Here are the steps I would recommend to build an application using the UK HESA/UNISTAT Key Information Set as linked open data:1. Contact HESA to discuss publishing the data as linked open data using common vocabularies like the ones discussed earlier (LRMI, BIBO, etc.). This will make the data interoperable. 2. HESA transforms the data into RDF and sets up a SPARQL endpoint to query the data. 3. Build a simple web interface that allows users to search or browse courses by subject area. Include basic course details on results.4. Allow filtering results by criteria like employment rate, degree class, satisfaction levels, etc. retrieved
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This document discusses using linked data technologies to connect open educational data. It begins with an overview of the current state of open data in education, including open educational resources from universities, repositories, and publishers. It then discusses the need for common vocabularies to facilitate linking this data. The document presents several examples of representing educational data as linked open data, including the AIISO, BIBO, and LRMI ontologies as well as a case study on the Bologna Ontology. It concludes by discussing potential applications of open linked educational data like social resource discovery and research exploration.
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Similar to Here are the steps I would recommend to build an application using the UK HESA/UNISTAT Key Information Set as linked open data:1. Contact HESA to discuss publishing the data as linked open data using common vocabularies like the ones discussed earlier (LRMI, BIBO, etc.). This will make the data interoperable. 2. HESA transforms the data into RDF and sets up a SPARQL endpoint to query the data. 3. Build a simple web interface that allows users to search or browse courses by subject area. Include basic course details on results.4. Allow filtering results by criteria like employment rate, degree class, satisfaction levels, etc. retrieved
Similar to Here are the steps I would recommend to build an application using the UK HESA/UNISTAT Key Information Set as linked open data:1. Contact HESA to discuss publishing the data as linked open data using common vocabularies like the ones discussed earlier (LRMI, BIBO, etc.). This will make the data interoperable. 2. HESA transforms the data into RDF and sets up a SPARQL endpoint to query the data. 3. Build a simple web interface that allows users to search or browse courses by subject area. Include basic course details on results.4. Allow filtering results by criteria like employment rate, degree class, satisfaction levels, etc. retrieved (20)
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Here are the steps I would recommend to build an application using the UK HESA/UNISTAT Key Information Set as linked open data:1. Contact HESA to discuss publishing the data as linked open data using common vocabularies like the ones discussed earlier (LRMI, BIBO, etc.). This will make the data interoperable. 2. HESA transforms the data into RDF and sets up a SPARQL endpoint to query the data. 3. Build a simple web interface that allows users to search or browse courses by subject area. Include basic course details on results.4. Allow filtering results by criteria like employment rate, degree class, satisfaction levels, etc. retrieved
- 1. Open Web Data for Education Linked Data technologies for connecting open educational data Mathieu d’Aquin, Philippe Cudre- Mauroux, Besnik Fetahu, Marieke Guy The Open University, University of Fribourg, L3S Hanover, Open Knowledge Foundation @mdaquin @FetahuBesnik @mariekeguy Slides at: http://slideshare.net/mdaquin
- 2. The way it used to be… (Excessively simplifying) Secondary School Primary School Higher Education
- 3. coursera eX d Now… (Still simplifying, I guess) UDACITY MIT OCW MOOCs and OER OpenLearn Primary School Secondary School Other institutions through online courses Open Universities Higher Education
- 4. “I want to be a photographer, what should I do?” Siri, I want to become a professional photographer. What should I do? I found this Open University course (T189), that you can enrolled to in the regional centre 2 miles from here (cost £427). “OK, anything free I can try first?” There is an Introduction to Photography course on MIT OCW, and a Computational Photography course on coursera starting soon.
- 5. Needs data from everybody, contributed to one common data space (… linked data maybe?) eX d learning outcomes assessment UDACITY MIT courses results topics locations courses requirements OCW topics OpenLearn coursera results locations learning topics outcomes courses results topics requirements learning outcomes
- 6. Outline of the talk(s)/tutorial 1- The state of open/linked data in education II- How to contribute to open/linked data in education III- Case study - The Bowlogna Ontology IV- Making things with open/linked data in education V- Open Education – more than just open data
- 7. State of open data in education Historically, mostly open educational resources, i.e., these guys Repositories Universities But more and more of them and them now! Government bodies Publishers Thesaurus, vocabularies, etc. And hopefully, very soon, them? Loosely based on http://data.linkededucation.org/linkedup/catalog/
- 8. LinkedUp Catalogue of Web Data for Education http://data.linkededucation.org/linkedup/catalog/
- 11. Pause What are we missing?
- 12. How to contribute In other words: How to represent data in education for sharing Examples of sharing linked open data in education
- 13. Bias: We like Open and Linked Data Person: Mathieu Open University Website author Publication: Pub1 workFor Open University VLE offers M366 Course page KMi Website Mathieu’s Homepage Course: M366 Organisation: The Open University availableIn setBook Mathieu’s List of Publications Mathieu’s Twitter Country: Belgium Book: Mechatronics The Web The Web of Linked Data
- 14. Need for common vocabularies AIISO Media Ontology Geo Ontology SIOC FOAF Dublin Core LRMI DOAP BIBO TEACH DataCube SKOS VIVO
- 15. From LinkedUp data catalogue 17/11/13 LinkedUp – Author Name 15
- 17. Example: BIBO bibo:partOf bibo:Document bibo:DocumentPar t rdfs:subClassOf rdfs:subClassOf bibo:Book bibo:Article rdfs:subClassOf All bibo:partOf rdfs:subClassOf rdfs:subClassOf bibo:BookSection bibo:EditedBook bibo:AcademicArticle rdfs:subClassOf rdfs:subClassOf bibo:AudioVisualDocument bibo:Chapter <=1 bibo:partOf bibo:Issue <=1 bibo:partOf bibo:Journal
- 18. Example: LRMI A common framework common metadata framework for describing or “tagging” learning resources on the web, with Schema.org Schema.org/CreativeWork educationalUse “e.g. assignment” timeRequired learningResourceType audience “e.g. presentation” LRMI/EducationalAudience useRightsUrl subClass Schema.org/Audience Schema.org/Duration educationalRole Schema.org/URL “e.g. HE student” http://www.lrmi.net/the-specification
- 19. Case-Study: Bowlogna Ontology Fostering Open Curricula and Agile Knowledge Bases for Europe’s Higher Education Landscape • The Bowlogna ontology • Extending & managing Bowlogna data – Entity-centric data management
- 20. The Bologna Reform • Started in June 1999 • Framework for higher education systems • 47 Countries • Common academic degrees • Common study structure • Common terminology 20
- 21. The university setting after Bologna • A lot of data is available – Not following standard schemas – Comprehensive and available data is a success factor • Shared data – Erasmus exchanges – Courses in a given language • Analytic tools may help monitoring university performance 21
- 22. An ontology about Bologna • A Lexicon for the Bologna Reform – Basic set of terms for the new system – Stable across time and institutions – Developed by a professional terminologist 22
- 23. The ontology creation process • The Bowlogna Ontology – 29 top classes (67 in total) – Classes: student, professor, evaluation, teaching unit, ECTS credit, semester, etc. – Concept definitions in English, French, German 23
- 25. Bowlogna Ontology • Private / Public parts – Public data can be shared with other uni (e.g., course descriptions) – Private data in sensible (e.g., evaluation results) • Private data might contain more instances • Aggregations over private data may be shared (e.g., number of enrolled students) 25
- 26. Managing Bowlogna Data • Entity-Centric Data Management – Searching for entities – Linking entities – Typing entities – Storing entities 26
- 27. Entities as Mediation • Rising paradigm – Store information at the entity granularity – Integrate information by inter-linking entities • Advantages? – Coarser granularity compared to keywords • More natural, e.g., brain functions similarly (or is it the other way around?) • Easier to integrate 3rd party information – Denormalized information compared to RDBMSs • Schema-later, heterogeneity, sparsity • Pre-computed joins, “Semantic” linking • Drawbacks? 27
- 28. Searching for Entities (1) • Main idea: combine unstructured and structured search – Inverted index to locate first candidates – Graph queries to refine the results • Graph traversals (queries on object properties) • Graph neighborhoods (queries on data type properties) type type type Keywords SPARQL title playsIn TheDescendants The Descendants HTTP GeorgeClooney dateOfBirth playsIn name May 6, 1961 name Shailene Woodley ShaileneW dateOfBirth Nov. 15, 1991 George Clooney Inverted Index DBMS 28
- 29. Searching for Entities (2) 3rd party search engines Pseudo-Relevance Feedback Entity Search Keyword Query Query Annotation and Expansion User Graph-Enriched Results WordNet Final Ranking Function Ranking Ranking Functions Ranking Functions Functions intermediate top-k results Inverted Index index() Structured Inverted Index Graph Traversals (queries on object properties) Neighborhoods (queries on datatype properties) RDF Store query() LOD Cloud 29
- 30. Linking Entities (1) • ZenCrowd: linking textual content to entities • Uses sets of algorithmic matchers to match entities to online concepts • Uses dynamic templating to create micromatching-tasks and publish them on MTurk • Combines both algorithmic and human matchers using probabilistic networks 30
- 31. Linking Entities (2) HTML Pages Input Z enCrowd Micro Matching Tasks MicroTask Manager Entity Extractors Crowdsourcing Platform HTML+ RDFa Pages Output Algorithmic Matchers Decision Engine Probabilistic Network LOD Index Get Entity Workers Decisions LOD Open Data Cloud 31
- 32. Storing Entities (1) • Fundamental impedance mismatch between graphs of entities and… – N-ary / decomposition storage model – Inverted Indices – Key-value paradigms 32
- 33. Storing Entities (2) • dipLODocus[RDF] – Materialize the joins! – Dense-pack the values – Provide new indices – Co-locate – Co-locate – Co-locate 33
- 34. Typing Entities Trank • Input: a knowledge base G, an Entity e, a context c in which e appears. • Output: e’s types ranked by relevance wrt the context c. Text extraction (BoilerPipe) Ranked list of types Named Entity Recognition (Stanford NER) Type ranking Type ranking Type ranking Type ranking List of entity labels List of type URIs foreach Entity linking (inverted index: DBpedia labels ⟹ resource URIs) Type retrieval (inverted index: resource URIs ⟹ type URIs) List of entity URIs 34
- 35. References • • • • • The Bowlogna ontology: Semantic Web J. 2013 Searching for entities: SIGIR 2012 Linking entities: WWW 2012,VLDB J. 2013 Storing entities: ISWC 2011 Typing entities: ISWC 2013 35
- 36. Pause What else needs representing in educational data?
- 37. What to do with it Social Resource Discovery Research Exploration
- 38. Example: UK HESA/UNISTAT Key Information Set http://www.hesa.ac.uk/unistatsdata “Unistats, which incorporates the KIS, provides course level information on all undergraduate higher education courses provided in the UK, which are of at least one year’s duration and consist of 120 or more credits of study” [1] Includes statistics about the success rate of degrees (courses), the type of assessment, and what students do afterwards (further study, jobs). [1] http://www.hesa.ac.uk/includes/C13061_resources/Unistats_checkdoc_ definitions.pdf?v=1.12
- 39. Simple application: Tell me the job you want to do, I tell you what degree (in the UK) you might want to study
- 40. Currently: It is Open Data (kind of)
- 41. Building an application on top of this? Need to download the data, unzip parse the xml, re-interpret it into own model, store the data, provide querying facility, and finally, build the application. Doing it as linked data with a SPARQL endpoint does that once for everybody! http://data.linkededucation.org/linkedup /catalog/browse/
- 42. 90 lines of HTML/Javascript, written in a couple of hours Using this SPARQL Query: select distinct ?course ?label ?link ?perc where { ?o <http://purl.org/linked-data/cube#dataSet> <http://data.linkedu.eu/kis/dataset/commonJobs>. ?o <http://data.linkedu.eu/kis/ontology/job> <http://data.linkedu.eu/kis/job/354>. ?o <http://data.linkedu.eu/kis/ontology/course> ?course. ?course <http://purl.org/dc/terms/title> ?label. ?course <http://data.linkedu.eu/kis/ontology/courseUrl> ?link. ?o <http://data.linkedu.eu/kis/ontology/percentage> ?perc. filter ( ?perc > 0 ) } order by desc(?perc)
- 43. Example: Resource Discovery (http://discou.info)
- 45. Resources URIs + common topics Interface SimilarityBased Search BBC Programme or iPlayer page Resource descriptions Indexes Synopsis Named Entity Recognition Semantic Entities (Dbpedia) Podcasts, OpenLearn Units and Articles data.open.ac.uk Semantic Indexing Indexes Semantic Index
- 46. API/Service view Named Entity Recognition Programme URI Similarity Search Indexing Scored sem. Entities & Prg URI Prg. URI Resource URIS Common Topic Extraction Prg. URI & Res. URI Common Sem. Entity Scored semantic entities Injected with bookmarklet Interface (Javascript)
- 47. Same thing, with just text (discou.info/alfa)
- 48. And on course material (open + closed data)
- 49. Example: Topic Exploration Domain Number of datasets Media 25 1,841,852,061 5.82 % 50,440,705 10.01 % Geographic 31 6,145,532,484 19.43 % 35,812,328 7.11 % Government 49 13,315,009,400 42.09 % 19,343,519 3.84 % Publications 87 2,950,720,693 9.33 % 139,925,218 27.76 % Cross-domain 41 4,184,635,715 13.23 % Life sciences 41 3,036,336,004 User-generated content 20 134,127,413 295 17/11/13 Triples 31,634,213,770 % (Out-)Links % 63,183,065 12.54 % 9.60 % 191,844,090 What is the data about? 38.06 % 0.42 % 3,449,143 0.68 % 503,998,829 Source: http://lod-cloud.net/state, September 2011 LinkedUp – Besnik Fetahu 17/11/13 49
- 50. The Big Picture: What is the data about? Domain Number of datasets Media 25 1,841,852,061 5.82 % 50,440,705 10.01 % Geographic 31 6,145,532,484 19.43 % 35,812,328 7.11 % Government 49 13,315,009,400 42.09 % 19,343,519 3.84 % Publications 87 2,950,720,693 9.33 % 139,925,218 27.76 % Cross-domain 41 4,184,635,715 13.23 % Life sciences 41 3,036,336,004 User-generated content 20 134,127,413 295 Triples 31,634,213,770 % (Out-)Links % 63,183,065 12.54 % 9.60 % 191,844,090 38.06 % 0.42 % 3,449,143 0.68 % and many more languages (16)… 503,998,829 and many more organisatio ns (184)… 17/11/13 LinkedUp – Besnik Fetahu 50
- 51. The Big Picture: How to find the right information? How to find information about “renewable energy”? search into individual resources in all these sources? Generate representative topics for the individual data sources Topics linking the data sources into a central and interlinked graph Explore the graph for specific concepts e.g. “renewable energy” 17/11/13 now what? 338 sources of information ~300 million individual resources - Manual inspection costly! - Current infrastructure is not reliable for such large scale queries! LinkedUp – Besnik Fetahu 51
- 52. Constructing Topic Profiles proceedings series http://de.dbpedia.org/ http://de.dbpedia.org/page/ http://de.dbpedia.org/pag http://dbpedia.org/page/ http://dbpedia.org http://dbpedia.org/p http://dbpedia.org/p report newspaper thesis e/Videoclip page/Linux Animation The Biodiesel /page/Price age/Economy age/Biofuel types of category:Pri category:Biodie audio documentcategory:Bioenerg category- information category:Economics manuscript categorycing sel y category-de:Animation de:Video de:Freies_Betriebssystem existing in the category:Biofue organization category:Economic book category:Marketing category:Biomass ls data source _systems category-de:Linux category:Liquid individual category:Fuels _fuels categorycategory:Renewab de:Unixoides_Betriebssystem le_fuels resources "British Association for Biofuels and Oils“ "British Association for and “ The prime objective of the Association is to persuade Government to modify the tax The prime objective of the Association is'green' fuel a Government to modify the tax to persuade chance to establish itself to on Biodiesel so as to give this splendidly Linux in wenigen Stunden beherrschen ; absolut keine the advantage of the environment. This means'green' fuel a chance to establish itself on so as to give this splendidly a tax structure which ensures that in wenigen Stunden beherrschen ; absolut keine Vorkenntnisse nötig! ; ideal für Einsteiger und Umsteiger ;the pump price of Biodiesel is at least competitive with fossil diesel. A second Vorkenntnisse Videos;und Sprachausg. erklären LINUX to the advantage established in Britain a Biodiesel means asufficient size which the . This plant of tax structure to get Animationen, nötig! ideal für Einsteiger und Umsteiger; objective is to seeof the Schritt für Schritt. , appropriate economies of scale in production costs. competitive with fossil diesel. und Sprachausg. erklären ensures that the pump of Biodiesel is at least LINUX Schritt für Schritt. A second objective is to see established in a Biodiesel plant of sufficient Biofuels Linux Animationen Videos 17/11/13 Oils Biodiesel environment price Britain LinkedUp – Besnik Fetahu size to get the appropriate economies of scale in production costs. 52
- 53. Constructing Topic Profiles (I) individual resources Linux in wenigen Stunden beherrschen; absolut keine Vorkenntnisse nötig! ; ideal für Einsteiger und Umsteiger; Animationen, Videos und Sprachausg. erklären LINUX Schritt für Schritt. "British Association for Biofuels and Oils“ The prime (…) to persuade Government to modify the tax on Biodiesel so as to give (…) to the advantage of the environment. This means a tax (…)that the pump price of (….) A second objective is to see established in Britain a Biodiesel plant of (…)appropriate economies of scale in production costs. topic profiles from the individual sources linu x economic systems bioenergy biofue l liquid fuels economy biomass video fuel biodiesel
- 54. Exploring topics: Finding the right information? How to find information about “renewable energy”? search individual resources from all information sources? economic systems biofuel linux bioenergy liquid fuels economy biomass fu el video biodiesel • Searching for topics about “renewable energy”, we find the following? • 5 datasets • data-gov-uk, clean-energy-reegle, educationalprograms_sisvu,… • Thousands of resources talking about: biodiesel, biofuel, wind farms, hydroelectricity, solar power, sugar canes, etc. 17/11/13 LinkedUp – Besnik Fetahu explorable topic graph 54
- 55. Finding resources about “Renewable Energy” http://www.reegle.info/profiles/JP http://enipedia.tudelft.nl/wiki/Windmar_Renewable_Energy • From millions of resources from all information http://enipedia.tudelft.nl/data/page/eGRID/Plant/57050 sources to top matching ranked resources about “Renewable Energy” http://enipedia.tudelft.nl/wiki/Us_Energy_Biogas_Corp • Resources with “Renewable Energy” as a topic convey information about different forms of renewable energy: • Solar Energy • Wind-farms • Biogas • Hydroelectricity etc. 17/11/13 LinkedUp – Besnik Fetahu 55
- 56. Topic Profiling: Applications! http://data-observatory.org/lod-profiles/ http://data-observatory.org/lod-profiles/profile-explorer/ http://data-observatory.org/lodprofiles/sparql-endpoint 17/11/13 LinkedUp – Besnik Fetahu 56
- 57. More examples: Data mining, knowledge discovery, analytics Exploring communities Course management Learning Analytics
- 58. Pause What applications for educational Web data?
- 59. Open Education Removing barriers to education
- 60. Open Education Food for thought More minds online • Around 2.7 billion people (40% of the world's population) will be connected to the Internet by the end of 2013 – UN sources • Several billion more in the forthcoming years – from developing countries, many with disabilities • Worldwide demand for higher education • New pedagogies needed for large-scale student teaching
- 61. Open Data in Education Overview Open data in education • All open data that can be used for educational purposes (e.g research data, GLAM data etc.) Data exploited/used by education. Open data that comes out of education institutions • Administrative data created by educational institutions that can improve efficiency, allow students to make informed decisions etc. Both relevant to the LinkedUp Project
- 62. What type of data?
- 64. How can we use open data …to meet educational needs? By supporting students • Through creation of new tools that enable new ways to analyse and access data e.g. maps of disabled access, tools for disciplines • By enriching resources, making it easier to share and find them, and how to personalize the way they are presented • By allowing student to explore resources, concepts, ideas and objects in various areas • To make informed choices on education e.g. by comparing scores, course data etc.
- 65. How can we use open data …to meet educational needs? By supporting schools and institutions • Learning analytics data can help retain students • Use data can enable efficiencies in practice e.g. library data can help support book purchasing • Benchmarking and performance measuring By supporting governments and policy • Open data can lead to change in policy • Open data can lead support transparency & enable efficiency • Data on equity and equality issues (3rd world countries) • Education reform
- 66. Education & Development How can open data help? • Data is crucial for planning, managing budgets and spending, and evaluation • Transparency of data is essential • Interesting work going on to build tools to analyse data, building capacity etc. • Global Partnership for Education Open Data Project (57 key education indicators from 29 countries) • The data revolution in education and development: http://bit.ly/data-development • School of data: http://schoolofdata.org
- 67. Keep an eye on…
- 68. Working Group Overview • Binds together people to promote open data, open educational resources (OER) and open educational practices • First activity: Writing the Open Education Handbook • Mailing list, Twitter feed • Want to see the discussions around open data in education pulled into the wider debates around open education • http://education.okfn.org
- 69. Open Education Handbook Overview • First activity of Working Group • Deliverable for LinkedUp Project • Collaboratively authored • Booksprint #1 London • Booksprint #2 Berlin • Open Ed Timeline event • Now on Booktype • Looking at synergies between areas
- 74. Case Study: data.open.ac.uk AIISO Course information: 600 modules/ description of the course, information about the levels and number of credits associated with it, topics, and conditions of enrolment. Research publications: FOAF 25,000 academic articles / information about authors, dates, abstract and venue of the publication. Podcasts: BIBO 2220 video podcasts and 1500 audio podcats / short description, topics, link to a representative image and to a transscript if available, information about the course the podcast might relate to and license information regarding the content of the podcast. Open Educational Resources: 640 OpenLearn Units / short description, topics, tags used to annotate the resource, its language, the course it might relate to, and the license that applies to the content. DC Youtube videos: 900 videos / short description of the video, tags that were used to annotate the video, collection it might be part of and link to the related course if relevant. University buildings: GEO 100 buildings / address, a picture of the building and the sub-divisions of the building into floors and spaces. Library catalogue: MEDIA 12,000 books/ topics, authors, publisher and ISBN, as well as the course related. Others…
- 75. Deployment Web server SPARQL endpoint URI Resolver Dedicated extractors Original systems / Databases daily updates RDF Triple store
- 77. Example: data.open.ac.uk/query select distinct ?q (count(distinct ?t) as ?n) where { ?q a <http://purl.org/net/mlo/qualification>. ?q <http://data.open.ac.uk/saou/ontology#hasPathway> ?p. ?p <http://data.open.ac.uk/saou/ontology#hasStage> ?s. {{?s <http://data.open.ac.uk/saou/ontology#includesCompulsoryCourse> ?c} union {?s <http://data.open.ac.uk/saou/ontology#includesOptionalCourse> ?c}}. ?c <http://purl.org/dc/terms/subject> ?t. [] <http://www.w3.org/2004/02/skos/core#hasTopConcept> ?t. } group by ?q order by desc(?n) List of courses (degrees, etc.) at The Open University, with number of topics they cover URI of the query: http://data.open.ac.uk/query?query=select%20distinct%20...
- 78. Example: Map of buildings Interactive map of Open University Buildings in the UK Built in 1 hour Connected to Ordnance Survey for location based on post-codes Allowed us to find out about issues in the data.