C4 - Cultural and sCientific Content in Context
The simplest way is to use bower. C4 is available in the package repository, so bower install c4 will install everything you need.
After c4 is installed, you might need to configure the paths for requirejs. This can be comfortably automated with grunt-bower-requirejs. If you choose to configure the paths manually, your configuration might look similar to this (first part of the script, in which you want to use c4 modules):
requirejs.config({
baseUrl: 'bower_components/',
paths: {
jquery: 'jquery/dist/jquery',
"jquery-ui":'jquery-ui/jquery-ui',
graph:'graph/lib/graph',
"tag-it":'tag-it/js/tag-it'
}
});Once the paths are configured, you need to include your script via requirejs as usual, for example like so:
<script data-main="myScript" src="https://github.com/EEXCESS/c4/raw/master/bower_components/requirejs/require.js"></script>where myScript is the script you want to execute and in which you use c4 modules.
APIconnector A module that simplifies requests to the EEXCESS privacy proxy. It allows to send (privacy preserved) queries, obtain details for a set of document badges and provides a cache of the last queries/result sets. paragraphDetection A module that allows to extract textual paragraphs from HTML documents (opposed to navigational menus, advertisements, etc.), construct queries in the EEXCESS query profile format and determine the currently focused paragraph.CitationBuilder A module to assemble ready-to-use citations from metadata provided as JSON. See the CitationBuilder README.md for details.searchBar A module to add a bar to the bottom of the page, which allows query interaction and displaying results.iframes A utility module for communication with iframes, which enables broadcasting messages.namedEntityRecognition A utility module for communication with the DoSer named entity recognition service.logging A module that simplifies the handling of different types of logging events. The APIconnector module provides means to communicate with the (EEXCESS) Federated Recommender via the Privacy Proxy.
A working example using the APIconnector can be found in examples/searchBar_Paragraphs
init(settings): allows to initialize the APIconnector with custom parameters. You must call this method and specify the origin attribute (see below), before you can send queries. The minimum configuration is shown in the example below. The following parameters can be customized:
base_url The basic url of the server to calltimeout The timeout in ms, after which a request to the server is canceled. Default is 10000.logTimeout The timeout in ms, after which a logging request to the server is canceled. Default is 5000.loggingLevel Flag whether queries/results should be logged on the privacy proxy. Defaults to 0 (logging enabled). If you want to disable the logging on the server you need to set the flag to 1. cacheSize The size of the query/result cache. Determines how many queries and corresponding result sets should be cached. Default is 10.suffix_recommend The endpoint for the recommender service. Default: "recommend".suffix_details The endpoint to get details for result items. Default: "getDetails".suffix_favicon The endpoint from which to retrieve the provider favicons. Default: "getPartnerFavIcon?partnerId=".suffix_log The endpoint for logging requests. Default: "log/".origin The identifier for the requesting client/user. This object must contain the attributes clientType, clientVersion and userID, see the example below.
require(['c4/APIconnector'], function(api) {
api.init({
origin:{
clientType:"some client", // the name of the client application
clientVersion:"42.23", // the version nr of the client application
userID:"E993A29B-A063-426D-896E-131F85193EB7" // UUID of the current user
}
});
});query(profile,callback): allows to query the Federated Recommender (through the Privacy Proxy). The expected parameters are a EEXCESS profile and a callback function.
require(['c4/APIconnector'], function(api) {
var profile = {
contextKeywords:[{
text:"someKeyword"
}]
};
api.query(profile, function(response) {
if(response.status === 'success') {
// do something with the result contained in response.data
} else {
// an error occured, details may be in response.data
}
});
});queryPeas: allows to query the Federated Recommender (through the Privacy Proxy) in a privacy-preserving way. It returns the exact same result as query. It uses the PEAS indistinguishability protocol. This example shows how to use it:
require(["APIconnector"], function(apiConnector){
var nbFakeQueries = 2; // The greater the better from a privacy point of view, but the worse from a performance point of view (2 or 3 are acceptable values).
var query = JSON.parse('{"origin": {"userID": "E993A29B-A063-426D-896E-131F85193EB7", "clientType": "EEXCESS - Google Chrome Extension", "clientVersion": "2beta", "module": "testing"}, "numResults": 3, "contextKeywords": [{"text": "graz","weight": 0.1}, {"text": "vienna","weight": 0.3}]');
apiConnector.queryPeas(query, nbFakeQueries, function(results){
var resultsObj = results.data;
});
});getDetails(detailsRequestObj,callback): allows to retrieve details for result items from the Federated Recommender (through the Privacy Proxy). The expected parameter is a detailsRequestObj object, that has an origin, queryID and a list of document badges of the items for which to retrieve details. A callback function can be used to return the results to.
require(['c4/APIconnector'], function(api) {
var detailsRequestObj = {
origin : {"origin": {"userID": "E993A29B-A063-426D-896E-131F85193EB7", "clientType": "EEXCESS - Google Chrome Extension", "clientVersion": "2beta", "module": "testing"},
documentBadge: [
{
id: "/09003/4A65C4999F4077781A1F9CF2510EE512CD6571B9",
uri: "http://europeana.eu/resolve/record/09003/4A65C4999F4077781A1F9CF2510EE512CD6571B9",
provider: "Europeana"
}
],
queryID: "70342716"
};
api.getDetails(detailsRequestObj, function(response) {
if(response.status === 'success') {
// do something with the result contained in response.data
} else {
// an error occured, details may be in response.data
}
});
});getCache(): allows to retrieve the cached queries/result sets.
require(['c4/APIconnector'], function(api) {
api.getCache().forEach(function(){
console.log(this.profile); // the query
console.log(this.result); // the result set
});
});getCurrent(): allows to retrieve the last successfully executed query and corresponding result set. Returns null if no successful query has been executed up to that point.
require(['c4/APIconnector'], function(api) {
var current = api.getCurrent();
console.log(current.profile); // the query
console.log(current.result); // the result set
});logInteractionType: Enum for logging interaction types. See sendLog for usage.
sendLog(interactionType, logEntry): allows to send logging requests to the server. The parameter interactionType specifies the type of the interaction to log and the parameter logEntry the entry to be logged.
require(['c4/APIconnector'], function(api) {
// the log entry normally will be created within a widget, here we define one explicitly.
// The entry we create logs the citation of a result item as an image.
var logEntry = {
origin:{
module:"example widget"
},
content:{
documentBadge:{<documentBadge of the item>}
},
queryID:<identifier of the query that provided this result item>
}
api.sendLog(api.logInteractionType.itemCitedAsImage,logEntry);
});A module to extract textual paragraphs from arbitrary webpage markup, find the paragraph currently in focus of the user and create a search query from a paragraph.
A working example using the paragraphDetection can be found in examples/searchBar_Paragraphs
init(settings):allows to initialize the paragraph detection with custom parameters. You only need to provide the parameters you want to change. Parameters that can be changed are a prefix that is used for the identifiers of newly created HTML elements and the classname that will added to those elements (atm a wrapper div with the mentioned parameters is created around the detected paragraph). The example uses the default values, if you are fine with these, you do not need to call the init method.
require(['c4/paragraphDetection'], function(paragraphDetection) {
paragraphDetection.init({
prefix:"eexcess", // default value
classname:"eexcess_detected_par" // default value
});
});getParagraphs([root]): allows to detect text paragraphs in arbitrary HTML markup. The detection heuristic tries to extract 'real' paragraphs, opposed to navigation menus, advertisements, etc. The root parameter (optional) specifies the root HTML-element from where to start the extraction. If it is not given, the detection will use document as root.
Returns an array of the detected paragraphs with the entries in the following format:
{
id: "<prefix>_par_0", // identifier, the prefix can be customized via the init method
elements:[], // the HTML-elements spanning the paragrah
multi:false, // indicator, whether the paragraph consists of e.g. a singe <p> element or several <p> siblings
content:"Lorem ipsum dolor", // the textual content of the paragraph
headline:"Sit Amet" // textual content of the corresponding headline of the paragraph
}Usage:
require(['c4/paragraphDetection'], function(paragraphDetection) {
var paragraphs = paragraphDetection.getParagraphs();
paragrahps.forEach(function(entry){
console.log(entry); // do something with each paragraph
});
});paragraphToQuery(text,callback,[id],[headline]): creates a query from the given text in the EEXCESS profile format. Only the attribute contextKeywords will be set. The parameters to be set are:
require(['c4/paragraphDetection'], function(paragraphDetection) {
var text = 'Lorem ipsum dolor sit amet...';
paragraphDetection.paragraphToQuery(text, function(response){
if(typeof response.query !== 'undefined') {
// query has sucessfully been constructed
console.log(response.query);
} else {
// something went wrong
console.log(response.error);
}
});
});findFocusedParagraphSimple([paragraphs]): tries to determine the paragraph, the user is currently looking at.
In this simple version, the topmost left paragraph is accounted as being read, except for the user explicitly clicking on a paragraph. When a change of the focused paragraph occurs, a paragraphFocused event is dispatched with the focused paragraph attached. The set of paragraphs to observe can be specified via the optional paragraphs parameter. If this parameter is not set, the method will observe paragraphs already detected by the module (if any - e.g. from a previous getParagraphs call). The paragraphFocused event may be dispatched several times for the same paragraph.
require(['jquery','c4/paragraphDetection'], function($,paragraphDetection) {
// detect paragraphs in the document
paragraphDetection.getParagraphs();
// listen for paragraphFoucsed events
$(document).on('paragraphFocused', function(e){
console.log(evt.originalEvent.detail); // the focused paragraph
});
// set up tracking of focused paragraph
paragraphDetection.findFocusedParagraphSimple();
});findFocusedParagraph([paragraphs]): tries to determine the paragraph, the user is currently looking at.
This method is in principle identical to findFocusedParagraphSimple, but accounts for more implicit user interaction. The probability of a focused paragraph is calculated by a weighted combination of its size, position and distance to the mouse position. When mouse movements occur, the distance to the mouse position has a higher weight, while scrolling events render the paragraph position more important.
require(['jquery','c4/paragraphDetection'], function($,paragraphDetection) {
// detect paragraphs in the document
paragraphDetection.getParagraphs();
// listen for paragraphFoucsed events
$(document).on('paragraphFocused', function(e){
console.log(evt.originalEvent.detail); // the focused paragraph
});
// set up tracking of focused paragraph
paragraphDetection.findFocusedParagraphSimple();
});Please see the README.md of the CitationBuilder module for details.
A module that adds a search bar to the bottom of the page, which enables to show and modify the query and display the results.
A working example using the searchBar can be found in examples/searchBar_Paragraphs
init(tabs[,config]): initializes the search bar with a set of visualization widgets (parameter tabs) and custom configuration options (optional parameter config).
The tabs parameter specifies the visualization widgets to use for displaying the result in the following format:
[{
name:"widget name" // name of the widget, will be displayed in the tab navigation for selection of the widget
url:"<path>" // path to the main page of the widget
icon:"<path>" // path to an icon image for the widget (optional)
},{
name:"widget2",
url:"<path2>"
},{
// ...
}
]The config object allows to customize the following parameters (you only need to specify the ones you would like to change):
queryFn - a custom function to query a server for results. The function must look like function(profile,function(response){
console.log(response.status); // should inform about the status, either 'success' or 'error'
console.log(response.data); // should contain the results on success and error details on error
});where the profile parameter represents an EEXCESS query profile. By default, the query method of the APIconnector module is used.
imgPATH - path where images are stored. Defaults to 'img/'queryModificationDelay - the delay before a query is executed (in ms) after the user interacted with it (added/removed keywords, changed main topic, etc). Defaults to 500.queryDelay - the delay (in ms) before a query is executed due to changes from the parent container. This delay is used after the query has been changed through the setQuery method of this module. Defaults to 2000.setQuery function, in order to enable different delays for specific interactions.storage - an object providing storage capabilities. By default, the search bar will use the browser's local storage to store values. The storage function must exhibit two functions:set(item, callback) The item passed to this function is an object containing key value pairs to store. It looks like this:
{
key1:"value1", // value can be a simple type like String
key2:{
// value can also be an JSON-serialiazable objects
}
}The callback parameter is a callback function without parameters to be executed after storing the item.
get(key, callback) The key parameter is either a single String (to get a single value) or an Array of Strings (to get several values).
The callback function should be called with an object, containing the provided key(s) and their corresponding values like so:
var response = {
key1: value1,
key2: value2
}
callback(response);setQuery(contextKeywords [,delay]): sets the query in the search bar.
The contextKeywors must be in the format as the contextKeywords in the EEXCESS query profile format.
The query will automatically be executed after the delay given by the settings (default: 2000ms, can be customized via searchBar.init(<tabs>,{queryDelay:<custom value>}). Alternatively, this setting can be overwritten by providing the optional delay parameter, which specifies the delay in ms.
require(['jquery','c4/searchBar'], function($,searchBar) {
// searchBar needs to be initialized first, omitted here
var contextKeywords = [{
text:"Lorem"
},{
text:"ipsum"
}];
searchBar.setQuery(contextKeywords, 0); // query is set and will be immediately executed (delay: 0ms)
});A utility module for communicating between iframes
sendMsgAll(message): send a message to all iframes embedded in the current window. The expected parameter is the message to send. The example below shows how to inform all included widgets that a new query has been issued.
require(['c4/iframes'], function(iframes) {
var profile = {
contextKeywords:[{
text:'someKeyword'
}];
};
iframes.sendMsgAll({
event:'eexces.newQueryTriggered',
data:profile
});
});A utility module to query the EEXCESS recognition and disambiguation service
entitiesAndCategories(paragraphs,callback): allows to extract Wikipedia entities and associated categories from a given piece of text. In addition, the main topic of the text and time mentions are extracted. The expected parameters are a set of paragraphs and a callback function.
require(['c4/namedEntityRecognition'], function(ner) {
var paragraph = {
id:42,
headline:"I am a headline",
content:"Lorem ipsum dolor..."
};
ner.entitiesAndCategories({paragraphs:[paragraph]}, function(response){
if(response.status === 'success') {
// the results are contained in response.data.paragraphs
response.data.paragraphs.forEach(function(){
console.log(this.time); // contains time mentions and associated entities/categories
console.log(this.topic); // contains the main topic entity
console.log(this.statistic); // contains the extracted entities/categories
this.statistic.forEach(function(){
console.log(this.key.text); // label of the entity
console.log(this.key.categories); // associated categories
console.log(this.key.type); // type of the entity (person, location, organization, misc)
console.log(this.value); // number of occurences of the entity in the paragraph
});
});
} else {
// an error occured, details may be in response.data
}
});
});A module that provides an API for generating logging events in the format specified by Logging Format. Logging-Events are passed over to the APIconnector which sends it to the logging endpoints of the Privacy Proxy. A working example on how the logging is to be used, can be found in examples/loggingExample.
The logging-API provides methods to create logging events in the correct format and it broadcasts these events as messages via the browser's Messaging-API. Thus, the client application needs to listen to the following messages and forward them to the Privacy Proxy:
require(['c4/APIconnector'], function(api) {
api.init({origin: {
clientType: "EEXCESS Chrome extension",
clientVersion: "2.0.1"
userID: "93939A-8494BE-99ADF2"
}});
window.onmessage = function(msg) {
if (msg.data.event) {
switch (msg.data.event) {
case 'eexcess.log.moduleOpened':
api.sendLog(api.logInteractionType.moduleOpened, msg.data.data);
break;
case 'eexcess.log.moduleClosed':
api.sendLog(api.logInteractionType.moduleClosed, msg.data.data);
break;
case 'eexcess.log.moduleStatisticsCollected':
api.sendLog(api.logInteractionType.moduleStatisticsCollected, msg.data.data);
break;
case 'eexcess.log.itemOpened':
api.sendLog(api.logInteractionType.itemOpened, msg.data.data);
break;
case 'eexcess.log.itemClosed':
api.sendLog(api.logInteractionType.itemClosed, msg.data.data);
break;
case 'eexcess.log.itemCitedAsImage':
api.sendLog(api.logInteractionType.itemCitedAsImage, msg.data.data);
break;
case 'eexcess.log.itemCitedAsText':
api.sendLog(api.logInteractionType.itemCitedAsText, msg.data.data);
break;
case 'eexcess.log.itemCitedAsHyperlink':
api.sendLog(api.logInteractionType.itemCitedAsHyperlink, msg.data.data);
break;
case 'eexcess.log.itemRated':
api.sendLog(api.logInteractionType.itemRated, msg.data.data);
break;
default:
break;
}
}
}
});The methods of the logging-API are as follows:
init(config): allows to initialize the logging-API with custom parameters. You must call this method and specify the origin attribute (see below), before you can call methods of the logging-API. The following parameters can be customized:
origin The identifier for the requesting component. This object must contain a module attribute, that specifies the name of the issuing component, see the example below.require(['c4/logging'], function(logging) {
logging.init({
origin:{
module: "Dashboard Visualization"
}
});
});The logging-API provides the following methods to create corresponding logging events:
moduleOpened(moduleName): Create the logging event moduleOpened. The expected parameter is the name of the component that has been opened.moduleClosed(moduleName): Create the logging event moduleClosed. The expected parameter is the name of the component that has been closed.moduleStatisticsCollected(statistics): Create the logging event moduleStatisticsCollected. The expected parameter can be of any type. statistics is logged as-is.itemOpened(documentBadge, queryID): Create the logging event itemOpened. The expected parameters are a documentBadge, which refers to the resource that was opened in detailed view, and a queryID, which refers to the query that returned the resource.itemClosed(documentBadge, queryID, duration): Create the logging event itemClosed. The expected parameters are a documentBadge, which refers to the resource that was closed in detailed view, a queryID, which refers to the query that returned the resource, and a duration. The latter specifies the time in milliseconds, during which the item was opened in detailed view.itemCitedAsImage(documentBadge, queryID): Create the logging event itemCitedAsImage. The expected parameters are a documentBadge, which refers to the resource that was cited as an image, and a queryID, which refers to the query that returned the resource.itemCitedAsText(documentBadge, queryID): Create the logging event itemCitedAsText. The expected parameters are a documentBadge, which refers to the resource that was cited as text, and a queryID, which refers to the query that returned the resource.itemCitedAsHyperlink(documentBadge, queryID): Create the logging event itemCitedAsHyperlink. The expected parameters are a documentBadge, which refers to the resource that was cited as a hyperlink, and a queryID, which refers to the query that returned the resource.itemRated(documentBadge, queryID, minRating, maxRating, rating): Create the logging event itemRated. The expected parameters are a documentBadge, which refers to the resource that was rated and a queryID, which referst to the query that returned the rated resource. minRating and maxRating allow to specifiy the range a rating can have. rating is the actual value that has been assigned to the resource.The following examples demonstrate the usage of these methods:
require(['c4/logging'], function(logging) {
logging.init({
origin:{
module: "Dashboard Visualization"
}
});
var queryID = "483904939"
var documentBadge = {
id: "995eb36f-151d-356c-b00c-4ef419bc2124",
uri: "http://www.mendeley.com/research/hellenism-homoeroticism-shelley-circle",
provider: "Mendeley"
};
logging.moduleOpened("anotherVisualizationName");
logging.moduleClosed("anotherVisualizationName", 5000);
logging.moduleStatisticsCollected({usageStatistics: 42});
logging.itemOpened(documentBadge, queryID);
logging.itemClosed(documentBadge, queryID, 1500);
logging.itemCitedAsImage(documentBadge, queryID);
logging.itemCitedAsText(documentBadge, queryID);
logging.itemCitedAsHyperlink(documentBadge, queryID);
logging.itemRated(documentBadge, queryID, 0, 4, 3);
});