Methodological Guidelines for Publishing Library Data as Linked Data
| Autor: | Andrés Tello, Yusniel Hidalgo-Delgado, Bin Xu, Boris Villazon-Terrazas, Reina Estrada-Nelson, Amed Leiva-Mederos |
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| Rok vydání: | 2017 |
| Předmět: |
Data cleansing
Computer science business.industry 05 social sciences Interoperability 02 engineering and technology Linked data computer.file_format computer.software_genre Data science Discoverability Metadata Publishing 020204 information systems 0202 electrical engineering electronic engineering information engineering 0501 psychology and cognitive sciences RDF business computer Semantic Web 050104 developmental & child psychology |
| Zdroj: | 2017 International Conference on Information Systems and Computer Science (INCISCOS). |
| DOI: | 10.1109/inciscos.2017.17 |
| Popis: | Publishing data as Linked Data increases the interoperability and discoverability of resources over the web space. This process involves several design decisions and technologies. However, there is no one-size-fits-all formula for publishing data as Linked Data. Also, the quality of linked data published is a key issue to take into account. In the library domain, the quality of linked data is a crucial point for improving the retrieval and use of the data. In this paper, we propose a set of methodological guidelines based on five activities for publishing library data as Linked Data. The proposed guidelines consider the quality of published data as a key issue. In this line, our approach includes a preprocessing task for data cleansing and normalization. The proposed approach has been applied in a use case for publishing bibliographic data from Open Access journals in Cuba. The results obtained show the applicability of the methodological guidelines proposed in a real environment. |
| Databáze: | OpenAIRE |
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