Open Government Data as Multi-dimensional 5 Star Data: cube.link

Michael Luggen, Benedikt Hitz, Julien Audiffren, Djellel Eddine Difallah, Jean-Luc Cochard, Philippe Cudré-Mauroux

Abstract: Many governments made commitments to publish data collected and created by taxpayers as Open Government Data (OGD). Yet, a common challenge is that data producers are not always end-users, leading to inefficiencies, gaps, and inconsistencies in how data is used and interpreted. OGD can originate from various sources and can sometimes be noisy. For instance, smart cities can produce fine-grained and precise data via sensor networks such as power grids or transportation networks, whereas data automatically extracted from government documents can be highly noisy. A common pattern, however, is that this data often describes spatiotemporal phenomena with multidimensional facets pertaining to real-world entities. Having a common ontology for such observations can help standardize their downstream usage. This paper describes the effort made by the Swiss Government to create an ecosystem that allows to publish open government data in a pragmatic and efficient manner while maintaining the goal of publishing high-quality data that are integrated and interoperable. The paper introduces the domain-independent ontology Cube Schema (https://cube.link), which is supported by open-source tools to publish, integrate, and validate diverse data sources, as well as multiple end-user tools for providing and visualizing data. With underlying statistics, we show the usage of these tools by both data providers and data consumers with several deployment use-cases.

External IDs:dblp:conf/semweb/LuggenHADCC25