2023-10-12 –, Create
For decades, GLAM institutions have been exploring the benefits of publishing their digital collections as Linked Open Data using controlled vocabularies. They have reused external repositories such as Wikidata and VIAF to enrich their content as well as to experiment with advanced visualisations. Recent advances in technology have provided a new context in which data quality has become a crucial element in a wide diversity of tasks such as the training of AI models and the use of NLP methods.
This session will present several methods to assess and describe the data quality in terms of Linked Open Data in the GLAM sector. In this context, SPARQL can be used to query an RDF dataset and retrieve the information required (e.g. number of classes, properties, etc.). More advanced approaches are based on the use of Shape Expressions that enable the definition of constraints to be tested against RDF datasets.
The session will encourage researchers to reuse high quality data provided by LOD repositories made available by GLAM institutions. It will provide an overview of the methods for the assessment of data quality in LOD by including real examples based on several research projects performed in collaboration with other institutions. The code is available in the form of open source code repositories to be able to reproduce the results.
http://rua.ua.es/dspace/handle/10045/109459
https://rua.ua.es/dspace/handle/10045/117374
https://doi.org/10.1002/asi.24761
Gustavo Candela is a member of the IT department at the Biblioteca Virtual Miguel de Cervantes since 2010. His main areas of research interest are Semantic Web and Collections as Data. He holds a PhD in Computer Science from the University of Alicante where he has been an associate professor since 2016. He authored several publications and is involved in the integration and quality of LOD in libraries. He has also worked with Collections as Data and Jupyter Notebooks. He is involved in the International GLAM Labs Community and he co-authored the Open a GLAM Lab book.