mtsr

Linked Data Scopes

~ Victor ~ Leave a comment

At this year’s Metadata and Semantics Research Conference (MTSR2020), I just presented our work on Linked Data Scopes: an ontology to describe data manipulation steps. The paper was co-authored with Ivette Bonestroo, one of our Digital Humanities minor students as well as Rik Hoekstra and Marijn Koolen from KNAW-HUC. The paper builds on earlier work by the latter two co-authors and was conducted in the context of the CLARIAH-plus project.

This figure shows envisioned use of the ontology: scholarly output is not only the research paper, but also an explicit data scope. This data scope includes (references to) datasets.

With the rise of data driven methods in the humanities, it becomes necessary to develop reusable and consistent methodological patterns for dealing with the various data manipulation steps. This increases transparency, replicability of the research. Data scopes present a qualitative framework for such methodological steps. In this work we present a Linked Data model to represent and share Data Scopes. The model consists of a central Data scope element, with linked elements for data Selection, Linking, Modeling, Normalisation and Classification. We validate the model by representing the data scope for 24 articles from two domains: Humanities and Social Science.

The ontology can be accessed at http://biktorrr.github.io/datascope/ .

You can do live sparql queries on the extracted examples as instances of this ontology at https://semanticweb.cs.vu.nl/test/query

Paper: Victor de Boer, Ivette Bonestroo, Rik Hoekstra and Marijn Koolen A Linked Data Model for Data Scopes. In Proceedings of 14th International Conference on Metadata and Semantics Research. MTSR2020 Springer CCIS vol 1335 Download

You can watch a pre-recorded video of my presentation below. Or you can check out the slides here [pdf]

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The Benefits of Linking Metadata for Internal and External users of an Audiovisual Archive

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[This post describes the Master Project work of Information Science students Tim de Bruyn and John Brooks and is based on their theses]

Audiovisual archives adopt structured vocabularies for their metadata management. With Semantic Web and Linked Data now becoming more and more stable and commonplace technologies, organizations are looking now at linking these vocabularies to external sources, for example those of Wikidata, DBPedia or GeoNames.

However, the benefits of such endeavors to the organizations are generally underexplored. For their master project research, done in the form of an internship at the Netherlands Institute for Sound and Vision (NISV), Tim de Bruyn and John Brooks conducted a case study into the benefits of linking the “Common Thesaurus for Audiovisual Archives” (or GTAA) and the general-purpose dataset Wikidata. In their approach, they identified various use cases for user groups that are both internal (Tim) as well as external (John) to the organization. Not only were use cases identified and matched to a partial alignment of GTAA and Wikidata, but several proof of concept prototypes that address these use cases were developed. 

 

For the internal users, three cases were elaborated, including a calendar service where personnel receive notifications when an author of a work has passed away 70 years ago, thereby changing copyright status of the work. This information is retrieved from the Wikidata page of the author, aligned with the GTAA entry (see fig 1 above).

A second internal case involves the new ‘story platform’ of NISV. Here Tim implemented a prototype enduser application to find stories related to the one currently shown to the user, based on persons occuring in that story (fig 2).

The external cases centered around the users of the CLARIAH Media Suite. For this extension, several humanities researchers were interviewed to identify worthwile extensions with Wikidata information. Based on the outcomes of these interviews, John Brooks developed the Wikidata retrieval service (fig 3).

The research presented in the two theses are a good example of User-Centric Data Science, where affordances provided by data linkages are aligned with various user needs. The various tools were evaluated with end users to ensure they match their actual needs. The research was reported in a research paper which will be presented at the MTSR2018 conference: (Victor de Boer, Tim de Bruyn, John Brooks, Jesse de Vos. The Benefits of Linking Metadata for Internal and External users of an Audiovisual Archive. To appear in Proceedings of MTSR 2018 [Draft PDF])

Find out more:

See my slides for the MTSR presentation below

 

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DIVE+ collection enrichment paper wins best paper award at MTSR2017

~ Victor ~ Leave a comment

Last week, I visited the 11th Metadata and Semantics Research Conference (MTSR2017) in Tallinn, Estonia. This conference brings together computer scientists. information scientists and people from the domain of digital libraries to discuss their work in metadata and semantics. The 2017 edition of the conference draws around 70 people which is a great size for a single-track conference with lively discussions. The paper included interesting tracks on Cultural Heritage and Library (meta)data as well as one on Digital Humanities.

On the last day I presented our paper “Enriching Media Collections for Event-based Exploration” [draft pdf], co-authored with the people in the CLARIAH and DIVE+ team working on data enrichment and APIs: Liliana Melgar, Oana Inel Carlos Martinez Ortiz, Lora Aroyo and Johan Oomen.  The slides for the presentation can be found here on slideshare. We were very happy to hear that our paper was presented the MTSR2017 Best Paper Award!

In the paper, we present a methodology to publish, represent, enrich, and link heritage collections so that they can be explored by domain expert users. We present four methods to derive events from media object descriptions. We also present a case study where four datasets with mixed media types are made accessible to scholars and describe the building blocks for event-based proto-narratives in the knowledge graph

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