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Research into Practice case study 2: Library linked data implementations and perceptions: implications for practice

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The research underlying this presentation explored the role that libraries play in the linked data context. Focusing on European national libraries and Scottish libraries, multiple data gathering methods and constant comparative analysis were applied in the study. Amongst the findings, a general lack of awareness within the library community of the Semantic Web and the implications of linked data was identified. At the same time, there is recognition that linked data augments the discoverability and enhances the interoperability of library data. The presentation will include recommendations for the application of the findings of this research in practice.

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Research into Practice case study 2: Library linked data implementations and perceptions: implications for practice

  1. 1. RIVAL Network Event 2 – November 7th 2019 – Edinburgh Library linked data implementations and perceptions: implications for practice Dr Diane Pennington, Strathclyde University & Laura Cagnazzo, UWS Research, Impact, Value & LIS - #lisrival - Edinburgh – 7th November 2019
  2. 2. Library linked data implementations and perceptions: Implications for practice Dr Diane Rasmussen Pennington FHEA FRSA Senior Lecturer in Information Science, University of Strathclyde @infogamerist diane.pennington@strath.ac.uk Ms Laura Cagnazzo MA MSc Repository & Research Data Librarian, University of the West of Scotland @LauraFCagnazzo laurafcagnazzo@outlook.com
  3. 3. The evolution of the Web (1989-now) • Web 1.0: hand-coded HTML pages; accessible and readable, but not interactive • Web 2.0: Facebook and Twitter; everyone can post, share, and respond without extensive technical knowledge • Web 3.0: the Semantic Web – “Semantic” is “meaning in language” – “Semantic Web” communicates “the meaning of the content on web pages in a way that computers can understand. If they can process these meanings, they can then make and convey relationships between related web pages. This leads to improved – and more meaningful – information retrieval.” (p. 34) Source: Rasmussen Pennington, D. (2016, July/August). Demystifying linked data: Are you ready for what's next? CILIP Update, 34-36.
  4. 4. 4 Linked open data principles 1. Use URIs as names for things 2. Use HTTP URIs so that people can look up those names 3. When someone looks up a name, provide useful Resource Description Framework [RDF] information, using the standards (RDF*, SPARQL) 4. Include links to other URIs so that they can discover more things Source: http://www.w3.org/DesignIssues/LinkedData.html
  5. 5. 1. Use URIs as names for things 2. Use HTTP URIs so that people can look up names 5 • The Hypertext Transfer Protocol (HTTP) is a networking protocol for distributed, collaborative, hypermedia information systems. • HTTP is the foundation of data communication for the World Wide Web. • Use URIs to name people, for institutions, concepts, topics, and geographical places. Examples: • http://www.strath.ac.uk (a university) • https://www.facebook.com/CILIPinfo (a professional association) • https://personal.cis.strath.ac.uk/diane.pennington (a lecturer) • https://www.flickr.com/photos/chandlerinok/6168389622 (a Chihuahua)
  6. 6. 3. When someone looks up a name, provide useful [RDF] information 6 • Use RDF subject-predicate-object ‘triples’ to describe a thing • Reciprocate triples to show relationships between things Emma Watson → StarredInMovie → Harry Potter and the Half-Blood Prince Emma Watson is the subject, StarredInMovie is the predicate, and Harry Potter and the Half-Blood Prince is the object. This relationship also needs to be reciprocated: Harry Potter and the Half-Blood Prince → Has Movie Star → Emma Watson RDF, or Resource Description Framework, is the language of the Semantic Web predicate objectsubject
  7. 7. 7 4. Include links to other URIs so that users can discover more things An example using DBpedia; shows relationships between philosophers Source: http://io9.gizmodo.com/5923583/the-complete-history-of-philosophy-visualized-in-one-graph
  8. 8. 8 Google's Knowledge Graph uses linked data to connect related resources
  9. 9. • Semantic Web = enhanced form of web; content expressed in machine-readable format (Berners-Lee, Hendler, Lassila, 2001) • SW = goal; LD = means to reach it (Bizer et al., 2009) • LD as “a means to dismantle data silos” (Heath, 2009) • W3C standards • LD applied to library data: Baker et al., 2011; Tallerås, 2013; Shiri & Davoodi, 2016; OCLC surveys 2014, 2015, 2018 (Karen Smith-Yoshimura) Linked data: what we know
  10. 10. 10 Linked data use across European national libraries: methodology • Literature review • Semi-structured interviews (n=15; Skype, email) • Departmental ethics approval • Recruitment through Twitter, libraries’ email addresses, electronic mailing lists • Online resources analysis (n=26; Semantic Radar)
  11. 11. • Short online Qualtrics survey • Departmental ethics approval • Recruitment through Twitter, SLIC, CILIPS • Open from 03/05/17 to 18/05/2017 • n=113 completed responses Linked data: Opening Scotland’s library content to the world: methodology
  12. 12. Scottish library types participating in the survey Public School Academic Other National Did not specify
  13. 13. Scottish Government’s Open Data Strategy (2015) “This strategy seeks to create a Scotland where non- personal and non-commercially sensitive data from public services is recognised as a resource for wider societal use and as such is made open in an intelligent manner and available for re-use by others … The Vision sets out ambitions for a Scotland which, by 2020, recognises the value of data and responsibly makes use of data to improve public services and deliver wider societal and economic benefits for all.” Source: http://www.gov.scot/Publications/2015/02/6614
  14. 14. • Open government initiatives spreading world- wide • Transparency (fight corruption / improve accountability) • Enable citizens’ participation • Strengthen democracy • Data generated, gathered and stored by government agencies (e.g., national, school, public libraries) using public money (through taxes) should be available to everyone Open Government Data
  15. 15. • Two individual studies revealed similar results • Status of awareness of “linked data” and “Semantic Web” concepts • Linked data uses • Reasons for, challenges/benefits of linked data implementation • Recommendation and best practice Findings
  16. 16. Do you know what the term ‘Semantic Web' means? Definitely yes Probably yes Might or might not Probably not Do you know what the term 'linked data' means? Definitely yes Probably yes Might or might not Probably not Linked data awareness • European national libraries: lack of awareness among staff (e.g., IT) hinders projects design and actuation • Scottish libraries:
  17. 17. European nat. libraries Linked data implementation status Scottish libraries Have implemented Have plans to implement Have no current plans to implement No response Have Implemented Have plans to implement Not implemented Taking steps towards
  18. 18. Uses of linked data European nat. libraries • Provide data to LD data sets (VIAF, Wikidata, Europeana) • Publish bibliographic and authority data • National bibliographies • Digitized resources • Thesauri and ontologies Scottish libraries • MARC catalogue records • Digitized resources • Social media • Research outputs using RDF, Dublin Core, SPARQL • OWL, SKOS, Europeana Data Model
  19. 19. • Popularity of linked data on international scene (perceived/expected benefits) • Improve data visibility and discoverability • Enhance existing data sets • Enriched, open, reusable information, available for various purposes to the wider community • Adhere to standards (W3C) • Open up data silos Reasons for implementing linked data
  20. 20. • Lack of awareness • Lack of expertise / time / staff • Difficulties in obtaining management buy- in • Licencing constraints (permission needed from database providers to link) • Potential loss of control of data • Lack of agreement on standards • Lack of tools / guidelines Challenges of implementation
  21. 21. • Augment visibility and discoverability of library data • Support interoperability • Overcome linguistic barriers • Acquire better understanding of linked data potential • Enable cataloguing efficiency and innovation (e.g., workload reduction) • Obtain authoritative position as data provider (to which other institution will refer to) Benefits of implementation
  22. 22. • Is LD the right technology for your scope? • Design a detailed roadmap before acting • Consider legal issues • Training • Adopt tools to support implementation • Contact/collaborate with LD implementers • Seek expert developers, if necessary • URI syntax maintenance • Reuse data /existing vocabularies, whenever possible • Adopt entity-based approach to data Best practices
  23. 23. • Teach practitioners what linked data can achieve • Familiarize yourself with LD • Focus on goals, rather than technical matters • Involve your institution/community of stakeholders • Look at examples offered by successful projects • Focus on data specific to your institution • Consider needs of wider community (not just library community) • Collaborate with local universities/institutions and benefit from their expertise – Collaboration is key! Recommendations
  24. 24. • Encourage open data movement at government level • Case studies: Successful implementation examples • Re-use vs creation of ontologies • Licensing constraints • Step-by-step implementation guidelines • Improve communication between system providers/technicians and information professionals • Collaboration towards design and adoption of a common model, to facilitate data integration Further research / direction
  25. 25. Conclusions • Still far from the SW as envisaged by Berners-Lee, Hendler, and Lassila in 2001 – SW enabling better “understanding between humans and machines” • No agreed-upon standards = risk of “LD silos” • Need for spreading awareness and advocate for LOD with government / public bodies
  26. 26. Is that all???
  27. 27. Implementation/Review User testing – evaluation> revision> improvement Building documentation on progress>Assessing outcomes Project definition and planning Defining scope, timeframe, core team involved, desired end results Resource (staff, tools, budget) assessment – gap analysis Initial needs assessment / Management buy-in What is our data? Evidence of successful implementation cases - How implementation will benefit UWS Scenario: publishing researcher data as linked data at UWS
  28. 28. Thank you! (this is the end, we promise!)
  29. 29. References • Baker, T., Bermès, E., Coyle, K., Dunsire, G., Isaac, A., Murray, P., Panzer, P., Schneider, J., Singer, R., Summers, E., Waiters, W., Young, J. and Zheng, M. (2011) Library Linked Data Incubator Group final report, W3C, http://www.w3.org/2005/Incubator/lld/XGR-lld-20111025/ • Berners-Lee, T., Linked Data: http://www.w3.org/DesignIssues/LinkedData.html • Berners-Lee, T., Hendler, J. and Lassila, O. (2001) ‘The Semantic Web’. Scientific American, 284(5), pp.29-37, https://tinyurl.com/hh3h9m6 • Bizer, C., Heath, T. and Berners-Lee, T. (2009) ‘Linked Data: The story so far’. International Journal on Semantic Web and Information Systems, 5(3), pp.1-22 • Cagnazzo, L. (2017) Linked Data: Implementation, Use, and Perceptions across European National Libraries, MSc Dissertation, http://hdl.handle.net/10760/32004 • Heath, T. (2009) ‘Linked Data? Web of Data? Semantic Web? WTF?’ Tom Heath’s Displacement Activities, 2 March, http://tomheath.com/blog/2009/03/linked-data-web-of-data-semantic- web-wtf/ • Hobbs, P. (2009) Project management, London: Penguin Random House. • Rasmussen Pennington, D. (2016, July/August). Demystifying linked data: Are you ready for what's next? CILIP Update, 34-36. 29
  30. 30. • Rasmussen Pennington, D. (2017) ‘Linked data: Opening Scotland’s library content to the world’, https://www.slideshare.net/CILIPScotland/linked-data- opening-scotlands-library-content-to-the-world • Shiri, A. and Davoodi, D. (2016) ‘Managing Linked Open Data across discovery systems’, in Spiteri, L. (ed.) Managing metadata in web-scale discovery systems. London: Facet Publishing, pp.57-90 • Smith-Yoshimura, K. (2015) ‘Linked Data implementations— Who, what and why?’, http://www.oclc.org/research/themes/data- science/linkeddata.html • Suominen, O. and Hyvönen, N. (2017) ‘From MARC silos to Linked Data silos?’, O-bib, 4(2), https://www.o- bib.de/article/view/2017H2S1-13/5883 • The Linking Open Data cloud diagram: http://lod-cloud.net/ • Tallerås, K. (2013) ‘From many records to one graph: Heterogeneity conflicts in the linked data restructuring cycle’. Information Research, 18 (3), http://www.informationr.net/ir/18- 3/colis/paperC18.html#.WUEwnZB95dg References
  31. 31. RIVAL Network Event 2 – November 7th 2019 – Edinburgh Library linked data implementations and perceptions: implications for practice Dr Diane Pennington, Strathclyde University & Laura Cagnazzo, UWS Research, Impact, Value & LIS - #lisrival - Edinburgh – 7th November 2019

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