Data maturity project in High Value Nutrition (Phase 2) – National Science Challenge
Dr Dharani Sontam, Yvette Wharton, Professor Mark Gahegan, Centre for eResearch; Dr Simmon Hofstetter, Operations Manager, Professor Richard Mithen, Liggins Institute and Joanne Todd, Challenge Director, High Value Nutrition, National Science Challenge
About High-Value Nutrition Ko Ngā Kai Whai Painga
High-Value Nutrition Ko Ngā Kai Whai Painga (HVN) is one of 11 National Science Challenges the Ministry of Business, Innovation and Employment (MBIE) established to tackle New Zealand’s biggest issues and opportunities. It’s mission is “to grow the science excellence and knowledge New Zealand needs to create and deliver food to the world” by building a systems-level understanding of nutrition and health. The mission includes a focus on increasing export revenues from the country’s Food & Beverage sector.
Data maturity in HVN
Integration of multi-dimensional datasets and collaboration across multi-disciplinary and cross-institutional teams can only be achieved through a data management strategy that facilitates frictionless data sharing. Following an introductory workshop on data maturity delivered by the Centre for eResearch (CeR), the HVN Directorate identified an opportunity to review and raise data maturity within HVN.
We began our work with a situational analysis of current data management practices in the four priority research programmes (PRPs): Infant Health, Metabolic Health, Digestive Health and Immune Health. We consulted with researchers, research support staff, doctoral candidates, the Science Leadership Team (SLT) and the Directorate for their views, understanding and approach on data management and maturity. We adopted a modified version of CMMI institute’s data maturity framework (DMM) to assess the maturity level of the organisation along five themes:
- Data governance
- Data quality
- Data management
- Platforms and infrastructure
- Data operations
With the challenge’s data goals and its data management needs in mind, we crafted a proposal to streamline data management practices and raise the data maturity within the organisation.
We are currently in the execution phase following the acceptance of our proposal. This phase involves:
- Streamlining data management practices in HVN, which will be accomplished through creating standard operating procedures (SOPs), data ecosystem maps and data management plans (DMPs) tailored to the needs of the research projects.
- Creating a metadata catalogue for digital research data emerging from major projects in HVN.
We began our data management work with two projects chosen by the Directorate and the SLT, engaging with the project researchers and co-designing solutions to the data issues that arose from our discussions. We held regular workshops with the data champions – researchers and research support staff who are the points of contact for data at their respective institutions. During this process data flows were mapped, sample and file naming schema were agreed upon, data sharing tools and solutions were discussed, questions around data preservation and publication were raised and pain points in the data flows were identified. These meetings were also used to upskill researchers on research data management topics including FAIR (Findable, Accessible, Interoperable and Reusable), CARE (Collective benefit, Authority to control, Responsibility and Ethics), Māori data sovereignty principles, data publishing, and copyright. As a result, SOPs, data ecosystem maps and data management plans (DMPs) are now in place for the chosen projects.
We have also designed data management templates and guides to be disseminated across the wider HVN challenge (figure 1). The aim of these templates is to equip project research personnel with the knowledge and materials necessary to plan for their research data throughout its lifecycle. The second arm of our work involves the creation of a metadata catalogue for digital research data, for projects in HVN. Metadata is structured information that makes it easier to locate, retrieve, understand and use specific data. It plays a vital role in making research data FAIR. The metadata catalogue will be a searchable record of descriptive information about the projects and datasets in HVN. As with the data maturity work, this will begin with consultations with all the key research personnel and relevant stakeholders to understand their requirements. Currently, consultation has begun to develop the requirements, standards and identification of a suitable place to host the metadata. Our data maturity work’s overarching aim is to make digital research data generated in HVN be FAIR and CARE compliant where feasible. We support HVN in their efforts to realise the maximum value from their research, now and in the future.
Figure 1. Research data management planning flowchart. The chart is visual guide and sets out research data requirements and processes that need to be discussed and documented so that data is managed appropriately throughout its lifecycle.
