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Edmundo Tovar, Nelson Piedra, Jorge López, Janeth Chicaiza Bali Indonesia May 8-10, 2013 Serendipity a Faceted Search engine for OpenCourseWare Content.

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Presentation on theme: "Edmundo Tovar, Nelson Piedra, Jorge López, Janeth Chicaiza Bali Indonesia May 8-10, 2013 Serendipity a Faceted Search engine for OpenCourseWare Content."— Presentation transcript:

1 Edmundo Tovar, Nelson Piedra, Jorge López, Janeth Chicaiza Bali Indonesia May 8-10, 2013 Serendipity a Faceted Search engine for OpenCourseWare Content @nopiedra #ocwcglobal #OCW #OER #Serendipity #UTPL

2 The main purpose of the service developed is to provide students, teachers and self-learners with an faceted search engine that allow them to find and discover open educational resources related to OCW from OpenCourseWareConsortium and OCW-Universia. Purpose of Serendipity

3 Faceted search, also called faceted navigation, is a technique for accessing content organized according to a faceted classification system, allowing users to explore a collection of information by applying dynamic and multiple filters. With the benefit of search results diversification, no need for a priori knowledge, and never leading to zero result, it can significantly reduce information overload. About Faceted Exploration

4 Facets refer to categories used to characterize information items in a collection. A faceted classification system classifies each information element along multiple explicit dimensions, enabling the classifications to be accessed and ordered in multiple ways rather than in a single, pre-determined, and taxonomic order. Facets and taxonomic order

5 Faceted exploration is a proven technique for supporting flexible exploration and discovery through the information space. The user can refine queries based on facets such as size, language, knowledge-domain, geographic localization and neighbourhood characteristics. The facets are extracted by applying a parser specialized for parsing classified content. Refine queries based on facets

6 Serendipity is for people Serendipity is an faceted search engine based on Semantic Web Technologies. Open Linked Data from Open Educational Content. Current version of Serendipity is based on Flamenco.

7 Serendipity is an faceted search engine based on Semantic Web Technologies. Serendipity is based on Flamenco. The main objectives of faceted navigation are to support flexible navigation through the information space: refining and expanding, provide suggestions of exploration choices at each point in the search process, prevent empty result sets, and provide a sense of control and reduce confusion in the use. About Serendipity

8 Serendipity use Linked Data Design Issues to retrieve information that is semantically described and related to open educational resources (OER) that are accessible via Internet. Linked data have the potential of create bridges between OER data silos.

9 The collection under study consisted of approximately 8000 OpenCourseWare in the collection of the OCW- Dataset of LOCWD Project. This collection contained standard OER metadata facets, including creators names, language, licenses of OCW, repositories, tags, knowledge areas, universities, countries and dates. Collection Preparation

10 The data extracted by Serendipity are being validated through the sponsorship and collaboration of OpenCourseWare Consortium. Sponsorship from OCWC

11 Faceted Queries i. Faceted Query of OCW based on Linked OpenCourseWare data CASE: FIND, OpenCourseWare about “Web”

12 http://serendipity.utpl.edu.ec Serendipity is an OCW faceted search engine based on Semantic Web Technologies.

13 Guided navigation Previews of Results Refine search Add keywords With Serendipity Explore OCW in an integrated and incremental manner, from any of the repositories of institutions that publish OpenCourseWare.

14 The user, when presented with the facets, is likely to discover new facets of the query that they were not aware of before. When clicking on a facet, they will narrow down their search by expanding the original query with the suggested facet. Discover new facets by expanding the original query Discover new facets by expanding the original query

15 Facets Share this OCW Inspect current OCW Refine your search Access the full description of the courses as published by the home institution, along with complimentary information such as language, license, author, country, geographic location of the institution and other semantically related information available via the Web. Propose change

16 Inspect the result from OCW original site Get more accurate and complete results, since it locates OCWs using different metadatas and data elements, providing the user with visible options that help clarify and refine the queries.

17 Link current OCW to Other LinkedData Source

18 Points of Interest ii. Map to visualize OER Points of Interest

19 As an important feature of Serendipity, Serendipity POIs (Points of Interest), allows users visualize data of OCW/OER/MOOC/OEP/Projects/Repositories from an dataset based on Linked Data technologies. About Serendipity POIs

20 Serendipity POIs use icons to represent different categories of POI on a map graphically. A point of interest, or POI, is a OER specific point location that someone may find useful or interesting.

21 A point of interest specifies, at minimum, the latitude and longitude of the POI, assuming a certain map datum (extrated from serendipity datasource). A name or description for the POI is usually included, and other information such as description, number of resources, contact information, language, license or a link to dbpedia/freebase may also be attached.

22 An example is a point on the Earth representing the location of the Massachusetts Institute of Technology, or a point on Spain representing the location of an OCW University.

23 Other example is a point on the Earth representing the location of the University of Cape Town

24 Serendipity use the term POIs when referring to Open Repositories of OCW/OER/OEP/Projects, Open Data for educational content, MOOCs or any other categories used in open educational systems.

25 Open Data iii. Open Data from Open Educational Content

26 Serendipity POIs seeks to become a repository for the information about OER that the Serendipity Multiagent Environment collects. Therefore, the site would publish to the public any data collected that is not private or restricted. Collecting and downloading OER Data

27 Serendipity Open Data is the idea that certain data should be freely available to everyone to use and republish as they wish, without restrictions from copyright, or other mechanisms of control.

28 Why publish Linked OER Data? Because LinkedData holds the potential to move our OER collections out of their silos Open the data and content silos, to leverage the knowledge capital represented by our OER repositories To enrich our information landscape, to improve visibility To improve ease of discovery open academic resources To improve ease of consumption and reuse of OCW To reduce redundancy in searched of OER Promoting innovation and Added Value to Open Educational Content

29 Points of Interest iv. Suggest new Points of Information

30 The purpose of Serendipity POIs - Open data is to increase public access to high value, machine readable datasets generated by volunteers and data extracted from Serendipity multiagent environment.

31 Data Visualizatio ns v. Data visualization

32 Why OER DataViz? Serendipity POIs - Open data contains valuable information that will drive insights, innovations, and discoveries, but it can be difficult to access and digest. Using data visualization, we’re simplify the complexity and drive a deeper understanding of the open educational context.

33 The main goal of data visualization is its ability to visualize OER data, communicating information clearly and effectivelty.

34 Data Visualization 1. It shows information of Universities classified hierarchically, taken starting point to continents, then countries, cities and universities

35 Data Visualization 2: Tree structures to show another way to visualize the information the universities members of OCW initiatives.

36 Data Visualization 3: Search courses by tag and use geographic information to show courses of universities and social network analysis (SNA) to form networks of collaboration and recommend related tags

37 @nopiedra #ocwcglobal #OCW #OER #LOCWD #LinkedData #UTPL Thank s! @nopiedra, @etc91


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