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Workflow models for aggregating cultural heritage data on the web: A systematic literature review

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  • Joyce Siqueira
  • Dalton Lopes Martins

Abstract

In recent years, different cultural institutions have made efforts to spread culture through the construction of a unique search interface that integrates their digital objects and facilitates data retrieval for lay users. However, integrating cultural data is not a trivial task; therefore, this work performs a systematic literature review on data aggregation workflows, in order to answer five questions: What are the projects? What are the planned steps? Which technologies are used? Are the steps performed manually, automatically, or semi‐automatically? Which perform semantic search? The searches were carried out in three databases: Networked Digital Library of Theses and Dissertations, Scopus and Web of Science. In Q01, 12 projects were selected. In Q02, 9 stages were identified: Harvesting, Ingestion, Mapping, Indexing, Storing, Monitoring, Enriching, Displaying, and Publishing LOD. In Q03, 19 different technologies were found it. In Q04, we identified that most of the solutions are semi‐automatic and, in Q05, that most of them perform a semantic search. The analysis of the workflows allowed us to identify that there is no consensus regarding the stages, their nomenclatures, and technologies, besides presenting superficial discussions. But it allowed to identify the main steps for the implementation of the aggregation of cultural data.

Suggested Citation

  • Joyce Siqueira & Dalton Lopes Martins, 2022. "Workflow models for aggregating cultural heritage data on the web: A systematic literature review," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(2), pages 204-224, February.
    • Handle: RePEc:bla:jinfst:v:73:y:2022:i:2:p:204-224
    DOI: 10.1002/asi.24498
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