Towards long-term preservation of linked data - the PRELIDA project


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The slides were presented at the EOD Conference 2014 in Innsbruck, Austria by Dr. García José María, a member of the PRELIDA project.

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Towards long-term preservation of linked data - the PRELIDA project

  1. 1.© Copyright 2008 STI INNSBRUCK Towards long-term preservation of linked data The PRELIDA project Dieter Fensel & José M. García 11th April 2014 – EOD Conference, Innsbruck
  2. 2. Short biographies • Univ.-Prof. Dr. Dieter Fensel – Professor at the University of Innsbruck, Austria – Director of Semantic Technology Institute (STI) Innsbruck – Scientific director and coordinator of more than 70 ICT & IST projects • Dr. José María García – University assistant (Postdoc) at the University of Innsbruck, Austria – Senior researcher at STI Innsbruck – Participation in several national and EU-funded projects, including WP leadership in PRELIDA and BYTE • STI Innsbruck ( – A leading institute for semantic technologies – Established in Innsbruck, Tyrol, in August 2002, initially as a “Next Web Generation” research group at the University of Innsbruck – Possesses strong links to local start-ups and SMEs, especially in the areas of tourism and online marketing – Participating in PRELIDA in roadmapping, scientific events organization and dissemination leaders 2
  3. 3. Outline • Public Open Data • Linked (Open) Data • PRELIDA: Digital Preservation  Linked Data • What Digital Preservation community can provide • What Linked Data community needs • Outlook 3
  4. 4.© Copyright 2008 STI INNSBRUCK Public Open Data Open Data
  5. 5. Public Open Data: What is Open Data? 5 Definitions: • Open data is non-personally identifiable data produced in the course of an organisation’s ordinary business, which has been released under an unrestricted licence (like the Open Government Licence). • Open public data is underpinned by the philosophy that data generated or collected by organisations in the public sector should belong to the taxpayers, wherever financially feasible and where releasing it won’t violate any laws or rights to privacy (either for citizens or government staff). [linkedgov project]
  6. 6. Public Open Data: Features of Open Data Open Data principles [1]: 1. completeness – all data that can be open (w.r.t. privacy and security) should be open 2. primary source – all open data should be gathered at their source in raw format 3. temporal closeness – all open data should be up-to-date 4. easy access – all open data should be easily accessible 5. machine readability – all open data should be structured for machine processing 6 [1] Source [Kaltenböck M., Thurner T., (Hg.): Open Government Data Weißbuch, 2011]
  7. 7. Public Open Data: Features of Open Data Open Data principles [1]: 6. non-discriminating – all open data should be accessible for everyone 7. open standards – all open data should use open standards 8. liberal licensing – all open data should use a liberal licensing without huge obligations for potential users 9. durability – all open data should be available on a long term basis 10. non-discriminating usage costs – some open data might involve usage costs. These should be kept as low as possible. 7 [1] Source [Kaltenböck M., Thurner T., (Hg.): Open Government Data Weißbuch, 2011]
  8. 8. Public Open Data • Openness: Open Data is about changing behaviour • Heterogeneity: Different vocabularies are used • Interlinking: Need to link these data sets to prevent data silos •  Linked Open Data 8
  9. 9.© Copyright 2008 STI INNSBRUCK Linked (Open) Data
  10. 10. 10 Motivation: From a Web of Documents to a Web of Data • Web of Documents • Fundamental elements: 1. Names (URIs) 2. Documents (Resources) described by HTML, XML, etc. 3. Interactions via HTTP 4. (Hyper)Links between documents or anchors in these documents • Shortcomings: – Untyped links – Web search engines fail on complex queries “Documents” Hyperlinks
  11. 11. 11 Motivation: From a Web of Documents to a Web of Data • Web of Documents • Web of Data “Documents” “Things” Hyperlinks Typed Links
  12. 12. 12 Motivation: From a Web of Documents to a Web of Data • Characteristics: – Links between arbitrary things (e.g., persons, locations, events, buildings) – Structure of data on Web pages is made explicit – Things described on Web pages are named and get URIs – Links between things are made explicit and are typed • Web of Data “Things” Typed Links
  13. 13. Google Knowledge Graph • “A huge knowledge graph of interconnected entities and their attributes”. Amit Singhal, Senior Vice President at Google • “A knowledge based used by Google to enhance its search engine’s results with semantic-search information gathered from a wide variety of sources” • Based on information derived from many sources including Freebase, CIA World Factbook, Wikipedia • Contains about 3.5 billion facts about 500 million objects 13
  14. 14. Google Knowledge Graph 14
  15. 15. Linked Data – a definition and principles • Linked Data is about the use of Semantic Web technologies to publish structured data on the Web and set links between data sources. 15 Figure from C. Bizer
  16. 16. Linked Data – a definition and principles 1. Use URIs as names for things. 2. Use HTTP URIs so that people can look up (dereference) those names. 3. When someone looks up a URI, provide useful information, using the standards (RDF*, SPARQL) 4. Include links to other URIs. so that they can discover more things. 16
  17. 17. 5-star Linked (Open) Data Available on the web (whatever format) but with an open license, to be Open Data Available as machine- readable structured data (e.g. excel instead of image scan of a table) as (2) plus non-proprietary format (e.g. CSV instead of excel) All the above plus, Use open standards from W3C (URIs, RDF and SPARQL) to identify things, so that people can point at your stuff All the above, plus: Link your data to other people’s data to provide context 17
  18. 18. 18 LOD Cloud May 2007 Figure from
  19. 19. 19 LOD Cloud May 2007 Basics: The Linked Open Data cloud is an interconnected set of datasets all of which were published and interlinked following the Linked Data principles. Facts: •Focal points: •DBPedia: RDFized vesion of Wikipiedia; many ingoing and outgoing links •Music-related datasets •Big datasets include FOAF, US Census data •Size approx. 1 billion triples, 250k links Figure from
  20. 20. 20 LOD Cloud September 2011 Figure from
  21. 21. 21 LOD Cloud September 2011 Facts: • 295 data sets • Over 31 billion triples • Over 504 billion RDF links between data sources Figure from
  22. 22. Challenges ahead • Data economy – Non tangible assets (i.e. data) play a significant role in the creation of economic value – Data generates the potential for many new types of product of services – Sustainability of services depends on availability of data • Linked Data community – needs to preserve the data • Digital Preservation community – needs Linked Data for metadata – faces new challenges by Linked Data • So far, little or no interaction between the two communities 22
  23. 23.© Copyright 2008 STI INNSBRUCK The PRELIDA project
  24. 24. PRELIDA • PREserving LInked DAta • EU-funded Coordination and Support Action (FP7) • Running from 01/2013 to 12/2014 • Consortium – Consiglio Nazionale delle Richerche – Alliance for Permanent Access – University of Huddersfield – Universität Innsbruck, STI Innsbruck – Europeana Foundation – STI International 24
  25. 25. PRELIDA – Objectives Bridge the Linked Data and Digital Preservation communities for • making the LD community aware of the existing DP results • making the DP community aware of the challenges posed by LD – intrinsic features of Linked Data, including their structuring, interlinking, dynamicity and distribution. 25
  26. 26. PRELIDA – Objectives • collect, organize and publish use cases related to the long-term access to LD • create a comprehensive state of the art on LD and DP technologies • set up a technology observatory • bring together scientists and stakeholders for identifying relevant challenges and paths for addressing them in the near future • draw attention of standardization bodies 26
  27. 27. PRELIDA – Next event More info at 27 • PRELIDA / ESWC Summer School • Featuring specific track for Digital Preservation of Linked Data • From 1st to 6th September 2014 • Venue: Kalamaki, Crete, Greece • Application is now open! • Deadline: June 20th • Several grants available
  28. 28.© Copyright 2008 STI INNSBRUCK What Digital Preservation community can provide
  29. 29. Digital Preservation - definition • “Digital preservation refers to the series of managed activities necessary to ensure continued access to digital objects for as long as necessary” Neil Beagrie and Maggie Jones: “Preservation management of digital materials: The Handbook” (Digital Preservation Coalition, 2008) • “The goal of digital preservation is, hence, the accurate rendering of authenticated content over time” Wikipedia • “The act of maintaining information, Independently Understandable by a Designated Community, and with evidence supporting its Authenticity, over the Long Term” Open Archival Information System (OAIS) 29
  30. 30. OAIS Reference model 30
  31. 31. Digital Preservation - some solutions • Use file formats based on standards • Use services of digital archives to store documents for the long-term • Create and maintain high quality documentation • Use multiple storage facilities (the LOCKSS -Lots Of Copies Keeps Stuff Safe- method) 31
  32. 32. Web archiving – Internet Archive ( 32
  33. 33. Web archiving – National Libraries 33
  34. 34. Web archiving – National Libraries 34
  35. 35. Digital Preservation – topics relevant for LD • Object classification and validation – Rendered vs non-rendered – Complex vs simple – Dynamic vs static – Active vs passive • Representation information (representation network) – The information model is key – Recursion ends at KNOWLEDGEBASE of the DESIGNATED COMMUNITY (this knowledge will change over time and region) – Does not demand that ALL Representation Information be collected at once – A process which can be tested • Persistent identifiers • Audit & Certification / Trustworthy Digital Repositories 35
  36. 36.© Copyright 2008 STI INNSBRUCK What Linked Data community needs
  37. 37. Particularities of Linked Data • Differences between Linked Data and other types of data with respect to Digital Preservation requirements – Is it only about reliable storing RDF data? • Is LD preservation a special case of Web archiving? • Differences with other special types of data (e.g. multimedia content) • Functionality on top of RDF dataset (e.g. SPARQL endpoints, inference) – Must be also preserved? • Evolving data – Versioning – Other datasets directly or indirectly connected • Particularities of LD may complicate preservation requirements in terms of stakeholders, rights over data, ownership of an interlinked dataset and ownership of the archived version 37
  38. 38. Challenges ahead on LD preservation (I) • Selection of LD sources – Which data sources should be preserved? – When we stop crawling? -> Same as Web Archival? • Who is responsible for the preservation? • Which formats can we distinguish? • Database approach • What about Linked Data which is not Open? – Rights and licenses is the main difference, preservation-wise • Ownership and authenticity 38
  39. 39. Challenges ahead on LD preservation (II) • Storage – Multiple redundancy to reduce risks – Trust – Scalability (as in Web archival) • Metadata and definitions – Self-descriptiveness requires preserving the ontologies too – Provenance and additional information 39
  40. 40.© Copyright 2008 STI INNSBRUCK Outlook
  41. 41. Digital preservation  Linked Data • Ultimately, both communities can benefit from each other • Digital preservation using Linked Data – Archival metadata • Linked Data preservation – Storage redundancy – Archiving data – Retrieving functionality – Many other challenges to cover • 5-star Preservable Linked Data – Outcome of PRELIDA midterm workshop of last week – Upcoming report to be published 41
  42. 42. PRELIDA Roadmap • Gap analysis and consolidated state-of-the-art • Defining a roadmap for long-term preservation of Linked Data • PRELIDA Summer School – 1st-6th September 2014 – Kalamaki, Crete, Greece – More info at • Final PRELIDA workshop – October 2014 – Location TBD (tentatively co-located with ISWC 2014 in Riva del Garda, Italy) • Stay tuned at and @PRELIDA_project (Twitter) 42
  43. 43.© Copyright 2008 STI INNSBRUCK Thanks for your attention Any questions? PRELIDA is co-funded by the EU Commission under FP7 grant no. 600663