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Build and Train for a Data - Intensive Future

Speakers
Mr Paul Wong, Mr Keith Russell

Australian Research Data Commons

Abstract
Data-intensive research is rapidly growing as a methodology in academic research, business and informing policy decisions. Yet we urgently need to improve the technical infrastructure supporting the discovery and reuse of research data. Often weeks or months of specialist technical effort is needed

to gather the data necessary to answer research questions. This is not because we lack appropriate technology, it is because we do not pay our valuable digital objects the careful attention they deserve. To help address this problem, in 2016 the FAIR Guiding Principles for scientific data management and stewardship were published in Nature’s Scientific Data as guidelines to improve the findability, accessibility, interoperability, and reuse of digital assets. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles also address the ability of machines to automatically find and use data.

The Principles have received worldwide recognition as a framework for providing a range of benefits to researchers, research communities, research infrastructure facilities and research organisations. While they are easy to agree with, in practice they are not easy for a researcher on their own to implement. Researchers need technical infrastructure to support them in preparing their data along with skills that will enable them to maximise the value of the FAIR infrastructure investment.

The Australian Research Data Commons (ARDC) has been leading and supporting the Australian research sector to implement changes that support FAIR. In this talk, we will discuss how we have developed and supported infrastructure that enables FAIR data across the research sector. This includes building the skills required amongst so ware engineers, infrastructure development project teams and librarians. We have for example worked on a Biosciences platform to assess their infrastructure and make changes to enable FAIR data; we have developed and delivered FAIR data and so ware skills workshops, webinars, resources and we have partnered with global organisations in a global sprint to develop discipline specific FAIR resources.