Good things come in small packages: A repository-based approach to the publication of "small data" Humanities and Cultural Heritage research objects
Creators: name: O'Donnell, Daniel
Publisher: name: Zenodo
Year: 2019

description: Shareable draft (submitted) to 2019 Partnership Development Grant programme. The challenge<br> Is smaller scale Humanities and Cultural Heritage (HCH) research missing out on the data revolution?<br> Can HCH research benefit from the same "big data" tools and approaches common in Science,<br> Technology, Engineering, and Medicine (STEM)? Can it do it without sacrificing traditional strengths in<br> the detailed analysis and curation typically focussed on individual cultural objects or small collections?<br> Can it do it while improving the ease and reducing the costs currently inherent in digital HCH<br> publication?<br> These are questions the "Good Things Come in Small Packages" partnership intends to answer. A<br> research and mobilisation project in the SSHRC research domains of Library and Information Science,<br> Archival Science, and Communications Technology, this partnership proposes a new approach to the<br> development and dissemination of HCH research using simple semantic web technologies that opens<br> traditional HCH research to the power of big data analytics without requiring a change in focus or scale.<br> Overall goal and objectives<br> The overall goal of this partnership is to prototype and mobilise a new approach to the development and<br> dissemination of primary source HCH research data and analyses on FAIR (Findable, Achievable,<br> Interoperable, and Reusable) principles. This builds on workflow, infrastructure, and tools originally<br> developed to support big data projects, particularly in STEM, but shows how they can be adapted to<br> support the often different interests, methods, and scale of typically much smaller HCH research<br> projects.<br> The result is a new type of research object and workflow that uses semantic web technologies to reduce<br> development, publication, and maintenance costs of digital HCH projects of any size while supporting<br> BOTH the intensive analysis and curation of cultural objects characteristic of HCH research AND the<br> organic development of larger machine-readable big data networks of cultural research through the use<br> of standard computer ontologies, persistent identifiers, and similar semantic technologies. This closes a<br> gap that currently exists between newer, big data approaches to HCH research and more traditional<br> small-scale approaches still widely characteristic of research in the domain.<br> Breadth of partnership and engagement of partner organisations<br> The proposed partnership consists of organisations that span the data cycle. These include important<br> Open Data repository projects (CERN/Zenodo and FRDR); developers of research tools (CNR-ISTI;<br> Textual Communities; Edition Visualisation Technology); pioneering Digital Humanities publishers and<br> developers (SEENET; Scholarly Digital Editions; Net7); and a number of HCH research projects.<br> The partnership allows its participants to leverage previous investments to promote a semantic approach<br> to the production and dissemination of digital HCH research. For the projects, it provides an opportunity<br> to improve their dissemination in an archivally responsible fashion. For the tool and platform<br> developers, it provides an opportunity to develop new use cases and improve interoperability and<br> impact. For the repository hosts, it provides guidance from an important end-user community. By<br> pooling expertise and working together, the partners produce an outcome that none could accomplish on<br> its own.