Uncovering Hidden Data Assets through Smart Discovery

The Dataset Search Engine from MISSION KI unlocks Dark Data: a modular open-source system (MIT license, proof-of-concept) that makes distributed data repositories searchable without migration. At its core is the Extended Dataset Profile Service (EDPS), which automatically creates quality profiles directly at the source. Following the compute-to-data principle, sensitive data remains protected within its original environment. This makes hidden data assets visible, assessable, and accessible for AI applications for the first time.

→ Projektdetails and GitHub-Repository: LINK

What to expect in this webinar:

• Live "under the hood" demonstration: Experience how federated search aggregates datasets from different ecosystems on a single interface, making them comparable. We'll showcase the architecture, APIs, and integration processes.

• Quality at first glance: Understand how the EDPS automatically creates detailed profiles, enabling you to make informed assessments of data quality before accessing it.

• Making your data discoverable: We'll show you how to use the search capabilities for your work today and outline the steps needed to prepare your own datasets for federated discovery. You'll receive access to the code and documentation for your own testing.

Target audience: Anyone involved in data discovery and assessment, from data scientists and open data teams to project leaders in smart city initiatives. Also decision-makers and professionals without technical backgrounds who want to understand how modern data discovery works.

Register now and discover how to implement the Data Act in practice!

This event is part of the webinar series:

Jeder Community Call bietet Ihnen:

• Live-Demos & Use Cases – Sehen Sie die Tools in Aktion

• Open Source zum Mitmachen – Lösungen frei verfügbar und anpassbar

• Praxisnaher Austausch – Diskutieren Sie mit Entwickler:innen und Anwender:innen

Jetzt anmelden und entdecken, wie Sie Dark Data sichtbar, nutzbar und wertvoll machen.