In the last decade, open data production related to Public Sector is quickly increased due to different factors, in particular: EU Open Data Directive fostered the openness of specific typology of datasets from the Public Sector (i.e. High Value Datasets); the improvement of the smart city paradigms (e.g. IoT deployments, digital twins) has dramatically improved the production of city-related data accessible by citizens; private companies are more and more contributing to public sector/utilities data availability used by citizens in their everyday life. Anyway, actual data use by third-party services still remains a challenge; a lot of data produced by public authorities, even “officially open”, is still not discoverable or is accessible only by humans, in a heterogeneous format not machine-readable. Moreover, there is no quality control of the data that prevents its use in value-added services, particularly those AI enhanced.
In this context, BeOpen aims at providing a holistic framework to support open data and metadata life cycle management pipelines aimed at accessing, curating and publishing HVDs, based on the FAIR principles, to be made available for future Data Spaces supporting sustainable city domain.
The framework will include open source tools, replicable pipeline and ontologies, and best practices to perform data collection, curation, semantic annotation, data and metadata harmonization, improve quality and publish in machine- readable format (in bulk or via APIs) HVDs, particularly related to: statistics, mobility, environmental, earth observation and geo-spatial.
MKLab is responsible for the implementation of multiple technical aspects of the BeOpen project having various tasks in 5 WPs that deal with:
BeOpen framework will be tested and validated on the field through 8 use cases across Europe. The use case of MKLab in collaboration with NOA aims to make available machine-readable HVD related to natural disasters and the urban environment for Attica region validating the APIs to access and reuse them.