Open Government Data: A Data Analytics Approach

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Abstract:

In December 2010 the International Open Government Dataset Search (IOGDS) team at the Tetherless World Constellation at Rensselaer Polytechnic Institute embarked on a project to discover, document and analyze open data catalogs published by governments at various levels around the world. By early 2013 the IODGS project had accumulated descriptive metadata for over 1,022,787 datasets from 192 catalogs in 24 languages, representing 43 countries and international organizations. RPI's aggregate catalog, implemented in RDF and published using both a public SPARQL endpoint and a faceted user interface, has proven to be a valuable tool for gaining insight into the nature of open government data publication. In this article we discuss what our team has learned about international government data publication trends and tendencies through the application of data analytics and data visualization to this metadata collection.

Related Projects:

DCO-DS LogoLinking Open Government Data (LOGD)
Principal Investigator: Deborah L. McGuinness and Jim Hendler
Description: The LOGD project investigates the role of Semantic Web technologies, especially Linked Data, in producing, enhancing and utilizing government data published on Data.gov and other websites.

Related Research Areas:

Data Science
Lead Professor: Peter Fox
Description: Science has fully entered a new mode of operation. Data science is advancing inductive conduct of science driven by the greater volumes, complexity and heterogeneity of data being made available over the Internet. Data science combines of aspects of data management, library science, computer science, and physical science using supporting cyberinfrastructure and information technology. As such it is changing the way all of these disciplines do both their individual and collaborative work.

Data science is helping scienists face new global problems of a magnitude, complexity and interdisciplinary nature whose progress is presently limited by lack of available tools and a fully trained and agile workforce.

At present, there is a lack formal training in the key cognitive and skill areas that would enable graduates to become key participants in escience collaborations. The need is to teach key methodologies in application areas based on real research experience and build a skill-set.

At the heart of this new way of doing science, especially experimental and observational science but also increasingly computational science, is the generation of data.

Concepts:
Web Science
Lead Professor: Jim Hendler, Deborah L. McGuinness
Description: Web Science is the study of the World Wide Web and its impact on both society and technology, positioning the Web as an object of scientific study unto itself. Web Science recognizes the Web as a transformational, disruptive technology; its practitioners study the Web, its components, facets and characteristics. Ultimately, Web Science is about understanding the Web and anticipating how it might evolve in the future.
Concepts: Semantic Web