Welcome to the Unisa Research Data Management LibGuide. This Guide will provide information on processes, procedures and policy with regards to research data management (RDM), as well as access to resources and tools that can support researchers in managing their data.
It will also serve as a space to pilot platforms for archiving the research data
Please send any suggestions and comments to the compiler of this guide.
MANTRA Online Research Data Management Course
MANTRA is a free online course for those who manage digital data as part of their research project.
Please click on the following links for an Online open access course for researchers and librarians:
Researchers: http://mantra.edina.ac.uk/
Librarians: http://mantra.edina.ac.uk/libtraining.html
In order to promote open access to research data, many funding agencies require research data produced as a funded project to be made publicly available. Many funding agencies have stipulated requirements for data sharing and a formal data management plan.
National Research Foundation (NRF) Funding Requirement
From 01 March 2015, authors of research papers generated from research either fully or partially funded by NRF, when submitting and publishing in academic journals, should deposit their final peer-reviewed manuscripts that have been accepted by the journals, to the administering Institution Repository with an embargo period of no more than 12 months. Earlier Open Access may be provided should this be allowed by the publisher. If the paper is published in an Open Access journal or the publisher allows the deposit of the published version in PDF format, such version should be deposited into the administering Institutional Repository and Open Access should be provided as soon as possible.
In addition, the data supporting the publication should be deposited in an accredited Open Access repository, with the provision of a Digital Object Identifier for future citation and referencing.
The NRF encourages its stakeholder community, including NRF’s Business Units and National Research Facilities, to:
The NRF requires its relevant Business Units and National Research Facilities to actively collaborate with relevant governmental departments and public higher education and research institutions to facilitate Open Access to publications generated from publicly funded research. The NRF requires its stakeholder community to actively seek collaboration with the international scientific community to facilitate the Open Access of publications generated from publicly funded research across the world.
The following is a selection of the core funding agencies for the potential researcher to consider:
South Africa
The benefits of Research Data Management include the following:
It is important to distinguish between data and information. The following sourced from Data vs Information explains this difference:
" ... Data are the facts or details from which information is derived. Individual pieces of data are rarely useful alone. For data to become information, data needs to put in context. ... "
In turn, information allows us to expand our knowledge.
The infographics on the second and third tab illustrate this further.
The following "Infogineering Model" illustrates the progression from data to information to knowledge.
Research data may be broadly described as "... data that is collected, observed, or created, for purposes of analysis to produce original research results." (What is "Research Data")
Research data may be generated for different purposes and through different processes and may be divided into the following categories. Each category may require a different type of data management plan.
Observational
Experimental
Simulation
Derived or compiled
Reference or Canonical
These data can come in many forms such as, text, numerical, multimedia, models, software, discipline specific (i.e., FITS in astronomy, CIF in chemistry), or instrument specific.
Sourced from: Boston University Libraries - Research Data Management
Research data management, also referred to as Data Management is the process of controlling the data generated during a research project. The outcome is a usually a publication in the form of an article, report, thesis, dissertation and the like.
Any research project will require some level of data management. Funding agencies are increasingly requiring researchers and scholars to plan and execute good data management practices.
Managing data or data management is an integral part of the research process.
It can be challenging particularly when studies involve several researchers and/or when studies are conducted from multiple locations.
How data is managed depends on the types of data involved, how data is collected and stored, and how it is used - throughout the research lifecycle.
The outcome of a research project depends in part on how well the raw data is managed.
Managing data helps the researcher to organize research files and data for easier access and analysis. It helps ensure the quality of the research. It supports the published results of the work and, in the long term, helps ensure accountability in data analysis.
Effective data management practices include:
Sourced from: Penn State University Libraries - What is data management
Due to contractual and licensing agreements, access to some content may be restricted to the Unisa community.
Inclusion in this LibGuide does not imply University nor library endorsement of any ideas expressed.
