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LinkedUp - Linked Data & Education

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LinkedUp - Linked Data & Education

  1. 1. Stefan Dietze 06/11/12 1
  2. 2. Motivation Data on the Web Some eyecatching opener illustrating growth and or diversity of web data LinkedUp: Linking Web Data for Education Project – Open Challenge in Web-scale Data Integration Stefan Dietze (L3S Research Center, DE) Stefan Dietze 06/11/12 2
  3. 3. Web-scale exploration of (educational) resources and data ? RecSys (Linked) Web Data TEL
  4. 4. TEL data vs Linked Open Data TEL data on the Web  Open Educational Resource (OER) metadata & MOOC collections (e.g. OpenCourseware, OpenLearn, Merlot, Coursera)  Competing Web interfaces (e.g. OAI-PMH, SOAP, REST)  Competing metadata standards (e.g. IEEE LOM, ADL SCORM, DC…) & taxonomies & exchange formats (JSON, RDF, XML)  Issues: heterogeneity & lack of interoperability Stefan Dietze 06/11/12 4
  5. 5. TEL data vs Linked Open Data TEL data on the Web Linked Open Data  Open Educational Resource (OER) metadata & MOOC  Vision: well connected graph of open Web data collections (e.g. OpenCourseware, OpenLearn, Merlot, Coursera)  W3C standards (RDF, SPARQL) to expose data, URIs to interlink datasets  Competing Web interfaces (e.g. OAI-PMH, SOAP, REST)  => vast cloud of interconnected datasets  Competing metadata standards (e.g. IEEE LOM, ADL SCORM, DC…) & taxonomies & exchange formats (JSON,  Crossing all sorts of domains RDF, XML)  32 billion triples (September 2011)  Issues: heterogeneity & lack of interoperability Stefan Dietze 06/11/12 5
  6. 6. TEL data vs Linked Open Data Linked Data for Education Linked Open Data Relevant knowledge and data  Vision: well connected graph of open Web data  Publications: ACM, PubMed, DBLP (L3S), OpenLibrary  W3C standards (RDF, SPARQL) to expose data, URIs  (Cross-)domain knowledge & resources: Bioportal for Life to interlink datasets Sciences, historic artefacts in Europeana, Geonames,  => vast cloud of interconnected datasets DBpedia, Freebase, …  Crossing all sorts of domains  Media resource metadata: BBC, Flickr, …  32 billion triples (September 2011) Explicit educational data  University Linked Data: eg The Open University UK, http://data.open.ac.uk, Southampton University, …  OER Linked Data: mEducator Linked ER ( http://ckan.net/package/meducator), Open Learn LD  Schemas: Learning Resource Metadata Initiative (LRMI, http://www.lrmi.net/), mEducator OER schema ( http://purl.org/meducator/ns) => http://linkededucation.org; http://linkeduniversities.org Stefan Dietze 06/11/12 6
  7. 7. Slow take-up => crucial challenges: Scalability, performance & robustness (in large-scale data environments) Licensing & legal issues Web data quality and consistency Benchmarking & evaluation … RecSys (Linked) Web Data TEL
  8. 8. LinkedUp in a nutshell Challenge and evaluation framework aimed at: LinkedUp  Leap in robustness/scalability of (Big) data integration technologies Web data submissi on data (data analytics, mining, storage, analysis)  Real-world use case: Web-based education facilitated by open Web data Personal data What? Stage 1- Initialisation Initialisation When? 3 stages of the LinkedUp competition LinkedUp Challenge Environment How? • Lowest requirements level for participation • LinkedUp Evaluation Framework • Inital prototypes and mockups, use of data … n o i t a p i c i t r a P testbed required • Methods and Test Cases Stage 2 • 10 to 20 projects are expected • LinkedUp Data Testbed • Competitor ranking list • Medium requirements level for participation …provides: • Working prototypes, minimum amount of LinkedUp Support Actions  Legal & technical data sources, clear target user group Stage 3 • 5 to 10 projects are expected • Dissemination (events, training) guidance a i r e t i r c • Data sharing initiatives  Data & use cases • Deployment in real-world use cases • Community building & clustering • Sustainable technologies, reaching out • Technology transfer  Evaluation to critical amount of users, Stage 4 • 3 to 5 projects are expected • Cashprice awards & consulting results ! 2 years !  Financial awards E P S P F  … Network of supporting organisations T I (see 3.2 Spreading excellence, exploiting results, disseminating knowledge) S E C B C O Stefan Dietze 06/11/12 8
  9. 9. LinkedUp consortium (Scientific) expertise in three strategic areas  Data integration, Web technologies & evaluation  Educational technologies, (meta)data and resources  Dissemination and exploitation of open Web data Stefan Dietze 25/05/12 9
  10. 10. LinkedUp consortium (Scientific) expertise in three strategic areas L3S Research Center, Leibniz University, DE Elsevier, NL  Leading institute in Web science &  Leading scientific & educational publisher data technologies as well as  Innovative research on the future of publishing & technology-enhanced learning extensive experience in data competitions  Strong experience in coordinating EC R&D CELSTEC, The Open University, NL projects  R&D institute in educational technologies and part of the largest distance university in the netherlands The Open Knowledge Foundation, UK  Not-for profit organisation to promote open knowledge and data; global network  Host of key events (OKCon) and platforms (eg CKAN) KMI, The Open University, UK  Leading R&D institute in areas related to LinkedUp  World’s largest distance university (over 200.000 students) Exact Learning Solutions, IT  SME in educational technologies and services with long-standing experience in (EC-funded) R&D projects
  11. 11. LinkedUp network/associated partners Persistent “LinkedUp Network”(community of industrial and academic institutions) Commonwealth of Learning, COL (CA) Athabasca University (CA) International Talis Group (UK) (outside Europe) SURF NL (NL) Université Fribourg, eXascale Infolab Group (CH) Democritus University of Thrace (GR) AKSW, Universität Leipzig (DE) Aristotele University of Thessaloniki (GR) CNR Institute for Educational Technologies (IT) Clam Messina Service and Research Centre (IT) Eurix (IT) Ontology Engineering Group (OEG), UPM, (ESP) 11 18/09/12 Stefan Dietze
  12. 12. Advisory Board Dan Brickley  Google, UK & W3C  Schema.org / Learning Resource Metadata Initiative  FOAF project Sören Auer Venkataraman Balaji  Agile Knowledge Engi-  Director, Technology & neering and Semantic Knowledge Management Web (AKSW) group leader, University  Commonwealth of Learning – of Leipzig http://col.org  DBpedia, Coordinator of LOD2 project Philippe Cudré-Mauroux  Head of eXascale Infolab  University of Fribourg, Switzerland Stefan Dietze 06/11/12 12
  13. 13. Previous collaborations R&D projects & events/initiatives R&D Projects Events & Initiatives EC IP OKKAM: Web entity LILE: Linked Learning (Linked Data for identification & discovery Education) workshop series EC BPN mEducator: Integration of educational LALD: Learning Analytics and Linked resources based on LOD Data workshop (series) EC STREP LUISA: Semantic LinkedEducation Web technologies for http://linkededucation.org sharing of OER EC NoE STELLAR: LinkedUniversities educational Web http://linkeduniversities.org technologies network Joint special issues related to LinkedUp OpenScout: promotion of (Semantic Web Journal and ILE) use of open educational content European Association for Technology- enhanced Learning (EATEL) Stefan Dietze 06/11/12 13
  14. 14. Other related initiatives from LinkedUp partners Large-scale challenges & competitions Web data dissemination and events  Open Data Challenge  The Open Knowledge Conference (OKCon): (http://opendatachallenge.org/): Europe‘s annual open knowledge conference run by largest open data competition, 430 OKFN submissions from 24 member states  DataTEL theme team: gathering of open  Elsevier Grand Challenge data within education (OUNL) (http://www.elseviergrandchallenge.com):  Open Government Data Camp: communication of scientific information. http://ogdcamp.org/  Semantic Web Challenge  Open Data Handboook (http://challenge.semanticweb.org/) large- http://opendatahandbook.org/: living online scale Semantic Web data applications manual for basic concepts of ‘open data’  Semantic Web Service Challenge  Topical working groups and hackdays, eg (http://sws-challenge.org) : evaluation of http://okfn.org/wg/ semantic web service technologies Data catalogues & (educational) datasets  CKAN: The Data Hub, the most important registry of open knowledge datasets (hosted and managed by OKFN).  LUCERO, http://data.open.ac.uk: first extensive Linked Data university dataset, approach adopted by many universities  mEducator Linked Educational resources: one of first OER datasets in Linked Data cloud (LUH, OUUK) Stefan Dietze 06/11/12 14
  15. 15. ?
  16. 16. Goals Objective 1 Open Web Data Success Stories evaluate create support demonstrate create support support demonstrate Educational Web data & technologies Objective 2 support Objective 3 Evaluation evaluate create Technology Framework for demonstrate / support Transfer in the Open Web Education Data Sector Applications evaluate Stefan Dietze 06/11/12 16
  17. 17. Goals & tangible outcomes Web data LinkedUp submissi on data Personal data Stage 1- Initialisation Initialisation  Competition framework & community 3 stages of the LinkedUp competition LinkedUp Challenge Environment • Lowest requirements level for participation • LinkedUp Evaluation Framework  Evaluation framework for large-scale • Inital prototypes and mockups, use of data n o p c i t r a P testbed required • Methods and Test Cases Stage 2 • LinkedUp Data Testbed Web data applications and data • 10 to 20 projects are expected • Competitor ranking list Objective 1• Medium requirements level for participation (metrics, methods, benchmarks) Open Web • Working prototypes, minimumgroup of data sources, clear target user amount LinkedUp Support Actions Stage 3 • 5 to 10 projects are expected  Large-scale data testbed of quality- Data Success • Dissemination (events, training) a e t i r c • Data sharing initiatives Stories • Deployment in real-world use cases assessed datasets • Sustainable technologies, reaching out • Community building & clustering • Technology transfer to critical amount of users, Stage 4 • 3 to 5 projects are expected • Cashprice awards & consulting evaluate create P S E T P F Network of supporting organisations I support (see 3.2 Spreading excellence, exploiting results, disseminating knowledge) S B E demonstrate create support C O C support demonstrate Periodic/continuous challenge Educational Web data & technologies Objective 2 support Objective 3 Evaluation evaluate create Technology Framework for demonstrate / support Transfer in the Open Web Education Data Sector Applications evaluate Stefan Dietze 06/11/12 17
  18. 18. Goals & tangible outcomes Challenge & evaluation framework (WP1, WP2) LinkedUp in a nutshell Stefan Dietze 06/11/12 18
  19. 19. Goals & tangible outcomes Data curation & “testbed” (WP3): initial ideas Educational data gathering - community-approach: Linked Education cloud  “LinkedUp/Linked Education cloud” as subset of LOD cloud  CKAN – “The DataHub” (ckan.net) for data collection (analogous to LOD approach)  Dedicated group (“linked-education”) for cataloging educational datasets Educational Data Educational data integration & infrastructure: Linked Education graph  Linked Education cloud => Linked Education graph  Integration of (selected) datasets into coherent (RDF) dataset  Infrastructure and unified (SPARQL) endpoint for LinkedUp challenge Stefan Dietze 06/11/12 19
  20. 20. Goals & tangible outcomes LinkedUp in a nutshell  Highly innovative, evaluated applications of large-scale Web data  “LinkedUp Challenge” offers incentive and support to steer submissions Objective 1 Open Web  Educational scenario: (a) challenging vision Data Success and (b) real-world scenario and Stories requirements evaluate create support demonstrate create support support demonstrate Educational Web data & technologies Objective 2 support Objective 3 Evaluation evaluate create Technology Framework for demonstrate / support Transfer in the Open Web Education Data Sector Applications evaluate Stefan Dietze 06/11/12 20
  21. 21. Goals & tangible outcomes Success stories: in both research & practice Technical achievements & progress in, e.g. End-user applications facilitated by Open Data & resources  Information Retrieval tasks (performance, scalability)  Tutoring systems (course/resource development) &  Data integration (eg schema mapping, data interlinking, educational resource sharing and discovery solutions entity co-reference resolution)  Certificate-level Web education offerings Characteristics  Specific & constrained challenge tasks & datasets Characteristics  Evaluation with traditional quantitative measures  Open & less constrained challenge tasks (eg use cases) and (precision, recall, response times, … ) data  Impact primarily scientific (at least in short-term)  Evaluation via qualitative and quantitative criteria  Impact on academia, industry, society Stefan Dietze 06/11/12 21
  22. 22. Goals & tangible outcomes in a nutshell  Technology transfer, increase in collaboration and awareness (best practices, clusters/communities, Objective 1 events) Open Web  Transfer of innovative R&D results Data Success Stories  Increase in awareness about open Web data and scalable data integration evaluate create methods support demonstrate create support support demonstrate Educational Web data & technologies Objective 2 support Objective 3 Evaluation evaluate create Technology Framework for demonstrate / support Transfer in the Open Web Education Data Sector Applications evaluate Stefan Dietze 06/11/12 22
  23. 23. Exploitation, dissemination, sustainability Dissemination events & platforms Clustering  Joint clustering activities with Viral dissemination channels  Showcases & tutorials collocated with relevant conferences related organisations (“LinkedUp  Sharing of publications via Mendeley, (WWW, ISWC, ESWC, ICDE, LAK etc) Network”) … Research Gate, CiteULike,  System demonstrations  …and EC-funded R&D projects, Academia.edu  Topical hackdays such as  Advertisement of slides, showcases  LILE, LALD, DataTEL workshop series  LOD2 and demo videos on Slideshare,  ARCOMEM Youtube, Videolectures.net, Vimeo (established, persistent and growing communities)  SEALS, etc.  Social network channels such as  Open Knowledge Conference OKCON Twitter, LinkedIn  LinkedEducation.org,  Source code sharing via Source Forge LinkedUniversities.org  Use of open licensing schemes (CC) Standardisation  Participation/support of standardisation of schemas and technologies through working groups (eg W3C or http://okfn.org/wg/)  Data catalogues (eg CKAN) and community data portals (eg http://bibsoup.net/)  Standardisation initiatives and working groups (eg Creative Commons LRMI) Stefan Dietze 06/11/12 23
  24. 24. Thank you! http://purl.org/dietze / dietze@l3s.de http://linkededucation.org http://linkedup-project.eu Stefan Dietze 06/11/12 24

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