Copy the page URI to the clipboard
d'Aquin, Mathieu; Adamou, Alessandro; Daga, Enrico; Liu, Shuangyan; Thomas, Keerthi and Motta, Enrico
(2014).
URL: http://ceur-ws.org/Vol-1280/paper8.pdf
Abstract
In this paper, we present the data curation approach taken by the MK:Smart project, creating a large data repository of datasets about all aspects of the city of Milton Keynes in the UK and its citizens. The issues faced here, which we believe will become more and more common to large, data-centric smart-cities initiatives, is the one associated with the diversity of these thousands of datasets in terms of the licenses, policies and terms they are associated with them. We describe this repository of datasets, the MK Datahub, and its architecture to create data workflows from original sources to applications. We focus on the approach taken to record, in a structured, ontology-based way the components of the licenses and policies of each dataset, as well as the tools we are developing to manage such representations and to reason with them.
Viewing alternatives
Download history
Item Actions
Export
About
- Item ORO ID
- 42047
- Item Type
- Conference or Workshop Item
- ISSN
- 1613-0073
- Project Funding Details
-
Funded Project Name Project ID Funding Body MK:SMART, an integrated innovation and training programme leveraging large-scale city data to drive economic growth (Q-13-037-EM) H04 HEFCE - Extra Information
- collocated with the 13th International Semantic Web Conference (ISWC 2014), Riva del Garda, Italy, October 19, 2014.
- Keywords
- smart cities; linked data; data curation; ODR; smart-city
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Research Group
- Centre for Research in Computing (CRC)
- Copyright Holders
- © 2014 The Authors
- Related URLs
- Depositing User
- Alessandro Adamou