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Research digital skills training 2021

Research Data

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The University defines research data as the evidence that underpins the answer to a research question and can be used to validate findings regardless of its form (e.g., print, digital, or physical). It may include anything created, collected, and/or generated in the course of research e.g., interview transcripts, maps, photos, sound recordings, observations, field notes, instrument data, clinical results, etc. Managing research data enables collaboration, and stewardship and governance, including adherence to funder, ethics, sovereignty and legal considerations, before, during and after the project. It also increases research impact by supporting data sharing and research integrity through enabling reproducibility and the FAIR data principles. Effective 1st July 2023, the University is introducing a new Research Data Management Policy. The Centre for eResearch works with Connect Digital Services and Libraries and Learning Services to develop and promote research data services and support across the University research community.

Research Data Management

The term research data encompasses the entire gamut of output generated by research at the University of Auckland. It may include anything created, collected, and/or generated in the course of research. RDM services facilitate the discovery, access, and reuse of research data. Proper leverage of RDM supports collaboration and enhances research impact. Additionally, funding bodies are increasingly requiring researchers to explicitly state their RDM approach in the form of data management plans (DMPs). The Centre for eResearch is working with both the Libraries and Learning Services, and IT Services to develop and promote the RDM knowledge and tools necessary to produce rigorous, high-impact research.


Data Transfer

The Centre for eResearch offers support for using Globus for high speed data transfer between University research drives and external locations within New Zealand, such as NeSI. While it is possible to use this service to collaborate internationally, additional set up is required.We can also offer consultations to researchers who need assistance with transferring data within the University and between the University and external sites or repositories. We will often collaborate with Connect Digital Service to meet with you and discuss your specific needs.


Data Publishing

In addition to data publishing advice, we support the University’s research data repository, institutional Figshare. Available since 2017, this service enables researchers to publish research data descriptions and documentation (or metadata) supporting others to discovery and reuse. data and artefacts.All published items are assigned a persistent digital object identifier (DOI) through DataCite and indexed by Google. For data that is sensitive, embargoed or otherwise restricted in access one can make use of metadata only records, private links and/or reserve DOI features. All data published to our institutional Figshare are stored locally on the University of Auckland storage systems.The Centre for eResearch collaborates with Connect Digital Services  and Libraries and Learning Services to provide and support use of this predominantly self-service data publishing platform that is available to all University staff and doctoral students.


Instrument Data

The Centre for eResearch, in partnership with Connect Digital Services, offers support to researchers who seek effective data management solutions for their instrument data. We offer face-to-face consultations to understand the specific needs regarding your instrument data, and design solutions for storing, sharing, and transferring data. We can also point to appropriate avenues for publishing and archiving instrument data. We are developing an Instrument Data Service that will make use of a dedicated instrument data repository that can be added to the data workflow of specific instruments. We are currently working with a few early adopters.


In partnership with Libraries and Learning Services, the Centre for eResearch offers regular workshops aimed at PhD candidates, supervisors, principal investigators, and research staff to support research data management, data management planning and data publishing. Go to Research data support & training for details.

Case studies of research data

Passive acoustic modelling

Given the current global biodiversity declines, understanding the process of biodiversity loss and improving tools for species conservation are emerging as major issues for ecological research. Protected areas are crucial for protecting biodiversity.

Research data publishing and preservation at COMPASS

The Centre of Methods and Policy Application in the Social Sciences (COMPASS) is interested in leveraging online data publishing to enhance research impact, teaching, and collaborative opportunities. It is currently using the University’s Data Publishing and Discovery Service (DPADS), namely Digital Science’s Figshare platform – a pilot program led by the University Library and Learning Services and the Centre for eResearch.

Improving diagnosis for schistosomiasis by using the ‘metabolic footprint’ of urine samples from an animal model of Schistosoma infection to identify possible biomarkers

Schistosomiasis infection constitutes a major public health problem, particularly in countries where the disease is endemic. Worldwide. It is estimated 779 million people at the risk of contracting schistosomiasis, while about 210 million are infected with the disease.

Taking a ‘Big Data’ approach to find new clinical-omic associations in cancer

Cancer is the number two cause of mortality in the OECD behind heart disease. Up until the late 1990’s, there was a concerted effort by drug companies to develop ‘blockbuster therapies’ for the treatment of cancer, i.e. cancer therapies developed with a one-size-fits-all approach.

Giving Pacific research greater reach

Launched in March 2016, the New Zealand Institute for Pacific Research (NZIPR) is a national institute aimed at promoting and supporting excellence in Pacific research, in order to deliver a world-class research programme focused on Pacific development, investment and foreign-policy issues.

Data management planning for MOA

MOA is a Japanese New Zealand collaboration that makes observations on dark matter, extra-solar planets and stellar atmospheres using the gravitational microlensing technique. The phenomenon now known as gravitational microlensing was first described by Einstein in 1936.

Making stroke recovery prediction tools freely available

Stroke is a leading cause of adult disability worldwide. Most people who experience a stroke have weakness on one side of their body. The ability to live independently again after stroke depends largely on the recovery of strength and function on the affected side.