The data enrichment process is implemented by specifying, deploying, and executing data enrichment pipelines over data that can be structured, semi-structured and unstructured, in large amounts, and from static or streaming sources. While techniques exist to cover different enrichment operations such as data cleaning, linking, feature extraction, classification and semantic annotation, etc., the lack of comprehensive approaches and established tools dedicated to data enrichment makes the definition, implementation, and operation of enrichment pipelines difficult for too many organizations willing to improve their BDA and AI applications. The overall vision of the enRichMyData project is to create a novel paradigm for building rich, high-quality, valuable, and FAIR-compliant datasets to feed downstream BDA and AI applications in the context of data-sharing ecosystems, such as data spaces. The paradigm facilitates the specification and execution of data enrichment pipelines, focusing on supporting various data enrichment operations. enRichMyData makes this easily accessible to a wide set of large and small organizations that encounter difficulties in delivering suitable data to feed their BDA and AI solutions due to the lack of usable tools/expertise for the cost-effective management of data enrichment pipelines.
Project Duration: 36 months
Period: Oct 2022 – May 2025
Type of Funding: HORIZON-CL4-2021-DATA-01-03
