Humanities Data Inquiry

Humanities Data Inquiry (HDI) is a Social Science and Humanities Research-Council (SSHRC)-funded community of practice and network of projects and laboratories dedicated to understanding the role of data in traditional humanities research and publication workflows.

A premise of the project is that Humanities researchers understands and uses what other disciplines call data in (at times) fundamentally different ways from that found in those other disciplines: it is (often) produced through argument rather than experimentation and, as Christine Borgman argues, the definition of data is often a valuable act of Humanities research in its own right.

THE CHALLENGE

The last decade has seen great advances in the development of infrastructure, tools, and principles for the collection, storage, discovery, and dissemination of research data. Governments, funders, libraries and consortia, and private corporations have made large investments in what is rapidly becoming a robust Open and FAIR (Finadable, Accessible, Interoperable, and Reusable) research data ecosystem.

This ecosystem, however, was built largely with the needs of “Big Data” Science, Technology, Engineering, and Mathematics (STEM) in mind. While Humanities and Cultural Heritage (HCH) researchers and projects are encouraged to engage with it (including in the instructions to this grant), the fit is often quite poor. Where Big Data STEM typically involves large datasets produced through experiment, observation, or analysis, “Small Data” HCH research often involves the deep analysis and intensive curation of very small data sets focussed primarily on representation. While such projects can benefit from the thoughtful adoption and adaptation of Open and FAIR architecture and principles — particularly when it comes to ensuring long-term support, dissemination, and impact — this adaptation requires community engagement and input: thoughtful and bidirectional communication among grass-roots researchers and the organisations responsible for creating and supporting the Open and FAIR ecosystem.

OVERALL GOAL AND SPECIFIC OBJECTIVES

The goal of this project is to promote that engagement — to establish a Community of Practice (CoP) that will bring together individuals, projects, and organisations interested in the adaptation of Open and FAIR infrastructure and principles to the needs of the HCH research community and encouraging their adoption where appropriate by individual researchers and projects. More specifically, we intend to

• DISCOVER: Establish a Working Group that brings together HCH researchers and projects with Open and FAIR advocacy and support organisations in order to understand Open and FAIR HCH Research Data Management (RDM);
• DEMONSTRATE: Develop leadership within the HCH community by supporting collaboration among data-centric HCH research projects on common FAIR RDM problems; and
• MOBILISE: Promote knowledge of Open and FAIR RDM principles and infrastructure through annual workshops, conference sessions, and summer schools.

BREADTH OF PARTNERSHIP

The initial project team includes leaders in international HCH and data research, standards, and infrastructure representing a number of important national and international societies, research projects, standards, and infrastructure organisations including the Text Encoding Initiative, Research Data Alliance, DARIAH, OpenAire, Force11, and Portage/FRDR. From this initial core, we anticipate expanding relatively quickly to incorporate a number of other major initiatives in North and South America, Europe, and Japan.

The important thing about this project, however, is the opportunity it provides for these organisations to engage reciprocally with the HCH research community. The goal is to assist HCH researchers in learning about Open and FAIR principles and help our partners understand how this community can be better served by their infrastructure, policies, and tools. The individual team members have extensive experience in building such communities, including in several cases with previous SSHRC funding.

SCHOLARLY BENEFITS

• ENHANCED RESEARCH METHODS: The thoughtful adaptation of Open and FAIR RDM principles and infrastructure represent a new approach to the management of HCH research data and, in as much as they makes use of standardised reference and identification systems and permanent, professionally maintained repository systems, offer to greatly improve the survivability and long-term impact of HCH data (DISCOVER).
• ENHANCED COLLABORATION: The overall goal of this project is to create a Community of Practice to promote grass-roots awareness and development of Open and FAIR research practices. Our specific activities — developing a Working/Special Interest Group (DISCOVER), promoting and supporting inter-project collaboration and sharing of resources (DEMONSTRATE), and creating and delivering workshops and summer schools for the dissemination of the resulting best practice (MOBILISE) are all intended to promote new collaboration among HCH researchers and projects and between the HCH research community and the organisations responsible for developing and supporting Open and FAIR RDM.

SOCIAL BENEFITS

• ENRICHED PUBLIC DISCOURSE: The protection and preservation of Cultural Research Data is an intrinsic good that helps enrich public discourse. This is true even for data — such as that created by and for Indigenous communities — for which a STEM-oriented approach to Open RDM is inappropriate. Community focussed data-centric HCH projects have traditionally faced the same hurdles with regard to management, dissemination, and maintenance. Ensuring that such projects are able to serve their communities for the foreseeable future while reducing the overall costs is an important public benefit (DISCOVER).
• CULTURAL OUTCOMES: Ensuring that HCH research data is Findable, Accessible, Interoperable, and Reusable — whether this means to the world at large or to a specific community — is an important cultural outcome: a project that goes dark because its infrastructure is unsustainable is a project that is failing in its obligation to ensure that community members have access to and benefit from their cultural heritage. By encouraging HCH projects to improve their RDM and ensure that cultural data remains available and accessible, this project will significantly improve the ability of HCH researchers to give back to their communities (DEMONSTRATE).
• TECHNOLOGICAL OUTCOMES: Current Open and FAIR infrastructure has been designed largely to suit the needs of researchers working with “Big Data” in Science, Technology, Engineering, and Mathematics. By creating the conditions for dialogue between “Small Data” HCH researchers and Open and FAIR organisations, this project will improve the technological practice of both the HCH researchers and the Open and FAIR organisations (DISCOVER/MOBILISE).