velterop 2010). It was felt, however, that within the = scope of=20 the project a more achievable aim would be to concentrate on data = management at=20 the file level and higher. With this in mind, the following terms were=20 defined.

Information. Any type of knowledge that can be = exchanged.=20 In an exchange, it is represented by data.
Data. Reinterpretable representations of = information in a=20 formalized manner suitable for communication, interpretation or=20 processing.
Data Object. Either a physical object or a = digital object=20 containing data.
Data Record. A data object created, received and=20 maintained as evidence of an activity.
Data Case. The set of data records associated = with some=20 discrete research activity (project, task, experiment, = etc.).

The notion of a digital object corresponds roughly with that of a = file. As=20 digital (and physical) objects can be nested, in cases where a single = file=20 contains multiple data objects, the file can still be treated as a = digital=20 object in its own right. The only obstacle to evading the distinction = between=20 object and file are therefore the cases where a single digital object is = represented by a series of files.

Key to the entire data management endeavour is the notion of a data = record.=20 It implies that the data object has a level of importance within the = research=20 activity, and of conscious curatorial effort, exceeding that given to = those=20 which merely happen to survive. In order to model and visualize the = roles of the=20 various records in a data case, and thereby make decisions on how they = should be=20 managed, the authors constructed the following taxonomy (see Figure=20 1).

=20

Figure 1. The Research = Activity Data=20 Object Taxonomy.

Research Data Record. A record containing data = that are=20 descriptive of the research object, whether generated by the current = research=20 activity or a previous one. Its role is to provide the basis for = inferring new=20 knowledge about the object.
Context Data Record. A record containing data = that=20 support the research activity but do not describe the research object = nor are=20 the research object itself. Such records might include a description = of the=20 methodology, an explanatory narrative, dictionaries, ontologies, = standards=20 documents or environmental data. Where this information has not been = provided=20 explicitly to explain or illuminate other data or records, it is = referred to=20 instead as an unintentional context data object.
Associative Data Record. A context data record = that makes=20 explicit the associations between other data records or data.
Research Object Data Record. A record containing = data=20 which is, itself, the object of the research enquiry. For example, in = textual=20 analyses of nineteenth-century newspapers, the newspapers themselves = act as=20 Research Object Data Records.
Experimental Apparatus Data Record. A record = containing=20 symbolic representations which are functionally analogous to the = physical=20 experimental apparatus familiar in much laboratory-based research. For = example, in textual analyses of nineteenth-century newspapers, the = source code=20 of the text-mining software and the parameters used to control it = would form=20 the content of Experimental Apparatus Data Records.

When it came to using this taxonomy in the six case studies, the = authors did=20 not always find it easy to decide in which category a particular record = should=20 go. When analysing records of what Blessing=20 and Chakrabarti (2009) term prescriptive research, where=20 experimental processes and designs are tested, they found the lines = between=20 research data records, research object data records and context data = records=20 especially blurred. Nevertheless, they found the process of classifying = records=20 useful as a method of appreciating the overall scope and shape of a data = case.

4. = Research=20 Activity Information Development modelling

Having decided on a terminology for describing the data objects = associated=20 with a research activity, two further tasks remained. One was to model = the=20 processes by which a data case is developed, and the second was to = provide a way=20 of visualizing both data objects and data development processes. For the = second=20 task, the desiderata were for the visualization:

to use an existing standard, so that it could be at least = partially=20 understood using just the documentation for that standard;
to be both expressive enough to model most data cases but rigorous = enough=20 to permit comparisons between diagrams;
to be amenable to automation, both in terms of generating diagrams = automatically and translating them to machine readable code/linked=20 data.

After a review of the available standards, the most suitable = representation=20 languages were found to be IDEF3 (Mayer=20 et al. 1995) and UML (OMG=20 2009). While both had strengths and weaknesses, UML was chosen as = being more=20 familiar to those in the data management community. As both data objects = and=20 development processes were to be modelled, UML activity diagrams were = chosen as=20 the primary language to use, extended with UML object diagram notation. = Certain=20 aspects of UML notation had to be relaxed to accommodate the fact that = the=20 primary focus of the modelling would be on the objects rather than on = the=20 processes, and that the models would show actual instances rather than = idealized=20 classes; so, for example, as an aid to visual clarity instance names = were not=20 underlined as they would normally be in UML, activity flows were allowed = to be=20 incomplete, objects could be included without being an explicit part of = a flow,=20 and where multiple flows were shown on a single diagram they were not=20 interpreted as strictly concurrent.

The process of modelling a research activity in this way was given = the name=20 Research Activity Information Development (RAID) modelling, and the = resulting=20 diagrams produced were termed RAID diagrams. The intention was and is = for one=20 diagram to represent one research activity and hence one data case, = though large=20 data cases may require several diagrams.

4.1. Visualization of data=20 objects

Digital objects considered in the abstract (i.e. not as part of a = file) and=20 physical objects are visualized as simple UML objects. Digital objects = that=20 existed as files but were not kept as records are represented as UML = objects,=20 with the file name as the instance name and the role as the class name. = If the=20 role cannot be determined, the class 'Temporary File' may be used. = Properties of=20 the file are given in the lower partition (see Figure=20 2); to save space, the property keys 'mediaType', 'origin' and = 'description'=20 have been abbreviated to their initial letters.

=20

Figure 2. Representations = of a=20 physical object and a digital object.

Digital data records are modelled as UML datastores. If the record is = manifested as a single file, its file name is given as the instance = name,=20 otherwise a brief identifying phrase is used. The role of the record is = given as=20 the class name; if the role cannot be determined, the generic role 'Data = Record'=20 may be used. Again, properties of the file(s) are given in the lower = partition.=20 If the record is not to be packaged as part of the data case being = modelled, it=20 is marked with the keyword 'external'.

If an object from which data are generated is not itself a record, it = is=20 modelled as a datastore with class 'Source' (see Figure=20 3).

=20

Figure 3. Representations = of a data=20 source, a data record within the data case and a data record external to = the=20 data case.

4.2. = Definition=20 and visualization of development processes

When it came to enumerating the types of data development processes = that=20 occur in the course of research, the authors considered activities from = across=20 the spectrum of data purposing, data re-purposing and supporting data = re-use, as=20 well as from the perspectives of individual data, data records and = entire data=20 cases. The list they constructed was intended to be, but is not claimed = to be,=20 comprehensive from the perspective of engineering researchers (Howard=20 et al. 2010). In all, fifteen processes were identified; = these are=20 defined below. When it came to visualizing these processes, some = compromises had=20 to be made due to the fact that RAID diagrams display the data records = that make=20 up a data case, and do not decompose these records into individual data. = Thus=20 processes that, strictly speaking, operate at the data level are = visualized as=20 linking the records that contain them. In order to clarify where such=20 compromises have been made, the definitions below are accompanied by = notes on=20 how they are visualized.

Addition

Addition is the act of supplementing data at the data level. On a = RAID=20 diagram (see Figure=20 4), it is shown between two data records when data from within the = first=20 record has been added to the data within the second record.

=20

Figure 4. Representation of = data from=20 object X being added to object Y.

Aggregation

Aggregation is the act of combining similar data from different = sources for=20 the purposes of increasing the sample size. A clear example found in the = case=20 studies was of questionnaire responses being combined to form a single = dataset.=20 On a RAID diagram (see Figure=20 5), it is shown as taking several records as inputs and outputting a = further=20 record when data from within the former records have been aggregated = together=20 and stored within the latter record.

=20

Figure 5. Representation = of data=20 from objects X and Y being aggregated and recorded in object = Z.

Annotation

Annotation is the act of adding 'information or additional marks = formulated=20 on a document for enhancing it with brief and useful explanations' (Evrard=20 and Virbel 1996). In digital terms, this may be done either within = the file=20 itself using whatever commenting facilities the format provides = ('inline'), or=20 within a separate file that links to the annotated file or sections = thereof=20 ('stand-off'). On a RAID diagram (see Figure=20 6), inline annotation is represented as a UML activity, showing the = data=20 object whence the annotations originate if appropriate (examples [a] and = [b]).=20 Stand-off annotation is indicated by a UML note attached to the = annotated=20 record; the annotation can be placed directly in the RAID diagram if = required=20 (c), otherwise the file holding the annotations is represented as a data = record=20 within the note.

=20

Figure 6. Representations = of data=20 object X being annotated using inline annotation (a,b) or stand-off = annotation=20 (c,d).

Association

Association is the act of making explicit the relationship between = data, data=20 records and data cases. There are many ways in which this can be done, = for=20 example by using a file naming convention, embedding metadata or links, = or=20 constructing a RAID diagram. As such, the act of association itself is = not=20 appropriate for inclusion in a RAID diagram, as it would in most cases = be either=20 too abstract, too broadly applicable, or recursive. There is a = convention in=20 RAID diagrams, though, to record arbitrary associations as named object = flows=20 where the other action types do not apply (see Figure=20 7).

=20

Figure 7. Representation = of=20 arbitrary associations between data objects X, Y and Z.

Augmentation

Augmentation is the act of adding a data record to a data case. In = other=20 words, it refers to a commitment to include a data object in any = subsequent=20 packaging of the data as evidence of the research activity. It is a = process that=20 occurs at a higher level than that depicted by RAID diagrams, but may be = inferred from the inclusion within a RAID diagram of data objects marked = as=20 records (as opposed to transient data objects or data sources) without = the=20 'external' keyword (see Figure=20 3, above).

Collation

Collation is the act of giving order to data assembled from different = sources, and as such usually occurs in conjunction with aggregation. = While it=20 may seem a trivial operation to record, it can destroy potentially = useful clues=20 about data provenance, and therefore deserves some management attention. = On a=20 RAID diagram (see Figure=20 8), an act of collation that takes place at or close to the point at = which a=20 data record is created is represented by an action outputting the record = (example [a]). Acts of collation that occur later or repeatedly are = indicated by=20 an action both inputting and outputting the same data record.

=20

Figure 8. Representation of = data=20 being collated (a) as part of the process of creating data object Z, or = (b) as=20 part of the maintenance of Z.

Collection

Collection is the act of acquiring or bringing together pre-existing = data. On=20 a RAID diagram (see Figure=20 9), it is shown between a data source and a data record containing = (nothing=20 but) pre-existing data acquired from the source. Since the definition of = collection here applies equally to the use of pre-existing records and = the=20 aggregation/extraction of pre-existing data into a new record, on a RAID = diagram=20 the latter case may be represented either as a single 'collect' action = or=20 multiple 'collect' actions followed by an aggregation/extraction.

=20

Figure 9. Representation of = data=20 being collected from source X and stored within data record Y.

Deletion

Deletion is the act of expunging or obliterating data. It can happen = either=20 by the destruction of an entire record, or by removing data from within = a=20 record. The latter is distinct from refinement (see below) in that the = data are=20 removed entirely rather than tidied or cleaned through the selective = removal of=20 individual data. Deletion is also distinct from neglect, that is, = treating a=20 data object as transient rather than as a record. On a RAID diagram (see = Figure=20 10), if a deletion action is followed by a flow final node, this = indicates=20 that the preceding record has been destroyed; if the deletion is = followed by a=20 record, this indicates some data from the preceding record has been = removed to=20 create the following record. In-place deletion of data, where the = changes are=20 saved over the previous version instead of into a new version, should be = explained in an annotation on the 'delete' action.

=20

Figure 10. Representation of = (a) data=20 being deleted from object X to create object Y, and (b) data object X = being=20 deleted.

Derivation

The term derivation is used in data contexts to describe many = different kinds=20 of transformation; for example, NASA use it for combining datasets, = normalizing=20 data to standard grids and creating different visualizations (CDMC=20 1986; EOSDP=20 1986). In the ERIM terminology, derivation is used only of processes = that=20 deliberately create new data from existing data, such as logical = inference,=20 extrapolation, or interpolation. On a RAID diagram (see Figure=20 11) derivation is represented as an action taking one or more = records and=20 optionally functions as input, and outputting a further record. The=20 interpretation of this is that the function(s) have been used in = conjunction=20 with the data in the former record(s) to produce the data in the latter=20 record.

=20

Figure 11. Representation of = a=20 function being applied to the data contained in object X to derive the = data then=20 stored in object Y.

Duplication

Duplication is simply the act of making an identical copy of a file. = Since=20 such an operation is usually a small, transient step in larger process = (e.g.=20 circulating a questionnaire), it is not usually included in RAID = diagrams. If=20 visualizing a data case prior to packaging for archiving, it might be = useful to=20 indicate duplicate records on a RAID diagram so they may be reviewed as=20 candidates for deletion, in which case a 'duplicate' action can be used = (see Figure=20 12).

=20

Figure 12. Representation = of data=20 object X being duplicated, the result of which is object Y.

Extraction

Extraction is the creation of a new record from portions of the data = in one=20 or more existing records. On a RAID diagram (see Figure=20 13), it is shown between two data records when data from within the = first=20 record has been copied or removed and stored within the second = record.

=20

Figure 13. Representation = of data=20 from object X being extracted out into object Y.

Generation

Generation is the act of creating new data by acting on or = interacting with a=20 research subject. On a RAID diagram ([see Figure=20 14), it is represented by an action taking as inputs one or more = sources=20 (research subjects, experimental apparatus) and outputting one or more = data=20 records containing the new data. Records that explain the methodology = may be=20 indicated as annotations on the 'generate' action.

=20

Figure 14. Representation = of the=20 data in record Y being generated from the source X.

Migration

Migration is the transfer of digital information from one format to = another=20 with the intention of preserving the full information content. In the = case=20 studies it was shown to occur most frequently to allow the data to be = processed=20 by a different piece of software. On a RAID diagram (see Figure=20 15), it is shown between two records when the second record is the = result of=20 changing the file format of the first record. If information is = deliberately=20 lost in the migration, it should be represented as a combined migration = and=20 deletion process.

=20

Figure 15. Representation = of data=20 object X being migrated to a new file format and saved as object = Y.

Population

Population is the act of entering data from a record into an existing = framework such as a knowledge base, database, pro-forma or modelling = system. On=20 a RAID diagram (see Figure=20 16), it is shown instead of an 'add' action when the second record = is a=20 database, knowledge base or some other form of record where the = structure is=20 driven by existing systems and frameworks rather than arising naturally = from the=20 contents.

=20

Figure 16. Representation = of data=20 within object X being used to create or extend object Y according to an = existing=20 model or procedure.

Refinement

Refinement is the act of re-expressing data in a different way or = according=20 to a different data model. It covers both reversible processes such as = unit=20 conversion and the correction of systematic errors, and irreversible = processes=20 such as precision reduction and the removal of outlying data points, = noise,=20 duplicates, and so on. Refinement differs from derivation in that it = emphasizes=20 correcting and simplifying existing data, rather than creating new data = from=20 them.

On a RAID diagram (see Figure=20 4), refinement is shown between two data records when data within = the second=20 record is a refined version of data within the first record. In cases of = reversible refinement, it can sometimes be of benefit (in terms of = storage and=20 curatorial effort) to delete the earlier record while providing = sufficient=20 documentation to allow it to be recreated from the later record. = Depending on=20 the nature of the documentation, it should be added to the RAID diagram = either=20 as an input to or an annotation on the the 'refine' action.

=20

Figure 17. Representation of = data from=20 object X being refined and stored in object Y.

4.3. Research Data=20 Development Side Effects

Identifying the processes to which data are subject is important not = only to=20 understanding the data related to individual research activities, but = also=20 because associated with such processes are, particularly at the data = level, a=20 number of side-effects. The side-effects identified by the authors are = not only=20 a logical contingent of data development activities, but also can be = identified=20 and demonstrated in specific instances of development. These = side-effects are:=20 information loss, information gain, function loss, function gain and = state loss=20 (Howard=20 et al. 2010).

By understanding and recording the processes through which instances = of data=20 are developed appropriate management intervention can take place to = minimize the=20 impact that these side-effects might otherwise have on data re-use and=20 re-purposing.

4.4. = Applying=20 the RAID modelling method to a research activity

The above modelling technique was developed iteratively in the course = of its=20 application to the six ERIM case studies. The use of named flows to = represent=20 arbitrary associations, for example, came about in response to finding = important=20 inter-relationships between records that could not be expressed = succinctly in=20 process terms. In addition to the visual grammar already described, the = authors=20 found it helpful to group records and activities into partitions = representing=20 avenues and stages of research within the research activity. For this, = the=20 authors adopted UML swimlane notation.

=20

Figure 18. A RAID diagram of = selected=20 related data records in the CRYMAN data case revealing important = associational=20 information.

Figure=20 18 shows a RAID diagram mapping out a subset of the data records = produced in=20 the course of doctoral research into cryogenic machining. Swimlanes have = been=20 used to separate out two branches of the research, the first concerning = the=20 temperature profiles of a material (Set 1) and the second the material's = cutting=20 profiles (Set 2), with the latter further divided into the theoretical = stage and=20 the experimental stage.

Prior to the case study being performed, this research activity had = only one=20 data record =E2=80=93 the thesis reporting the results of the research = =E2=80=93 and no=20 intentional context data objects. It would have been impossible for any = future=20 researcher to validate the research findings, let alone build directly = on the=20 work. Performing RAID modelling retrospectively on the research improved = matters=20 in at least two regards. First, in considering the value of each of the=20 remaining data objects to the data case, the researcher identified a = large=20 number of objects that ought to be treated as data records, that is, = preserved=20 as evidence of the research. Second, the modelling process yielded an=20 intentional context data record =E2=80=93 the RAID diagram itself = =E2=80=93 that would clarify=20 for any future user of the data how each of the depicted records = contributed to=20 the research conclusions. The modelling technique also highlighted where = gaps=20 exist in the data case, either because information was not recorded at = the time=20 (as with some parts of the experimental procedure in this case) or = because it=20 was overwritten or deleted in the course of processing. Had the = researcher been=20 consciously building a data case from the beginning, these deficiencies = might=20 well have been avoided.

The authors estimate the cost of applying the RAID modelling = technique=20 retrospectively to this case study, to this limited extent, to be of the = order=20 of =C2=A3800. A fuller analysis would have taken much longer and = therefore cost more.=20 Ideally, switching researchers over to using the technique when = planning,=20 carrying out and archiving their research should result in them spending = the=20 same amount of time or less on it overall. The authors acknowledge that = this=20 would be difficult if not impossible to achieve while expecting = researchers to=20 perform the modelling manually. They have therefore started to explore = the=20 feasibility of a software tool with the ability to collect associative = and other=20 contextual data semi-automatically by monitoring the computer-based = activity of=20 a researcher (Darlington=20 2011b).

5. RAID and data = management=20 planning

The RAID modelling technique alone does not make a data management = strategy.=20 Even to derive maximum benefit from the technique implies a = sophisticated=20 research environment that can collect associational information largely=20 automatically, establish bidirectional links between RAID diagrams and = the=20 records they depict, update these links when transferring records from = working=20 directories to archival packages, and so on. Moving towards that state = implies=20 some discipline with regard to file name and directory structure = conventions,=20 version control and in-file metadata. There are also many data = management issues=20 that the technique does not address at all: interoperability with other = data=20 being produced within the discipline in terms of file formats, data = models,=20 terminology and methodology; data quality assurance; data security and = access;=20 and licensing. This wider set of issues was addressed by the ERIM = Project=20 through a general data management plan for all IdMRC projects = (Darlington=20 et al. 2010a) and a template for individual projects' data=20 management plans. The plan and template were derived from a set of data=20 management principles (Darlington=20 et al. 2010b) in conjunction with existing guidance, most = notably=20 the specification underlying the DCC's DMP Online tool (Donnelly=20 and Jones 2010). The template calls for each project to keep a data = record=20 manifest, and the place of RAID modelling within the plan is as the = preferred=20 method of completing this manifest.

The motivation behind the project data record manifest is both to = help=20 researchers keep track of their own data, and to help future researchers = understand the data, assess their suitability and re-use them for new = research.=20 It also satisfies the principle that data management plans should = provide a=20 specification of contextualizing methods in order to support = re-purposing. In=20 particular, the relationships recorded in the manifest between data = records=20 satisfy some users' requirements for provenance information.

6. Conclusions

The RAID modelling technique provides a method for visualizing in = context the=20 data records produced in the course of a research activity, emphasizing = the=20 development processes that lead from one data record to another. It aims = to=20 produce easily understandable diagrams, using UML activity diagrams as a = base,=20 for inclusion in data management plans. Such diagrams simplify the task = of=20 tracing the provenance of data in the final result, and of prioritizing = data=20 records for preservation.

While the technique has been developed and validated using six case = studies=20 of real-world engineering research, it has only been used = retrospectively so=20 far. Further work is needed to confirm the benefits of using the = technique in=20 the course of research, for the primary researcher as well as potential=20 re-users. Furthermore, it is recognized that manually modelling a data = case=20 using this method may be burdensome for researchers, especially where = the=20 research involves a large number of small data records, and that the = technique=20 will need to be at least partially automated if it is to gain = acceptance. To=20 this end, a set of use cases and functional requirements for a RAID = associative=20 tool were drawn up. Additional funding was sought and secured from the = JISC for=20 a continuation project to develop this tool, while also expanding the=20 IdMRC data management regime to the entire Department of = Mechanical=20 Engineering. This project is entitled REDm-MED (Research Data Management = for=20 Mechanical Engineering Departments) and runs for six months from = November=20 2011.

Acknowledgements

The paper reports work that was carried out within the Engineering = Research=20 Information Management (ERIM) project funded by JISC through the = Managing=20 Research Data (JISCMRD) Programme.

References

Ball, A. (2010) = Review of the=20 State of the Art of Digital Curation of Research Data, version = 1.2 (Bath,=20 UK: University of Bath) http://opus.bath.ac.uk/19022
Ball, A., Patel, M., = McMahon, C.,=20 Culley, S., Green, S., and Clarkson, J. (2006) "A Grand = Challenge:=20 Immortal Information and Through-Life Knowledge Management (KIM)",=20 International Journal of Digital Curation, Vol. 1, 53-59. = http://www.ijdc.net/ijd= c/article/view/9/
Blessing, L. and = Chakrabarti, A. (2009) DRM: a Design Research = Methodology.=20 (London: Springer)
CCSDS (2002) = Reference model=20 for an Open Archival Information System (OAIS), Blue Book CCSDS = 650.0-B-1=20 (Consultative Committee for Space Data Systems) http://= public.ccsds.org/publications/archive/650x0b1.pdf
CDMC (1986). Issues = and=20 Recommendations Associated with Distributed Computation and Data = Management=20 Systems for the Space Sciences, Committee on Data Management and=20 Computation, Space Science Board, National Research Council. = (Washington, DC:=20 National Academy Press) = http://www.nap.edu/openbook.php?record_id=3D12343&page=3D32
Darlington, M. = (ed.) (2011a)=20 "ERIM Terminology", version 4. University of Bath, last updated April = 12, 2011=20 http://wiki.bath.ac.uk/display/ERIMterminology/ERIM+Terminology+V4=
Darlington, M. = (2011b)=20 RAID Associative Tool Requirements Specification (Bath, UK:=20 University of Bath) http://opus.bath.ac.uk/22811
Darlington, M., Ball, = A.,=20 Howard, T., Culley S., and McMahon, C. (2010a) The Draft = IdMRC=20 Projects Data Management Plan (Bath, UK: University of Bath) = http://opus.bath.ac.uk/22200
Darlington, M., Ball, = A.,=20 Howard, T, McMahon, C. and Culley, S. (2010b). Principles = for=20 Engineering Research Data Management. (Bath, UK: University of = Bath)=20 http://opus.bath.ac.uk/22201
Darlington, M. J., = Culley, S.=20 J., Zhao, S., Austin, S. A., and Tang, L. C. M. (2008) = "Defining a=20 framework for the evaluation of information", International = Journal of=20 Information Quality, Vol. 2, No. 2, 115-132. http://hdl.handle.net/2134/4226<= /A>
Donnelly, M. and = Jones,=20 S. (2010). Template for a Data Management Plan, = version 1.2=20 (Edinburgh, UK: Digital Curation Centre). http://www.dcc.ac.uk/sites/default/files/DMP_template_v1.2_100106.r= tf
Down. K. A. (2010) = "Managing=20 Research Data (JISCMRD)". Joint Information Systems Committee, last = updated=20 August 23, 2010 http://www.ji= sc.ac.uk/whatwedo/programmes/mrd.aspx
Edwards, A. M., Bountra, = C., Kerr,=20 D. J., and Willson, T. M. (2009) "Open Access Chemical and = Clinical=20 Probes to Support Drug Discovery", Nature Chemical Biology = Vol. 5,=20 436-440. http://dx.doi.org/10.= 1038/nchembio0709-436
EOSDP (1986) Earth = Observing=20 System: Data and Information System, Technical Memorandum 87777, = Earth=20 Observing System Data Panel (Washington, DC: National Aeronautics = & Space=20 Administration). http://hdl.handle.net/206= 0/19860021622
EPSRC (2011) "EPSRC = Policy=20 Framework on Research Data". Engineering and Physical Sciences = Research=20 Council, last updated July 8, 2011 http://www.e= psrc.ac.uk/about/standards/researchdata
Evrard, F. and Virbel,=20 J. (1996) Realisation d'un prototype de station de = lecture active=20 et utilisation en milieu professionnel, Rapport du contrat = 9300571=20 (Toulouse: ENSEEIHT INPT)
Groth, P., Gibson, A., and = Velterop,=20 J. (2010) "The Anatomy of a Non-Publication", Information = Services and Use, Vol. 30, Nos. 1-2, 51-56. http://dx.doi.org/10.323= 3/ISU-2010-0613
Higgins, S. (2008) = "The DCC=20 Curation Lifecycle Model", International Journal of Digital = Curation,=20 Vol. 3, No. 1, 134-140. http://www.ijdc.net/ijd= c/article/view/69
Howard, T., Darlington, = M., Ball,=20 A., Culley, S. and McMahon, C. (2010) Understanding and=20 Characterizing Engineering Research Data for its Better = Management (Bath,=20 UK: University of Bath) http://opus.bath.ac.uk/20896/<= /SPAN>
Jones, S. (2009) A = Report on=20 the Range of Policies Required for and Related to Digital = Curation,=20 version 1.2. (Glasgow, UK: Digital Curation Centre) http://www.dcc.ac.uk/sites/default/files/docu= ments/reports/DCC_Curation_Policies_Report.pdf
Mayer, R. J., Menzel, C. = P.,=20 Painter, M. K., deWitte, P. S., Blinn, T., and Perakath, B. = (1995)=20 Information Integration for Concurrent Engineering (IICE) IDEF3 = Process=20 Description Capture Method Report, Technical Report=20 KBSI-IICE-90-STR-01-0592-02 (College Station, TX: Knowledge Based = Systems)=20 http://www.idef.com/pdf/Ide= f3_fn.pdf
NIH (2003) Final NIH = Statement=20 on Sharing Research Data (Bethesda, MD: National Institutes for = Health)=20 http://grants.nih.gov/grants/guide/notice-files/NOT-OD-03-032.html=
NSF (2011) "Grant = Proposal Guide".=20 National Science Foundation. http://www.nsf.gov/pubs/policydocs/pappguide/nsf11001/gpg_2.jsp#dmp
OMG (2009) OMG = Unified=20 Modelling Language (OMG UML), Superstructure, version 2.2 = (Needham, MA:=20 Object Management Group) http://www.o= mg.org/spec/UML/2.2/Superstructure/PDF/
Patel, M. (2010) = Requirements=20 Report, I2S2 Deliverable D1.1 (Bath, UK: University of Bath) = http://www.ukoln.ac.uk/projects/I2S2/documents/I2S2-WP1-= D1.1-RR-Final-100707.pdf
Pienta, A. M., Alter, G. = C. and=20 Lyle, J. A. (2010) "The Enduring Value of Social Science = Research:=20 The Use and Reuse of Primary Research Data". Paper from the = Organisation,=20 Economics and Policy of Scientific Research workshop, Torino, = Italy.=20 http://hdl.handle.net/2027.4= 2/78307
Piwowar, H. A., Day, R. = S. and=20 Fridsma, D. B. (2007) "Sharing Detailed Research Data is = Associated=20 with Increased Citation Rate". PLoS ONE, Vol. 2, No. 3, e308. = http://dx.doi.org= /10.1371/journal.pone.0000308
RIN and NESTA = (2010)=20 Open To All?: Case Studies of Openness in Research (Research=20 Information Network; National Endowment for Science, Technology and = the Arts)=20 http://www.rin.ac.uk/system/files/attachments/NESTA-RIN_Op= en_Science_V01_0.pdf
Stodden, V. (2009) = "Enabling=20 Reproducible Research: Open Licensing for Scientific Innovation".=20 International Journal of Communications Law and Policy, No. = 13, 1-25.=20 http://ww= w.ijclp.net/files/ijclp_web-doc_1-13-2009.pdf
STScI (2011) "Hubble = Space=20 Telescope Publication Statistics". Space Telescope Science Institute. = http://ar= chive.stsci.edu/hst/bibliography/pubstat.html
Wilson, J. A. J., Fraser, = M. A.,=20 Martinez-Uribe, L., Jeffreys, P., Patrick, M., Akram, A., and = Mansoori,=20 T. (2010) "Developing Infrastructure for Research Data = Management at=20 the University of Oxford". Ariadne, No. 65, October http://www.ariadn= e.ac.uk/issue65/wilson-et-al/

=0A= _uacct =3D "UA-10460423-1";=0A= urchinTracker();=0A=

------=_NextPart_001_004B_01CD97FF.955D8080-- ------=_NextPart_000_0000_01CD97FF.95565490 Content-Type: text/css; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable Content-Location: http://journals.tdl.org/styles/common.css BODY { TEXT-ALIGN: center; PADDING-BOTTOM: 0px; BACKGROUND-COLOR: #fbfbf3; = MARGIN: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: 0px; FONT-FAMILY: = Verdana, Arial, Helvetica, sans-serif; COLOR: #111; PADDING-TOP: 0px } DIV { TEXT-ALIGN: left; LINE-HEIGHT: 140% } TABLE { BORDER-BOTTOM: 0px; BORDER-LEFT: 0px; BORDER-SPACING: 0; FONT-SIZE: = 1em; BORDER-TOP: 0px; BORDER-RIGHT: 0px } FORM { MARGIN: 0px } A { TEXT-DECORATION: underline } A:link { COLOR: #375 } A:active { COLOR: #253 } A:visited { COLOR: #375 } A:hover { BACKGROUND: #cdc; COLOR: #253 } A.plain { TEXT-DECORATION: none } UL { PADDING-BOTTOM: 0px; MARGIN: 0.25em 0px 0.75em; PADDING-LEFT: 2.5em; = PADDING-RIGHT: 0px; PADDING-TOP: 0px } TT { FONT-SIZE: 1.25em } LABEL { =09 } LABEL.error { COLOR: #900 } INPUT.textField { BORDER-BOTTOM: #e8e8e1 2px solid; BORDER-LEFT: #666 2px solid; = BACKGROUND-COLOR: #f0f0e8; FONT-FAMILY: Verdana, Arial, Helvetica, = sans-serif; COLOR: #000; FONT-SIZE: 1em; BORDER-TOP: #666 2px solid; = BORDER-RIGHT: #e8e8e1 2px solid } SELECT.selectMenu { BORDER-BOTTOM: #e8e8e1 2px solid; BORDER-LEFT: #666 2px solid; = BACKGROUND-COLOR: #f0f0e8; FONT-FAMILY: Verdana, Arial, Helvetica, = sans-serif; COLOR: #000; FONT-SIZE: 1em; BORDER-TOP: #666 2px solid; = BORDER-RIGHT: #e8e8e1 2px solid } TEXTAREA.textArea { BORDER-BOTTOM: #e8e8e1 2px solid; BORDER-LEFT: #666 2px solid; = BACKGROUND-COLOR: #f0f0e8; FONT-FAMILY: Verdana, Arial, Helvetica, = sans-serif; COLOR: #000; FONT-SIZE: 1em; BORDER-TOP: #666 2px solid; = BORDER-RIGHT: #e8e8e1 2px solid } INPUT.uploadField { BORDER-BOTTOM: #e8e8e1 2px solid; BORDER-LEFT: #666 2px solid; = BACKGROUND-COLOR: #f0f0e8; FONT-FAMILY: Verdana, Arial, Helvetica, = sans-serif; COLOR: #000; FONT-SIZE: 1em; BORDER-TOP: #666 2px solid; = BORDER-RIGHT: #e8e8e1 2px solid } INPUT.button { BACKGROUND-COLOR: #e8e8e1; PADDING-LEFT: 0.5em; PADDING-RIGHT: 0.5em; = FONT-SIZE: 1em } INPUT.defaultButton { BACKGROUND-COLOR: #375; COLOR: #fbfbf3; FONT-WEIGHT: bold } #container { MIN-WIDTH: 730px !important; TEXT-ALIGN: center; LINE-HEIGHT: 125%; = MARGIN: 0px auto; WIDTH: 100% !important } #header { TEXT-ALIGN: center; BACKGROUND-COLOR: #aba; WIDTH: 100% } #headerTitle { TEXT-ALIGN: left !important; PADDING-BOTTOM: 0px; MARGIN: 0px auto; = PADDING-LEFT: 0px; WIDTH: 100%; PADDING-RIGHT: 0px; PADDING-TOP: 0px } #header H1 { PADDING-BOTTOM: 0.25em; LINE-HEIGHT: 130%; MARGIN: 0px auto; = PADDING-LEFT: 10%; PADDING-RIGHT: 0px; FONT-FAMILY: Georgia, "Times New = Roman", Times, serif; FONT-WEIGHT: normal; PADDING-TOP: 0.5em } #footer { POSITION: static; TEXT-ALIGN: center; BACKGROUND-COLOR: #aba; = MIN-HEIGHT: 50px; WIDTH: 100%; CLEAR: both } #footerContent { MARGIN: 0px auto; PADDING-LEFT: 10%; WIDTH: 100% } #main { PADDING-BOTTOM: 2em; MARGIN: 0px auto; PADDING-LEFT: 0em; WIDTH: 80%; = PADDING-RIGHT: 0em; PADDING-TOP: 0.5em } #main H2 { LINE-HEIGHT: 130%; MARGIN: 0em 1em 0.5em 0em; FONT-FAMILY: Georgia, = "Times New Roman", Times, serif; FONT-WEIGHT: normal; PADDING-TOP: 0.5em } #main H3 { MARGIN: 0em 1em 0.5em 0em; FONT-FAMILY: Georgia, "Times New Roman", = Times, serif; FONT-WEIGHT: normal; PADDING-TOP: 0em } #navbar { BORDER-BOTTOM: #000 2px dotted; PADDING-BOTTOM: 0.5em; MARGIN-RIGHT: = 0px } #breadcrumb { FONT-SIZE: 0.7em; PADDING-TOP: 1em } #content { PADDING-BOTTOM: 0px; MARGIN: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: = 0px; FONT-SIZE: 0.7em; BORDER-TOP: #000 2px dotted; PADDING-TOP: 0.5em } #content H3 { LINE-HEIGHT: 1.35em; MARGIN: 0em 1em 0.25em 0em; FONT-FAMILY: Georgia, = "Times New Roman", Times, serif; FONT-SIZE: 1.8em; FONT-WEIGHT: normal; = PADDING-TOP: 0.75em } #content H4 { MARGIN: 0.75em 1em 0.25em 0em; FONT-FAMILY: Georgia, "Times New Roman", = Times, serif; FONT-SIZE: 1.5em; FONT-WEIGHT: normal } #content H5 { MARGIN: 0em 1em 0.25em 0em; FONT-SIZE: 1em; FONT-WEIGHT: bold; = PADDING-TOP: 0.75em } #accessKey { MARGIN-BOTTOM: 2em } #accessKey IMG { PADDING-BOTTOM: 0px; MARGIN: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: = 0px; VERTICAL-ALIGN: middle; PADDING-TOP: 0px } #content IMG.accessLogo { PADDING-BOTTOM: 0px; MARGIN: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: = 0px; VERTICAL-ALIGN: middle; PADDING-TOP: 0px } #navbar A { LETTER-SPACING: 0.05em; FONT-SIZE: 0.65em } #navbar A:link { =09 } #navbar A:active { =09 } #navbar A:visited { =09 } #navbar A:hover { =09 } #breadcrumb A { TEXT-DECORATION: none } #breadcrumb A.current { FONT-WEIGHT: bold } #announcementsHome { MARGIN: 2em 0px; WIDTH: 100% } #announcementsHome H3 { TEXT-ALIGN: center } #announcements { WIDTH: 100% } #announcements H3 { TEXT-ALIGN: center } TABLE.announcements { WIDTH: 100% } TABLE.announcements TD { PADDING-BOTTOM: 0.25em; PADDING-LEFT: 0.5em; PADDING-RIGHT: 0.5em; = PADDING-TOP: 0.25em } TABLE.announcements TD.nodata { TEXT-ALIGN: center; FONT-STYLE: italic } TABLE.announcements TD.headseparator { LINE-HEIGHT: 1%; FONT-SIZE: 0.1em; BORDER-TOP: #000 1px dotted } TABLE.announcements TD.endseparator { LINE-HEIGHT: 10%; FONT-SIZE: 0.25em; BORDER-TOP: #000 1px dotted } TABLE.announcements TD.separator { LINE-HEIGHT: 1%; FONT-SIZE: 0.1em; BORDER-TOP: #ddddd0 1px dotted } TABLE.announcements TR.intro { =09 } TABLE.announcements TD.intro { =09 } TABLE.announcements TR.title { VERTICAL-ALIGN: top } TABLE.announcements TD.title { WIDTH: 85% } TABLE.announcements TD.title H4 { =09 } TABLE.announcements TR.description { VERTICAL-ALIGN: top } TABLE.announcements TD.description { WIDTH: 85% } TABLE.announcements TR.details { VERTICAL-ALIGN: bottom } TABLE.announcements TD.posted { FONT-STYLE: italic; PADDING-TOP: 1em } TABLE.announcements TD.more { TEXT-ALIGN: right; WIDTH: 15% } TABLE.announcementsMore { WIDTH: 100% } TABLE.announcementsMore TD { TEXT-ALIGN: right; PADDING-TOP: 1.5em } H4.tocSectionTitle { =09 } TABLE.tocArticle { WIDTH: 100% } TABLE.tocArticle TD.tocTitle { WIDTH: 70%; HEIGHT: 100% } TABLE.tocArticle TD.tocGalleys { TEXT-ALIGN: right; WIDTH: 30% } TABLE.tocArticle TD.tocAuthors { FONT-STYLE: italic; PADDING-LEFT: 30px; VERTICAL-ALIGN: top } TABLE.tocArticle TD.tocPages { TEXT-ALIGN: right; VERTICAL-ALIGN: top } .tocArticleCoverImage IMG { BORDER-BOTTOM: 0px; BORDER-LEFT: 0px; MARGIN: 0px 1em 1em 0px; WIDTH: = 100px; FLOAT: left; BORDER-TOP: 0px; BORDER-RIGHT: 0px } #homepageImage IMG { BORDER-BOTTOM: 0px; TEXT-ALIGN: center; BORDER-LEFT: 0px; MARGIN: 0px = auto; DISPLAY: block; BORDER-TOP: 0px; BORDER-RIGHT: 0px } .homepageImage IMG { BORDER-BOTTOM: 0px; TEXT-ALIGN: center; BORDER-LEFT: 0px; MARGIN: 1em = 1em 1em 0px; WIDTH: 100px; FLOAT: left; BORDER-TOP: 0px; BORDER-RIGHT: = 0px } #issueCoverImage IMG { BORDER-BOTTOM: 0px; BORDER-LEFT: 0px; DISPLAY: block; BORDER-TOP: 0px; = BORDER-RIGHT: 0px } .issueCoverImage IMG { BORDER-BOTTOM: 0px; BORDER-LEFT: 0px; MARGIN: 1em 1em 1em 0px; WIDTH: = 100px; FLOAT: left; BORDER-TOP: 0px; BORDER-RIGHT: 0px } #issueCoverImage A:link { =09 } .issueCoverImage A:link { =09 } #issueCoverImage A:active { =09 } .issueCoverImage A:active { =09 } #issueCoverImage A:visited { =09 } .issueCoverImage A:visited { =09 } #issueCoverImage A:hover { =09 } .issueCoverImage A:hover { =09 } #footer DIV.debugStats { FONT-SIZE: 0.6em } SPAN.disabled { COLOR: #666 } LABEL.disabled { COLOR: #666 } A.action { TEXT-TRANSFORM: uppercase; FONT-SIZE: 0.85em } A.file { TEXT-TRANSFORM: uppercase; FONT-SIZE: 0.85em } A.icon { TEXT-DECORATION: none } A.icon IMG { BORDER-BOTTOM: 0px; BORDER-LEFT: 0px; BORDER-TOP: 0px; BORDER-RIGHT: = 0px } A.icon:hover { BACKGROUND: none transparent scroll repeat 0% 0% } SPAN.formRequired { COLOR: #333; FONT-SIZE: 0.9em } SPAN.instruct { =09 } SPAN.heading { TEXT-TRANSFORM: uppercase; FONT-SIZE: 0.85em } SPAN.highlight { BORDER-BOTTOM: #000 1px dotted } .nowrap { WHITE-SPACE: nowrap } PRE { BACKGROUND-COLOR: #f0f0e8; COLOR: #000; FONT-SIZE: 1.25em } TABLE.info { =09 } TABLE.info TD { PADDING-BOTTOM: 0.5em; PADDING-LEFT: 0px; PADDING-RIGHT: 0.5em; = PADDING-TOP: 0px } TABLE.listing { =09 } TABLE.listing TR.highlight { BACKGROUND: yellow } TABLE.listing TD { PADDING-BOTTOM: 0.25em; PADDING-LEFT: 0.5em; PADDING-RIGHT: 1.5em; = PADDING-TOP: 0.25em } TABLE.listing TR.heading TD { PADDING-BOTTOM: 1em; LINE-HEIGHT: 120%; TEXT-TRANSFORM: uppercase; = PADDING-LEFT: 0.5em; PADDING-RIGHT: 1.5em; FONT-SIZE: 0.85em; = FONT-WEIGHT: normal; PADDING-TOP: 0.75em } TABLE.listing TD.heading { PADDING-BOTTOM: 1em; LINE-HEIGHT: 120%; TEXT-TRANSFORM: uppercase; = PADDING-LEFT: 0.5em; PADDING-RIGHT: 1.5em; FONT-SIZE: 0.85em; = FONT-WEIGHT: normal; PADDING-TOP: 0.75em } TABLE.info TD.heading { PADDING-BOTTOM: 1em; LINE-HEIGHT: 120%; TEXT-TRANSFORM: uppercase; = PADDING-LEFT: 0.5em; PADDING-RIGHT: 1.5em; FONT-SIZE: 0.85em; = FONT-WEIGHT: normal; PADDING-TOP: 0.75em } TABLE.listing TR.fastTracked { BACKGROUND-COLOR: #aba } TABLE.info TD.heading { PADDING-LEFT: 0px } TABLE.listing TD.nodata { TEXT-ALIGN: center; FONT-STYLE: italic } TABLE.info TD.nodata { TEXT-ALIGN: center; FONT-STYLE: italic } TABLE.listing TD.headseparator { LINE-HEIGHT: 1%; FONT-SIZE: 0.1em; BORDER-TOP: #000 1px dotted } TABLE.listing TD.endseparator { LINE-HEIGHT: 10%; FONT-SIZE: 0.25em; BORDER-TOP: #000 1px dotted } TABLE.listing TD.separator { LINE-HEIGHT: 1%; FONT-SIZE: 0.1em; BORDER-TOP: #ddddd0 1px dotted } TABLE.info TD.separator { LINE-HEIGHT: 1%; FONT-SIZE: 0.1em; BORDER-TOP: #ddddd0 1px dotted } TABLE.data { =09 } TABLE.data TR { =09 } TABLE.data TD { PADDING-BOTTOM: 0.25em } TABLE.data TD.label { PADDING-RIGHT: 1em } TABLE.data TD.value { =09 } TABLE.data TD.separator { PADDING-BOTTOM: 0.5em; LINE-HEIGHT: 1%; PADDING-LEFT: 0.5em; = PADDING-RIGHT: 0.5em; FONT-SIZE: 0.1em; PADDING-TOP: 0.5em } TABLE.data TD.heading { PADDING-LEFT: 0px; PADDING-RIGHT: 0px } TABLE.nested TR { PADDING-BOTTOM: 0px; MARGIN: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: = 0px; PADDING-TOP: 0px } SPAN.nested { PADDING-BOTTOM: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: 4px; FONT-SIZE: = 1.2em; PADDING-TOP: 0px } SPAN.formError { COLOR: #900; FONT-SIZE: 1em; FONT-WEIGHT: bold } UL.formErrorList { COLOR: #900 } UL.menu { PADDING-BOTTOM: 0px; MARGIN: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: = 0px; PADDING-TOP: 0px } UL.menu LI { PADDING-BOTTOM: 0px; MARGIN: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: = 1.5em; DISPLAY: inline; PADDING-TOP: 0px } UL.menu LI.current { FONT-WEIGHT: bold } UL.menu A { TEXT-TRANSFORM: uppercase; FONT-SIZE: 0.85em; TEXT-DECORATION: none } UL.steplist { PADDING-BOTTOM: 0px; LIST-STYLE-TYPE: decimal; MARGIN: 0px; = PADDING-LEFT: 0px; PADDING-RIGHT: 0px; PADDING-TOP: 0px } UL.steplist LI { PADDING-BOTTOM: 0px; TEXT-TRANSFORM: uppercase; MARGIN: 0px; = PADDING-LEFT: 0px; PADDING-RIGHT: 0.5em; DISPLAY: inline; FONT-SIZE: = 0.85em; PADDING-TOP: 0px } UL.steplist LI.current { FONT-WEIGHT: bold } UL.steplist A { TEXT-DECORATION: none } UL.plain { LIST-STYLE-TYPE: none; PADDING-LEFT: 1.5em } UL.filter { PADDING-BOTTOM: 1.5em; LIST-STYLE-TYPE: none; MARGIN: 0px; = PADDING-LEFT: 0px; PADDING-RIGHT: 0px; PADDING-TOP: 1.5em } UL.filter LI { PADDING-RIGHT: 1.5em; DISPLAY: inline } DIV.separator { BORDER-BOTTOM: #000 1px dotted; PADDING-BOTTOM: 0px; LINE-HEIGHT: 25%; = MARGIN-TOP: 1em; PADDING-LEFT: 0px; WIDTH: 100%; PADDING-RIGHT: 0px; = MARGIN-BOTTOM: 0.25em; FONT-SIZE: 0.5em; PADDING-TOP: 0px } DIV.progressbar { BACKGROUND-IMAGE: url(../templates/images/progbg.gif); Z-INDEX: 1; = WIDTH: 505px; BACKGROUND-REPEAT: no-repeat; HEIGHT: 27px } ------=_NextPart_000_0000_01CD97FF.95565490 Content-Type: text/css; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable Content-Location: http://journals.tdl.org/styles/articleView.css #body { MARGIN: 0px auto; WIDTH: 95% } #container { MIN-WIDTH: 150px !important } #main { MARGIN: 0px; WIDTH: 95% } #main H2 { FONT-SIZE: 1em } #main H5 { MARGIN: 0em 1em 0.5em 0em; FONT-FAMILY: Georgia, "Times New Roman", = Times, serif; FONT-SIZE: 1.3em; FONT-WEIGHT: normal; PADDING-TOP: 0em } #main H6 { PADDING-BOTTOM: 0px; MARGIN: 0.5em 1em 0.5em 0em; PADDING-LEFT: 0px; = PADDING-RIGHT: 0px; FONT-FAMILY: Georgia, "Times New Roman", Times, = serif; FONT-SIZE: 1.2em; FONT-WEIGHT: normal; PADDING-TOP: 0px } #content { BORDER-BOTTOM: medium none; BORDER-LEFT: medium none; BORDER-TOP: = medium none; BORDER-RIGHT: medium none } #content IMG.accessLogo { PADDING-BOTTOM: 0px; MARGIN: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: = 0px; DISPLAY: inline; VERTICAL-ALIGN: middle; PADDING-TOP: 0px } #topBar { PADDING-BOTTOM: 2.5em; WIDTH: 100%; PADDING-TOP: 1em } #articleFontSize { FLOAT: right } #articleFontSize IMG { PADDING-BOTTOM: 0px; MARGIN: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: = 0px; DISPLAY: inline; VERTICAL-ALIGN: middle; PADDING-TOP: 0px } #accessKey { FLOAT: left } #accessKey IMG { PADDING-BOTTOM: 0px; MARGIN: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: = 0px; DISPLAY: inline; VERTICAL-ALIGN: middle; PADDING-TOP: 0px } #articleCoverImage { PADDING-BOTTOM: 1em; WIDTH: 100%; CLEAR: left; PADDING-TOP: 1em } #articleCoverImage IMG { BORDER-BOTTOM: 0px; BORDER-LEFT: 0px; DISPLAY: block; BORDER-TOP: 0px; = BORDER-RIGHT: 0px } DIV.rtSeparator { BORDER-BOTTOM: #000 2px dotted; PADDING-BOTTOM: 0px; LINE-HEIGHT: 0px; = PADDING-LEFT: 0px; WIDTH: 100%; PADDING-RIGHT: 0px; PADDING-TOP: 0px } DIV.rtSeparatorThin { BORDER-BOTTOM: #000 1px dotted; PADDING-BOTTOM: 5px; LINE-HEIGHT: 0px; = PADDING-LEFT: 0px; WIDTH: 100%; PADDING-RIGHT: 0px; PADDING-TOP: 5px } DIV.rtBlock { =09 } DIV.rtBlock A { TEXT-TRANSFORM: none; TEXT-DECORATION: none } DIV.rtBlock UL { PADDING-BOTTOM: 0px; MARGIN: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: = 0px; PADDING-TOP: 0px } DIV.rtBlock LI { LIST-STYLE-TYPE: none } SPAN.rtSubtitle { TEXT-TRANSFORM: uppercase; FONT-SIZE: 0.85em } A.rtAction { TEXT-TRANSFORM: uppercase; FONT-SIZE: 0.9em; TEXT-DECORATION: none } TABLE { BACKGROUND-COLOR: #f0f0e8 } TABLE.bm { BORDER-BOTTOM: #000 1px solid; BORDER-LEFT: #000 1px solid; BORDER-TOP: = #000 1px solid; BORDER-RIGHT: #000 1px solid } .tl-default { FONT-WEIGHT: bold } .tl-main-part { FONT-WEIGHT: bold } DT { WIDTH: 80px; DISPLAY: inline; FLOAT: left; MARGIN-LEFT: 20px } DD { MARGIN-LEFT: 100px } ------=_NextPart_000_0000_01CD97FF.95565490 Content-Type: text/css; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable Content-Location: http://journals.tdl.org/styles/rt.css #headerTitle { WIDTH: 100% } #header H1 { TEXT-ALIGN: right; PADDING-BOTTOM: 0.25em; PADDING-LEFT: 0em; = PADDING-RIGHT: 0em; FONT-SIZE: 1.2em; PADDING-TOP: 0.25em } #container { MIN-WIDTH: 615px } #body { MARGIN: auto; WIDTH: 615px } #footer { TEXT-ALIGN: center; PADDING-BOTTOM: 0px; BACKGROUND-COLOR: #aba; = PADDING-LEFT: 0px; PADDING-RIGHT: 0px; PADDING-TOP: 0px } #footerContent { WIDTH: 615px } #main { MARGIN: 0px auto } #main H2 { MARGIN: 0em 1em 0.25em 0em; FONT-SIZE: 1.5em; PADDING-TOP: 0px } #content H3 { FONT-SIZE: 1.5em } #main H6 { MARGIN-BOTTOM: -0.5em } ------=_NextPart_000_0000_01CD97FF.95565490 Content-Type: text/css; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable Content-Location: http://journals.tdl.org/plugins/themes/tdl/tdl.css HTML { BACKGROUND: url(../tdl/images/bg-default.png) #2c3342 repeat-x left top } BODY { TEXT-ALIGN: center; PADDING-BOTTOM: 0px; MARGIN: 0px; BACKGROUND: none = transparent scroll repeat 0% 0%; COLOR: #02161f; PADDING-TOP: 9px } #navbar { LINE-HEIGHT: 110% } #body { BORDER-BOTTOM: 0px; BORDER-LEFT: 0px; PADDING-BOTTOM: 40px !important; = MARGIN: 0px 0px 40px; MIN-HEIGHT: 800px; PADDING-LEFT: 0px; WIDTH: = 1000px !important; PADDING-RIGHT: 0px; BACKGROUND: #fff; FLOAT: right; = HEIGHT: 100%; BORDER-TOP: 0px; BORDER-RIGHT: 0px; PADDING-TOP: 0px; = -webkit-border-bottom-left-radius: 10px; = -webkit-border-bottom-right-radius: 10px; -moz-border-radius-bottomleft: = 10px; -moz-border-radius-bottomright: 10px; -border-radius: 10px; = -webkit-border-top-left-radius: 10px; -webkit-border-top-right-radius: = 10px; -moz-border-radius-topleft: 10px; -moz-border-radius-topright: = 10px } LABEL.error { COLOR: #f60 } INPUT.defaultButton { BACKGROUND: #fff; COLOR: #3a5662 } #container { BORDER-BOTTOM: 0px; BORDER-LEFT: 0px; MARGIN: auto; MIN-HEIGHT: 700px; = WIDTH: 1000px !important; BACKGROUND: white; BORDER-TOP: 0px; = BORDER-RIGHT: 0px; -border-radius: 10px; -webkit-border-top-left-radius: = 10px; -webkit-border-top-right-radius: 10px; -moz-border-radius-topleft: = 10px; -moz-border-radius-topright: 10px } #header { BORDER-BOTTOM: medium none; BORDER-LEFT: medium none; BACKGROUND-COLOR: = #fff; HEIGHT: 50px; BORDER-TOP: medium none; BORDER-RIGHT: medium none; = -border-radius: 10px; -webkit-border-top-left-radius: 10px; = -webkit-border-top-right-radius: 10px; -moz-border-radius-topleft: 10px; = -moz-border-radius-topright: 10px } #headerTitle { WIDTH: 100% } #headerTitle IMG { BORDER-BOTTOM: medium none; BORDER-LEFT: medium none; BORDER-TOP: = medium none; BORDER-RIGHT: medium none } #headerTitle H1 { POSITION: absolute; PADDING-BOTTOM: 0px; MARGIN: 0px; PADDING-LEFT: = 0px; PADDING-RIGHT: 0px; COLOR: white; FONT-SIZE: 0.01em; PADDING-TOP: = 0px } #headerTitle IMG { POSITION: absolute; PADDING-BOTTOM: 10px !important; WIDTH: 258px; = MARGIN-BOTTOM: 30px !important; HEIGHT: 43px; TOP: 10px; LEFT: 40px } #footer { BACKGROUND-COLOR: #040; COLOR: #fff } #footerContent { COLOR: #fff } #main { BORDER-BOTTOM: medium none; BORDER-LEFT: medium none; PADDING-BOTTOM: = 0px; MARGIN: 0px; MIN-HEIGHT: 800px; PADDING-LEFT: 40px; WIDTH: 770px; = COLOR: #4b4b4b; OVERFLOW: visible; BORDER-TOP: medium none; = BORDER-RIGHT: medium none; -webkit-border-bottom-left-radius: 10px; = -webkit-border-bottom-right-radius: 10px; -moz-border-radius-bottomleft: = 10px; -moz-border-radius-bottomright: 10px; -border-radius: 10px } #main > H2 { BORDER-BOTTOM: medium none; BORDER-LEFT: medium none; COLOR: #3a5662; = FONT-SIZE: 1.6em; BORDER-TOP: medium none; FONT-WEIGHT: bold; = BORDER-RIGHT: medium none } #main A { COLOR: #42516c; TEXT-DECORATION: underline } #main A:hover { COLOR: #42516c; TEXT-DECORATION: none } #container #main { MARGIN-TOP: -9px } #container #body #main { MARGIN-TOP: 0px } #main H2 { FONT-FAMILY: "Interstate Light", "Arial Narrow", Helvetica, Sans-Serif } #main H3 { FONT-FAMILY: "Interstate Light", "Arial Narrow", Helvetica, Sans-Serif } #content H1 { FONT-FAMILY: Arial, Helvetica, Sans-Serif } #content H2 { FONT-FAMILY: Arial, Helvetica, Sans-Serif } #content H3 { FONT-FAMILY: Arial, Helvetica, Sans-Serif } #content H4 { FONT-FAMILY: Arial, Helvetica, Sans-Serif } #content H3 { BORDER-BOTTOM: #c7c5c5 1px solid; DISPLAY: block; FONT-FAMILY: Arial, = Helvetica, Sans-Serif; FONT-SIZE: 1.5em; OVERFLOW: hidden; FONT-WEIGHT: = normal } #content H4 { MARGIN: 0em 1em 0.25em 0em; FONT-FAMILY: Arial, Helvetica, Sans-Serif; = FONT-SIZE: 1.2em; FONT-WEIGHT: normal; PADDING-TOP: 0.75em } #content H5 { MARGIN: 0em 1em 0.25em 0em; FONT-FAMILY: Arial, Helvetica, Sans-Serif; = FONT-SIZE: 1em; FONT-WEIGHT: bold; PADDING-TOP: 0.75em } #content H1 { FONT: 2em "Interstate Light", "Arial Narrow", Helvetica, Sans-Serif; = COLOR: #3a5662 } #content H2 { FONT-SIZE: 1.6em } A { COLOR: #3a5662; TEXT-DECORATION: none } A:visited { COLOR: #3a5662; TEXT-DECORATION: none } A:hover { TEXT-DECORATION: underline } A:link { COLOR: #3a5662 } #content A { BACKGROUND-COLOR: transparent; TEXT-DECORATION: underline } #content A:visited { BACKGROUND-COLOR: transparent; TEXT-DECORATION: underline } #content A:hover { BACKGROUND-COLOR: transparent; TEXT-DECORATION: underline } #navbar { BORDER-BOTTOM: 0px; BORDER-LEFT: 0px; PADDING-LEFT: 40px; WIDTH: 960px; = BACKGROUND: url(../tdl/images/breadcrumbbg.jpg) repeat-x 0px 0px; = MARGIN-LEFT: -40px; FONT-SIZE: 1.1em; BORDER-TOP: 0px; MARGIN-RIGHT: = 40px; BORDER-RIGHT: 0px } #navbar UL.menu LI A { MARGIN-BOTTOM: 10px } #navbar UL.menu LI A { TEXT-ALIGN: center; MARGIN-BOTTOM: 10px; COLOR: #fff; FONT-WEIGHT: = normal; TEXT-DECORATION: none } #navbar UL.menu LI A:visited { TEXT-ALIGN: center; MARGIN-BOTTOM: 10px; COLOR: #fff; FONT-WEIGHT: = normal; TEXT-DECORATION: none } #navbar UL.menu LI A:hover { BACKGROUND-COLOR: transparent; COLOR: #183d48; TEXT-DECORATION: none } #breadcrumb { PADDING-BOTTOM: 0px; LINE-HEIGHT: 2.5em; PADDING-LEFT: 8px; WIDTH: = 792px; PADDING-RIGHT: 0px; HEIGHT: 26px; COLOR: #646464 !important; = FONT-SIZE: 0.8em; RIGHT: auto; PADDING-TOP: 0px; LEFT: auto } #breadcrumb A { PADDING-BOTTOM: 0px; MARGIN: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: = 0px; COLOR: #646464 !important; TEXT-DECORATION: none; PADDING-TOP: 0px } #breadcrumb A:visited { PADDING-BOTTOM: 0px; MARGIN: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: = 0px; COLOR: #646464 !important; TEXT-DECORATION: none; PADDING-TOP: 0px } #breadcrumb A:hover { BACKGROUND-COLOR: transparent; TEXT-DECORATION: underline } #breadcrumb A.current { FONT-WEIGHT: normal } #content { BORDER-BOTTOM: 0px; BORDER-LEFT: 0px; PADDING-BOTTOM: 0px; LINE-HEIGHT: = 1.5em; MARGIN-BOTTOM: 0px; BACKGROUND: white; FONT-SIZE: 12px; = BORDER-TOP: 0px; BORDER-RIGHT: 0px } #content P { PADDING-BOTTOM: 0px; MARGIN-BOTTOM: 0px } #content UL { PADDING-BOTTOM: 0px; MARGIN-BOTTOM: 0px } #content H1 { LINE-HEIGHT: 1.2em } SPAN.highlight { BORDER-BOTTOM: #040 1px dotted } TABLE.listing TR.highlight { BACKGROUND: #fcff64 } TABLE.listing TR.fastTracked { BACKGROUND-COLOR: #82bd86 } TABLE.listing TD.headseparator { BORDER-TOP: #040 1px dotted } TABLE.listing TD.endseparator { BORDER-TOP: #040 1px dotted } SPAN.formError { COLOR: #f60 } UL.formErrorList { COLOR: #f60 } DIV.separator { BORDER-BOTTOM: #c7c5c5 1px solid; PADDING-BOTTOM: 0px; LINE-HEIGHT: 0; = MARGIN-TOP: 0px; PADDING-LEFT: 0px; WIDTH: 100%; PADDING-RIGHT: 0px; = MARGIN-BOTTOM: 0px; FONT-SIZE: 0.5em; PADDING-TOP: 0px } #rightSidebar { TEXT-ALIGN: center; PADDING-BOTTOM: 1em; BACKGROUND-COLOR: #fff; = MARGIN-TOP: 30pt; PADDING-LEFT: 0em; PADDING-RIGHT: 3px; FLOAT: right; = MARGIN-LEFT: 0px; FONT-SIZE: 0.65em; MARGIN-RIGHT: 3px; PADDING-TOP: 1em } #rightSidebar SPAN.blockTitle { COLOR: #4b4b4b; FONT-WEIGHT: bold } #rightSidebar SPAN.blockSubtitle { COLOR: #4b4b4b; FONT-WEIGHT: bold } #rightSidebar UL { LIST-STYLE-TYPE: none; PADDING-LEFT: 4px; MARGIN-LEFT: 4px } #rightSidebar TABLE { BACKGROUND: none transparent scroll repeat 0% 0% } #rightSidebar A.blockTitle { PADDING-BOTTOM: 0px; MARGIN: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: = 0px; COLOR: #42516c; FONT-SIZE: 1.2em; FONT-WEIGHT: bold; = TEXT-DECORATION: none; PADDING-TOP: 0px } #rightSidebar A.blockTitle:visited { PADDING-BOTTOM: 0px; MARGIN: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: = 0px; COLOR: #42516c; FONT-SIZE: 1.2em; FONT-WEIGHT: bold; = TEXT-DECORATION: none; PADDING-TOP: 0px } #rightSidebar A.blockTitle:hover { BACKGROUND-COLOR: transparent; TEXT-DECORATION: underline } #rightSidebar UL LI A { PADDING-BOTTOM: 0px; MARGIN: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: = 0px; COLOR: #42516c; FONT-WEIGHT: bold; TEXT-DECORATION: none; = PADDING-TOP: 0px } #rightSidebar UL LI A:visited { PADDING-BOTTOM: 0px; MARGIN: 0px; PADDING-LEFT: 0px; PADDING-RIGHT: = 0px; COLOR: #42516c; FONT-WEIGHT: bold; TEXT-DECORATION: none; = PADDING-TOP: 0px } #rightSidebar UL LI A:hover { PADDING-BOTTOM: 0px; BACKGROUND-COLOR: transparent; MARGIN: 0px; = PADDING-LEFT: 0px; PADDING-RIGHT: 0px; COLOR: #42516c; TEXT-DECORATION: = underline; PADDING-TOP: 0px } .homepageImage IMG { MARGIN-TOP: 25px !important } #content H3 { MARGIN-TOP: 15px !important } INPUT { BORDER-BOTTOM: #000000 1px solid; BORDER-LEFT: #000000 1px solid; = FONT-FAMILY: Arial, Helvetica, Sans-Serif !important; BORDER-TOP: = #000000 1px solid; BORDER-RIGHT: #000000 1px solid } SELECT { BORDER-BOTTOM: #000000 1px solid; BORDER-LEFT: #000000 1px solid; = FONT-FAMILY: Arial, Helvetica, Sans-Serif !important; BORDER-TOP: = #000000 1px solid; BORDER-RIGHT: #000000 1px solid } TEXTAREA { BORDER-BOTTOM: #000000 1px solid; BORDER-LEFT: #000000 1px solid; = FONT-FAMILY: Arial, Helvetica, Sans-Serif !important; BORDER-TOP: = #000000 1px solid; BORDER-RIGHT: #000000 1px solid } INPUT { PADDING-BOTTOM: 3px; PADDING-LEFT: 3px; PADDING-RIGHT: 3px; = PADDING-TOP: 3px } TEXTAREA { PADDING-BOTTOM: 3px; PADDING-LEFT: 3px; PADDING-RIGHT: 3px; = PADDING-TOP: 3px } .button { CURSOR: pointer } .headseparator { BORDER-BOTTOM: medium none; BORDER-LEFT: medium none; BORDER-TOP: = medium none; BORDER-RIGHT: medium none } .endseparator { BORDER-TOP: #c7c5c5 1px solid } #sidebarUser A:hover { BACKGROUND-COLOR: transparent !important } ------=_NextPart_000_0000_01CD97FF.95565490 Content-Type: text/css; charset="iso-8859-1" Content-Transfer-Encoding: 7bit Content-Location: http://journals.tdl.org/styles/fontSmall.css BODY { FONT-SIZE: 0.8em } ------=_NextPart_000_0000_01CD97FF.95565490 Content-Type: text/css; charset="iso-8859-1" Content-Transfer-Encoding: 7bit Content-Location: http://journals.tdl.org/styles/fontMedium.css BODY { FONT-SIZE: 1em } ------=_NextPart_000_0000_01CD97FF.95565490 Content-Type: text/css; charset="iso-8859-1" Content-Transfer-Encoding: 7bit Content-Location: http://journals.tdl.org/styles/fontLarge.css BODY { FONT-SIZE: 1.2em } ------=_NextPart_000_0000_01CD97FF.95565490 Content-Type: text/css; charset="iso-8859-1" Content-Transfer-Encoding: 7bit Content-Location: http://journals.tdl.org/tdl/rt.css BODY { COLOR: #02161f } #container { TEXT-ALIGN: left; MARGIN: 0px; WIDTH: 165px !important; HEIGHT: auto } HTML { BACKGROUND: #ffffff } #main { TEXT-ALIGN: left; WIDTH: 165px !important } #main H5 { FONT: bold 1.3em Arial, Helvetica, Sans-Serif } #main H6 { FONT: bold 1.1em Arial, Helvetica, Sans-Serif } rtseparator { BORDER-BOTTOM: #c7c5c5 1px solid } ------=_NextPart_000_0000_01CD97FF.95565490 Content-Type: application/octet-stream Content-Transfer-Encoding: quoted-printable Content-Location: http://journals.tdl.org/jodi/article/viewRST/5917/5892 =EF=BB=BF Ball

JoDI
Vol 13, No 1 (2012): Open Repositories 2011

Table of Contents

Reading Tools

Visualizing Resear...

Ball, Darlington, Howard, McMahon, Culley

Abstract
Review policy
About=20 the author
How=20 to cite item
Indexing=20 metadata
Print=20 version
Define=20 Terms
Notify colleague*
Email the author*
Add comment*