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Research Data Management

3 Mar 2022
WHY SHARE RESEARCH DATA?

WHY SHARE RESEARCH DATA?

Data sharing has become a mandatory requirement by institutions, funders and publishers.

Benefits of data sharing with research colleagues and communities include:

  • Promotes newdiscoveries
  • Increases research impact
  • Supportsvalidation and replication
  • Enhancescollaboration
  • Return on public investment
  • Reduced redundant research
USEFUL TOOLS & RESOURCES

USEFUL TOOLS & RESOURCES

UWC Data Management Plan (DMP) template

NRF Statement on Open Access (2015)

FAIR Data

Open Access and FAIR data principles

The FAIR Guiding Principles for scientific data management and stewardship

Data Intensive Research Initiative of South Africa (DIRISA)

DMP Online

DMP Online webinar

DCC Data Curation Lifecycle Model

Registry of Research Data Repositories

DMP Checklist

Elements of a Data Management Plan

Typical DMP components

Data Management Planning Workshop

F.A.I.R. DATA PRINCIPLES

Sharing data ensures that other researchers can access and use your data for further study. The FAIR data principles address the sharing of data by providing the following guidelines:

Findable: The research data record need to be discoverable by other researchers. Applying the appropriate description using general or subject specific metadata allows researchers to discover your data.

Accessible: Your data needs to be stored for the long term in an recognised storage facility such as a data repository. The data needs to be freely accessible and downloadable and useable.

Interoperable: Data and metadata needs to be written in a format that is accessible and can be interpreted by researchers and integrated with other data for analysis and processing. 

Re-useable: The goal is the optimum re-use of data. Data needs to be fully described in as much detail as possible including its provenance and using community or subject specific standards.

These principles apply to three aspects, the data (digital object), the metadata (a description of that object) and the infrastructure where the data is stored and from which it is shared.

SHARING RESEARCH DATA

DATA LIFECYCLE

Data Management Planning

Institutions and funders increasingly require a detailed description of how funded research data is going to be managed.

Data Management Plans include (but not limited to) the following:

Data description: what will be collected, how and for whom?

Access and sharing: How will the data be stored and accessed? Are there any restrictions?

Metadata: which metadata standards will be used?

Intellectual Property Rights: who owns the data? Are the any copyright or funder restrictions? 

Ethics and Privacy: How will consent be obtained? How will the subjects be protected?

Format: Which format will be used?

Archiving and preservation: What are the long-term storage plans? What are the backup plans?

Retention period: How long will the data be stored? 

Resources and Responsibilities: Which resources are required and who is responsible for what?

Data Management Plans are unique to each project and can be tailored to include more or less information.


CITING RESEARCH DATA

Citing data

How datasets link to publications

Quick guide to data citation

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