Abstract
Many of nowadays organizations can be said to be knowledge-based. That is, they have relevant decision-making processes that are supported by data and data mining processes. These data may be created/collected by the organization or acquired from external sources (e.g. open data portals). In any case, the quality of the data will, ultimately, be one of the main drivers of decision quality. In this context, it is important that data-producing organizations also produce relevant meta-information characterizing the provenance of the data, its context or the representation standards used. This paper presents a framework to facilitate this process, promoting the inclusion of information concerning representation standards, provenance, trust and permissions at the data level. The main goal is to promote data usability and, consequently, its value for the organizations.
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Acknowledgement
This work is co-funded by Fundos Europeus Estruturais e de Investimento (FEEI) through Programa Operacional Regional Norte, in the scopre of project NORTE-01-0145-FEDER-023577.
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Carneiro, D., Vieira, A. (2019). A Framework to Improve Data Collection and Promote Usability. In: Novais, P., et al. Ambient Intelligence – Software and Applications –, 9th International Symposium on Ambient Intelligence. ISAmI2018 2018. Advances in Intelligent Systems and Computing, vol 806. Springer, Cham. https://doi.org/10.1007/978-3-030-01746-0_42
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DOI: https://doi.org/10.1007/978-3-030-01746-0_42
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