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Wolfcon 2026 Details and Topics of Interest to Data Analysts

Wolfcon 2026 Details and Topics of Interest to Data Analysts

Conference: WOLFcon (World Open Library Foundation Conference) 2026


Dates: August 31 – September 3, 2026. The conference includes presentations, workshops, community discussions, and project meetings for the Open Library Foundation's open-source library communities.

Location: Prague University of Economics and Business, Prague, Czech Republic.

Registration:

  • Registration is open.

  • An early-bird discounted rate is available through July 28, 2026.

Accommodations:

  • Attendees are expected to arrange their own lodging; organizers indicated recommended accommodation information may be provided separately.

Pre-conference Workshops:

  • Held in person only on Monday, August 31, 2026.

Pre-Conference Training & Presentation Topics Likely of Interest to Data Analysts

WOLFcon focuses heavily on open-source library platforms (especially FOLIO and other Open Library Foundation projects), so the most relevant topics for a data analyst would include:

Pre-Conference Training Areas

  • Library analytics and reporting in FOLIO

  • Working with FOLIO data structures and APIs

  • Open-source data integration and interoperability

  • Metadata analytics and quality assessment

  • Assessment and usage-statistics reporting

  • Data extraction and transformation from library platforms

  • Business intelligence tools for library operations

  • Consortial and cross-institutional data analysis

  • Electronic resource and collection analytics

  • Open-source infrastructure and data governance

These topics align with WOLFcon's emphasis on open-source library technology, collaboration, and operational data.

Presentation Topics Worth Attending as a Data Analyst

Look for sessions covering:

  • Analytics dashboards and visualization

  • Library KPIs and performance measurement

  • Data-driven collection management

  • Usage, circulation, and resource-sharing analytics

  • Assessment of electronic-resource usage

  • Metadata quality metrics

  • Linked data and knowledge graphs

  • Data governance and stewardship

  • AI/ML applications in library systems

  • Open-source reporting frameworks

  • Data migration and system modernization

  • Research data management

  • Consortial reporting and benchmarking

  • Open-access and repository analytics

  • API-based integrations and data pipelines