Towards a Linked Data Publishing Methodology

Klein, Eduard; Gschwend, Adrian; Neuroni, Alessia (2016). Towards a Linked Data Publishing Methodology In: 2016 Conference for E-Democracy and Open Government (CeDEM 2016). Krems, Austria. 18-20 May 2016. 10.1109/CeDEM.2016.12

Text stamp.jsp_tp=&arnumber=7781923&tag=1 - Published Version Restricted to registered users only Available under License Publisher holds Copyright. Download (2kB) | Request a copy

Linked open government data (LOGD) can be a catalyst in the development of value-added services and products. The vision of many Linked Open Data (LOD) projects is to make publishing and reuse of linked data as easy as possible for the end user thanks to a thriving marketplace with data publishers, developers, and consumers along the value chain. In the large scale LOD project “Fusepool P3”, tourism-related applications and software components were developed that support data owners and open data enthusiasts in transforming legacy data to linked data. Based on experiences from this project, we present reflections and discuss pitfalls in drawing a linked data publishing methodology. An integrated view on all phases of the publishing process has not been described so far, for the technical phases linked data life-cycles have been identified only. The methodology deve loped enables stakeholders to transfer the lessons learned to other use cases and application contexts. This allows for better estimation of efforts and skills for future LOD projects.

Item Type:	Conference or Workshop Item (Paper)
Division/Institute:	Business School > Institute for Public Sector Transformation > Public Sector Innovation Business School
Name:	Klein, Eduard0000-0002-6860-5845; Gschwend, Adrian and Neuroni, Alessia0000-0003-2039-4388
ISBN:	9781467389341
Language:	English
Submitter:	Service Account
Date Deposited:	09 Aug 2019 11:43
Last Modified:	18 Dec 2020 13:28
Publisher DOI:	10.1109/CeDEM.2016.12
Related URLs:	Publication
Uncontrolled Keywords:	linked open data, data publishing, linked data life-cycle, publishing methodology, linked data platform
ARBOR DOI:	10.24451/arbor.7710
URI:	https://arbor.bfh.ch/id/eprint/7710