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Aggregation of Linked Data in the Cultural Heritage Domain: A Case Study in the Europeana Network

1
INESC-ID, Rua Alves Redol 9, 1000-029 Lisbon, Portugal
2
National Library of the Netherlands, 2595 BE The Hague, The Netherlands
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Metamatter, 9832 TE Den Horn, The Netherlands
4
Dutch Digital Heritage Network, 2595 BE The Hague, The Netherlands
5
Europeana Foundation, 2595 BE The Hague, The Netherlands
6
Department of Computer Science, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
*
Author to whom correspondence should be addressed.
This paper is an extended version of our presentation in the 2018 IEEE International Conference on Big Data, Seattle, WA, USA, 10–13 December 2018.
Information 2019, 10(8), 252; https://doi.org/10.3390/info10080252
Received: 18 June 2019 / Revised: 19 July 2019 / Accepted: 27 July 2019 / Published: 30 July 2019
(This article belongs to the Special Issue Big Data Research, Development, and Applications––Big Data 2018)
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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. View Full-Text
Keywords: data aggregation; data analysis; datasets; semantics; Big Data variety; RDF data aggregation; data analysis; datasets; semantics; Big Data variety; RDF
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Freire, N.; Voorburg, R.; Cornelissen, R.; de Valk, S.; Meijers, E.; Isaac, A. Aggregation of Linked Data in the Cultural Heritage Domain: A Case Study in the Europeana Network. Information 2019, 10, 252.

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