Curation After the Fact: Practical and Ethical Challenges of Archiving Legacy Evaluation Data

Abstract

Over a 12-year period, the Atlantic Philanthropies invested more than €127m in agencies and community groups, running 52 prevention and early intervention (PEI) programmes and services in the children and youth sector throughout Ireland. As a condition of this funding, each PEI programme was evaluated by a university-based research team, resulting in a substantial collection of metric and qualitative information about ways to improve the lives of vulnerable Irish families. In 2016, the Atlantic Philanthropies funded the Prevention and Early Intervention Research Initiative at the Children’s Research Network of Ireland and Northern Ireland (hereafter, the Initiative) to gather, prepare and share this evaluation data through the public data archives.

The Initiative faces several challenges in its objective to archive this extensive collection of legacy data, and this paper will present two of the more salient challenges: how to share this data so that it is both (1) meaningful and (2) ethical. The paper pays particular attention to the challenges of safely sharing evaluation data through anonymisation and restricted access conditions; and also, the practical and ethical challenges of retroactively preparing these datasets for the archive.

A series of publicly available documents that guide each stage of the Initiative are in development, and are emerging as a key output. This paper will describe two pivotal documents, namely the CRN-PEI Guiding Principles, and the CRN-PEI Protocols for preparing and archiving evaluation data. The CRN-PEI Guiding Principles outline the key legal and ethical obligations of archiving this legacy evaluation data, and act as moral compass to steer our progress through these uncharted waters. The CRN-PEI Protocols define the standards for how data included in the Initiative is prepared for deposition in the public data archives, so they are easily located, interpretable and comparable in the long term. This protocol is based upon best practice documentation from a number of international sources and our primary aim is to generate ‘safe, useful data’ (Elliot at al., 2016).