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Gabriel Bodard edited this page Mar 14, 2024 · 19 revisions

Linked Open Data: Digital collections

SunoikisisDC Digital Approaches to Cultural Heritage: Session 9

Date: Thursday March 14, 2024. 16:00-17:30 GMT.

Convenors: Paula Granados García (Endangered Material Knowledge Programme), Vera Moitinho de Almeida (CODA, University of Porto)

Youtube link: https://youtu.be/QF71MT_thJo

Slides: Combined slides (PDF)

Outline

This session introduces the concept of the Semantic Web and Linked Open Data Technologies (LOD) and its application to cultural heritage data as a way to interconnect, analyse and share digital collections. We discuss a series of resources that draw on these technologies and present a number of case studies to explore the research and dissemination value of LOD. We then introduce a freeware and open-source web-based tool called OpenRefine to clean and reconcile datasets.

Required readings

  • Zuiderwijk, A., Jeffery, K., & Janssen, M. (2012). "The Potential of Metadata for Linked Open Data and its Value for Users and Publishers." JeDEM - EJournal of EDemocracy and Open Government 4(2), 222-244. Available: https://doi.org/10.29379/jedem.v4i2.138.
  • Hugh A. Cayless. 2019. "Sustaining Linked Ancient World Data." In ed. Monica Berti, Digital Classical Philology: Ancient Greek and Latin in the Digital Revolution. De Gruyter Saur. Available: https://doi.org/10.1515/9783110599572-004.

Further readings

  • F. Bauer & M. Kaltenböck. 2012. Linked Open Data: The Essentials. Available: https://semantic-web.com/LOD-TheEssentials.pdf.
  • Paul Dilley, Ryan Horne & Sarah Bond (edd). 2020. Linked Ancient World Data: Practical Introductions. ISAW Papers 20. Available: http://dlib.nyu.edu/awdl/isaw/isaw-papers/20/
  • Thomas Elliott, Sebastian Heath & John Muccigrosso (edd). 2014. Current Practice in Linked Open Data for the Ancient World, edited by ISAW Papers 7. Available: http://dlib.nyu.edu/awdl/isaw/isaw-papers/7/
  • A. Freitas, E. Curry, J.G. Oliveira & S. O’Riain. 2012. "Querying Heterogeneous Datasets on the Linked Data Web: Challenges, Approaches, and Trends", IEEE Internet Computing 16 (1): 24–33. Available: http://www.edwardcurry.org/publications/freitas_IC_12.pdf
  • Gill, T. (2004). Building semantic bridges between museums, libraries and archives: The CIDOC Conceptual Reference Model. First Monday 9(5). Available: https://doi.org/10.5210/fm.v9i5.1145.
  • T. Heath and C. Bizer. 2011. Linked Data: Evolving the Web into a Global Data Space, in: J. Hendler and F. van Harmelen (eds.), Synthesis Lectures on the Semantic Web: Theory and Technology. Morgan & Claypool.
  • S. von Hooland and R. Verborgh. 2014. Linked Data for Libraries, Archives and Museums. How to clean, link and publish your metadata. London. Facet Publishing.
  • Alison Hitchens (2015). "What is #LODLAM?! Understanding Linked Open Data in Libraries, Archives [and Museums]" (Presentation slides). UWSpace. Available: http://hdl.handle.net/10012/12052.
  • P. Jain, P. Hitzler, P.Z. Yeh, K. Verma and A.P. Sheth. 2010. "Linked Data Is Merely More Data," in: D. Brickley, V.K. Chaudhri, H. Halpin, and D. McGuinness, Linked Data Meets Artificial Intelligence. Technical Report SS-10-07, AAAI Press, Menlo Park, California: 82–86. Available: https://web.archive.org/web/20120809091450/http:/knoesis.wright.edu/library/publications/linkedai2010_submission_13.pdf.
  • Palladino, Chiara; Bergman, James; Trammell, Caroline; Mixon, Eleanor; Fulford, Rebecca. 2019. "Using Linked Open Data to Navigate the Past: An Experiment in Teaching Archaeology." Available: https://doi.org/10.34894/PMZCUB.
  • Sarah Wild. 2024. "Millions of research papers at risk of disappearing from the Internet." Nature 4 March 2024. Available: https://doi.org/10.1038/d41586-024-00616-5.
  • Wilkinson, M., Dumontier, M., Aalbersberg, I. et al (2016). “The FAIR Guiding Principles for scientific data management and stewardship”. Scientific Data 3:160018. Available: https://doi.org/10.1038/sdata.2016.18.

Resources

Exercise

Following the instructions in the video and slideshow:

  1. Download and install OpenRefine. When you run the programme, a browser window will open.
  2. Download this sample dataset as CSV. Import the file into OpenRefine.
  3. Clean & transform the data for analysis
  4. Undo/Redo & using operations templates
  5. Reconcile & match data
  6. Export data for further analysis or visualisation
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