DiSHACLed
Jeroen Wouters
The DiSHACLed project aims to enhance data governance efficiency within the European data ecosystem by leveraging the Shapes Constraints Language (SHACL). The project focuses on three key data governance tasks: dataset discovery, interoperable tooling, and automated form generation. Flanders, a front-runner in adopting SHACL, provides a unique testing ground for these innovations.

The European Data Governance Act (DGA) seeks to promote fair and equitable data usage, enhance trust in data sharing, and establish a framework for data governance within the EU. Flanders, with its OSLO programme defining over 134 ratified semantic standards, is well-positioned to address data governance challenges through Linked Data technologies.

##Project Goals:
1. Data Discovery: Develop an algorithm for efficient dataset discovery using SHACL shapes, reducing discovery time from days to seconds. This will be piloted in at least two data portals, targeting a discovery rate of 20 datasets per second.
2. Interoperable Tooling: Create an automation strategy for connecting different data processors across project partners Sirus, Inuits, and Redpencil. This involves developing a shared specification for interoperable workflows, allowing seamless data integration and processing.
3. Automated Form Generation: Generate web forms for data collection automatically using SHACL shapes. This aims to cover 80% of existing data types, significantly reducing the manual effort required for form creation.

The project will culminate in a proof-of-concept map displaying traffic measurements across Flanders, showcasing the automated selection and integration of datasets based on SHACL shapes. This demonstrator will highlight the efficiency and scalability of the developed solutions. During this talk, we will go over the project goals in detail and explain the methodologies and strategies we are employing to achieve these research objectives. We will also discuss the specific technical challenges we face and how we will overcome them, providing a comprehensive overview of our approach and findings.
information technology for dp from document to data