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Using Open Data to Support Organizational Capabilities in Dynamic Business Contexts
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2018 (English)In: Advanced Information Systems Engineering Workshops: CAiSE 2018: Proceedings / [ed] Raimundas Matulevičius, Remco Dijkman, Springer, 2018, p. 28-39Conference paper, Published paper (Refereed)
Abstract [en]

In essence, Open Data (OD) is the information available in a machine-readable format and without restrictions on the permissions for using or distributing it. Open Data may include textual artifacts, or non-textual, such as images, maps, scientific formulas, and other. The data can be publicized and maintained by different entities, both public and private. The data are often federated, meaning that various data sources are aggregated in data sets at a single “online” location. Despite its power to distribute free knowledge, OD initiatives face some important challenges related to its growth. In this paper, we consider one of them, namely, the business and technical concerns of OD clients that would make them able to utilize Open Data in their enterprise information systems and thus benefit in terms of improvements of their service and products in continuous and sustainable ways. Formally, we describe these concerns by means of high-level requirements and guidelines for development and run-time monitoring of IT-supported business capabilities, which should be able to consume Open Data, as well as able to adjust when the data updates based on a situational change. We illustrated our theoretical proposal by applying it on the service concerning regional roads maintenance in Latvia.

Place, publisher, year, edition, pages
Springer, 2018. p. 28-39
Series
Lecture Notes in Business Information Processing, ISSN 1865-1348, E-ISSN 1865-1356 ; 316
Keywords [en]
Open Data, Capability, Context, Requirements, CDD
Keywords [sv]
verksamhetsmodellering, open data
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-158960DOI: 10.1007/978-3-319-92898-2_3ISBN: 978-3-319-92897-5 (print)ISBN: 978-3-319-92898-2 (electronic)OAI: oai:DiVA.org:su-158960DiVA, id: diva2:1240073
Conference
CAiSE 2018 International Workshops, Tallinn, Estonia, June 11-15, 2018
Available from: 2018-08-20 Created: 2018-08-20 Last updated: 2018-09-17Bibliographically approved

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