19 March 2024

Heritage Data Practices & Decentralisation

Discovery Project Webinar, March 19

This Towards a National Collection (TaNC) webinar will focus on navigating responsible data practices and decentralization in digital cultural heritage, bringing together researchers from two of our Discovery Projects, The Congruence Engine and The Sloane Lab.

  • Foteini Valeonti, University College London: Decentralising Digital Humanities
  • Anna-Maria Sichani, University of London: From collections-as-data to responsible data: data-driven approaches and ethics in digital cultural heritage

The webinar will begin with Foteini Valeonti, discussing a synthesis of web3-related technologies for digital humanities infrastructures, exploring opportunities of decentralisation and open access data storage, as well as associated risks and challenges. Anna-Maria Sichani will talk about data-related infrastructure requirements in cultural heritage institutions, exploring data-specific issues, from legacy and inconsistent datasets’ descriptions, resistance to standardisation to hidden bias and positionality in various data-related processes.


Full abstracts

Foteini Valeonti: Decentralising Digital Humanities

Advancements in Internet technology greatly influence digital humanities, yet research investigating "web3" and blockchain-based technologies within the domain remains limited. This presentation will examine decentralised technologies in relation to digital humanities infrastructures, exploring opportunities, as well as risks and challenges.

Anna-Maria Sichani: From collections-as-data to responsible data: data-driven approaches and ethics in digital cultural heritage

This presentation will focus on aspects of my research at the Congruence Engine on exploring, assessing and developing data-related infrastructure requirements for cultural heritage institutions. I will focus on the development of a sector-specific assessment framework for digital cataloguing practices in UK cultural heritage institutions and a positionality-aware methodology for the entire datasets’ lifecycle in data/AI-driven approaches, from production, documentation, management, ethics, and reuse of cultural heritage datasets. Through the development of responsible datasets and responsible operations at every point of data handling, we commit to an ethical approach, transparency, and reproducibility throughout our digital endeavours, as we embark towards a national collection of the industrial past.

Webinar Discovery Projects