Open Datasets provide one of the most popular ways to acquire insight and information about individuals, organizations and multiple streams of knowledge. Exploring Open Datasets by applying comprehensive and rigorous techniques for data processing can provide the ground for innovation and value for everyone if the data are handled in a legal and controlled way. In this study, authors propose an argumentation and abductive reasoning approach for data processing which is based on the data quality background.
Tag: QOD 2018
Open Government Data are valuable initiatives in favour of transparency, accountability, and openness. The expectation is to increase participation by engaging citizens, non-profit organisations, and companies in reusing Open Data (OD). A potential barrier in the exploitation of OD and engagement of the target audience is the low quality of available datasets.
Researchers publish papers to report their research results and, thus, contribute to a steadily growing corpus of knowledge. To not unintentionally repeat research and studies, researchers need to be aware of the existing corpus. For this purpose, they crawl digital libraries and conduct systematic literature reviews to summarize existing knowledge.
In this paper authors presents a new way to evaluate geospatial data quality using Semantic technologies. In contrast to non-semantic approaches to evaluate data quality, Semantic technologies allow them to model situations in which geospatial data may be used and to apply costumized geospatial data quality models using reasoning algorithms on a broad scale.
This paper introduces the ADEQUATe project—a platform to improve the quality of open data in a community-driven fashion. First, the context of the project is discussed: the issue of quality of open data, its relevance in Austria and how ADEQUATe attempts to tackle these matters.
