We are very pleased to announce that our group got a paper accepted for presentation at ICEGOV (International Conference on Theory and Practice of Electronic Governance). ICEGOV stands for International Conference on Theory and Practice of Electronic Governance. Established in 2007, the conference runs annually and is coordinated by the United Nations University Operating Unit on Policy-Driven Electronic Governance (UNU-EGOV). Part of the United Nations University and headquartered in the city of Guimarães, north of Portugal, UNU-EGOV is a think tank dedicated to Electronic Governance; a core centre of research, advisory services and training; a bridge between research and public policies; an innovation enhancer; a solid partner within the UN system and its Member States with a particular focus on sustainable development, social inclusion and active citizenship.
Here is the pre-print of the accepted papers with its abstract:
- “Cross-Administration Comparative Analysis of Open Fiscal Data” by Fathoni A. Musyaffa, Jens Lehmann, Hajira Jabeen.
Abstract: To improve governance accountability, public administrations are increasingly publishing their open data, which includes budget and spending data. Analyzing these datasets requires both domain and technical expertise. In civil communities, these technical and domain expertise are often not available. Hence, despite the increasing size of the open fiscal datasets being published, the level of analytics done on top of these datasets is still limited. Providentially, the developments in the computer science community enable further progress in data analysis in different domains, such as performing a comparative analysis of open budgets and spending data (open fiscal data). This is done by adopting and applying semantics on open fiscal data. In this paper, we demonstrate the feasibility of comparative analysis over linked open fiscal data and devise an approach to perform comparative analysis across from different public administrations. Open fiscal data are cleaned, analyzed, transformed (i.e., semantically lied), and have their related concept labels connected across different public administrations so budget/spending items from related concepts can be queried. Additionally, the growing information on linked open data (e.g., DBpedia) can also be used to provide additional context to the analysis and the query.
Update: The paper has received a best paper award nomination.