Abstract
Online cultural heritage resources are widely available through digital libraries maintained by numerous organizations. In order to improve discoverability in cultural heritage, the typical approach is metadata aggregation, a method where centralized efforts such as Europeana improve the discoverability by collecting resource metadata. The redefinition of the traditional data models for cultural heritage resources into data models based on semantic technology has been a major activity of the cultural heritage community. Yet, linked data may bring new innovation opportunities for cultural heritage metadata aggregation. We present the outcomes of a case study that we conducted within the Europeana cultural heritage network. In this study, the National Library of The Netherlands contributed by providing the role of data provider, while the Dutch Digital Heritage Network contributed as an intermediary aggregator that aggregates datasets and provides them to Europeana, the central aggregator. We identified and analyzed the requirements for an aggregation solution for the linked data, guided by current aggregation practices of the Europeana network. These requirements guided the definition of a workflow that fulfils the same functional requirements as the existing one. The workflow was put into practice within this study and has led to the development of software applications for administrating datasets, crawling the web of data, harvesting linked data, data analysis and data integration. We present our analysis of the study outcomes and analyze the effort necessary, in terms of technology adoption, to establish a linked data approach, from the point of view of both data providers and aggregators. We also present the expertise requirements we identified for cultural heritage data analysts, as well as determining which supporting tools were required to be designed specifically for semantic data.
| Original language | English |
|---|---|
| Article number | 252 |
| Pages (from-to) | 1-15 |
| Number of pages | 15 |
| Journal | Information (Switzerland) |
| Volume | 10 |
| Issue number | 8 |
| Early online date | 30 Jul 2019 |
| DOIs | |
| Publication status | Published - Aug 2019 |
Funding
Funding: This work was partially supported by Portuguese national funds through Fundação para a Ciência e a Tecnologia (FCT) with reference UID/CEC/50021/2013, and by the European Commission under contract number 30-CE-0885387/00-80.e, and grant agreement number INEA/CEF/ICT/A2018/1633581. This work was partially supported by Portuguese national funds through Funda??o para a Ci?ncia e a Tecnologia (FCT) with reference UID/CEC/50021/2013, and by the European Commission under contract number 30-CE-0885387/00-80.e, and grant agreement number INEA/CEF/ICT/A2018/1633581. We would like to acknowledge the supporting work by Valentine Charles and Marjolein de Vos, from the Europeana Foundation, in the analysis of the EDM and Schema.org data models, as well as their analysis of samples collected during the case study.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- Big Data variety
- Data aggregation
- Data analysis
- Datasets
- RDF
- Semantics
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