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.
Page 2 of 5
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.
Today׳s supply chain professionals are inundated with data, motivating new ways of thinking about how data are produced, organized, and analyzed. This has provided an impetus for organizations to adopt and perfect data analytic functions (e.g. data science, predictive analytics, and big data) in order to enhance supply chain processes and, ultimately, performance.
Open Data (OD) is one of the most discussed issue of Big Data which raised the joint interest of public institutions, citizens and private companies since 2009. However, the massive amount of freely available data has not yet brought the expected effects: as of today, there is no application that has fully exploited the potential provided by large and distributed information sources in a non-trivial way, nor any service has substantially changed for the better the lives of people.
Wikipedia is considered as the largest knowledge repository in the history of humanity and plays a crucial role in modern daily life. Assigning the correct quality class to Wikipedia articles is an important task in order to provide guidance for both authors and readers of Wikipedia. The manual review cannot cope with the editing speed of Wikipedia.
The DBpedia project is a community effort to extract structured information from Wikipedia and to make this information accessible on the Web. The resulting DBpedia knowledge base currently describes over 2.6 million entities. For each of these entities, DBpedia defines a globally unique identifier that can be dereferenced over the Web into a rich RDF description of the entity, including human-readable definitions in 30 languages, relationships to other resources, classifications in four concept hierarchies, various facts as well as data-level links to other Web data sources describing the entity.
The opportunities of open data have been recently recognized among companies in different domains. Digital service providers have increasingly been interested in the possibilities of innovating new ideas and services around open data. Digital service ecosystems provide several advantages for service developers, enabling the service co-innovation and co-creation among ecosystem members utilizing and sharing common assets and knowledge.
Public procurement is an area that could largely benefit from linked open data technology. The respective use case of the LOD2 project covered several aspects of applying linked data on public contracts: ontological modeling of relevant concepts (Public Contracts Ontology), data extraction from existing semi-structured and structured sources, support for matchmaking the demand and supply on the procurement market, and aggregate analytics.
