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Is the LOD cloud at risk of becoming a museum for datasets? Looking ahead towards a fully collaborative and sustainable LOD cloud

Debattista, Jeremy orcid logoORCID: 0000-0002-5592-8936, Attard, Judie orcid logoORCID: 0000-0001-7507-1864, Brennan, Rob orcid logoORCID: 0000-0001-8236-362X and O’Sullivan, Declan orcid logoORCID: 0000-0003-1090-3548 (2019) Is the LOD cloud at risk of becoming a museum for datasets? Looking ahead towards a fully collaborative and sustainable LOD cloud. In: Linked Data on the Web and its Relationship with Distributed Ledgers, 13-17 May 2019, San Francisco, USA. ISBN 978-1-4503-6675-5

The Linked Open Data (LOD) cloud has been around since 2007. Throughout the years, this prominent depiction served as the epitome for Linked Data and acted as a starting point for many. In this article we perform a number of experiments on the dataset metadata provided by the LOD cloud, in order to understand better whether the current visualised datasets are accessible and with an open license. Furthermore, we perform quality assessment of 17 metrics over accessible datasets that are part of the LOD cloud. These experiments were compared with previous experiments performed on older versions of the LOD cloud. The results showed that there was no improvement on previously identified problems. Based on our findings, we therefore propose a strategy and architecture for a potential collaborative and sustainable LOD cloud
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:Linked Data; LOD cloud; metadata quality; data quality; sustainable service
Subjects:Computer Science > World Wide Web
DCU Faculties and Centres:UNSPECIFIED
Published in: WWW '19: Companion Proceedings of The 2019 World Wide Web Conference. . Association for Computing Machinery (ACM). ISBN 978-1-4503-6675-5
Publisher:Association for Computing Machinery (ACM)
Official URL:http://dx.doi.org/10.1145/3308560.3317075
Copyright Information:© 2019 The Authors. CC-BY 4.0
Funders:Irish Research Council Government of Ireland Postdoctoral Fellowship [project ID GOIPD/2017/1204, Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie (EDGE) [grant agreement no. 713567], Science Foundation Ireland and co-funded by the European Regional Development Fund through the ADAPT Centre for Digital Content Technology [grant number 13/RC/2106].
ID Code:24657
Deposited On:19 Jun 2020 12:59 by Vidatum Academic . Last Modified 19 Jun 2020 12:59

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