Discovering Object Stories: Linking Unstructured Museum Data Through Semantic Annotation
This paper explores the application of Recogito Studio for annotating unstructured museum data to create semantic links and visualisations. The study focuses on a sample dataset from National Museums Scotland, which includes metadata about navigational instruments from the 19th and early 20th centur...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Ubiquity Press
2025-01-01
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| Series: | Journal of Open Humanities Data |
| Subjects: | |
| Online Access: | https://account.openhumanitiesdata.metajnl.com/index.php/up-j-johd/article/view/273 |
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| Summary: | This paper explores the application of Recogito Studio for annotating unstructured museum data to create semantic links and visualisations. The study focuses on a sample dataset from National Museums Scotland, which includes metadata about navigational instruments from the 19th and early 20th centuries. The authors aimed to develop methods for converting unstructured data into structured formats using Recogito Studio. Recogito Studio facilitates semantic annotation by allowing users to highlight and tag entities and relationships in texts and images, and link places to online gazetteers. The data model was developed using Linked Art and CIDOC CRM standards, with some bespoke terminology. Annotations focused on unstructured text fields, using Recogito Studio’s Geo-Tagger plugin to identify and tag geographical locations. The geo-tagged data was exported and visualised using Peripleo, requiring several data transformations to ensure compatibility. A user evaluation with cultural heritage professionals revealed usability challenges and areas for improvement, with Recogito Studio receiving a UMUX score of 73.3 and recommendations include enhancing geo-tagging, incorporating Named Entity Recognition, and developing automated workflows for Linked Open Data production. |
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| ISSN: | 2059-481X |