Finding and analysing energy research funding data: The EnArgus system

Leif Oppermann,Simon Hirzel, Alexander Güldner,Karoline Heiwolt, Joachim Krassowski, Ulrich Schade,Christoph Lange,Wolfgang Prinz

Energy and AI(2021)

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摘要
Abstract This paper presents the concept, a system-overview, and the evaluation of EnArgus, the central information system for energy research funding in Germany. Initiated by the German Federal Ministry for Economic Affairs and Energy (BMWi), EnArgus establishes a one-stop information system about all recent and ongoing energy research funding projects in Germany. Participants ranging from laypersons to experts were surveyed in three workshops to evaluate both the public and expert interfaces of the EnArgus system in comparison to peer systems. The results showed that the EnArgus system was predominantly evaluated positively by the various participants. It contributes to making the energy sector more transparent and offers clear advantages for professional use compared to similar systems. The system’s semantic processing enables more precise hits and better coverage by including semantically related terms in search results; its intelligence makes it fail-safe, rendering it suitable for areas where poor results can have dire consequences. Reporting on an actual real-world system, the paper also provides a roadmap-view of how electronic filing of administrative project data can be semantically enhanced and opened-up to provide the basis for new ways into the data that are key for future breakthrough AI interfaces.
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关键词
Energiewende,Information System,Wiki,Ontology,Databases,Evaluation
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