The State of Open Data 2021
Data Science - Figshare - Springer Nature
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Tips for engaging your researchers in open data sharing practices: practical guidance from the University of Pretoria

Veliswa Tshetsha
Senior Coordinator: Open Scholarship
University of Pretoria

Rosina Ramokgola
Data Curation Officer
University of Pretoria

Pfano Makhera
Metadata Specialist: Scholarly Communications
University of Pretoria

Background on data management and engagement practices at the University of Pretoria

The library at the University of Pretoria started engaging in research data management activities in 2009. We conducted an initial research data management (RDM) survey from October 2009 to March 2010. A second survey involved interviewing the Deputy Deans of Research from Faculties to determine the essential research data that the University should manage. Two pilot projects aimed at gaining insights and understanding of researchers’ RDM needs took place in 2013 and 2014 with the Institute for Cellular and Molecular Medicine (ICMM) and the  Neuro Physiotherapy Group These projects used open source document management systems, Alfresco and Islandora, and were customized to manage data. After the pilot projects, further developments took place including identifying a campus-wide database or repository for the publishing of open access datasets. Further investigation took place until 2018 where Figshare was introduced to the DLS and was approved and implemented as a data repository solution in July 2018. 

 The library developed RDM resources such as a LibGuide and implemented an RDM readiness Training Toolkit. The toolkit contains videos on how to upload datasets, how to be responsible with your research data, how research data management is quick and easy to implement with access to data remaining under your control, and why effective research data management matters today, tomorrow, and in years to come.

Researchers are supported with meeting funder requirements on data management plans and data sharing practices. The library has recently established a strong partnership with the institutional research grant office and is working toward integrating data management plans in the grant application process. Advocacy and support for researchers is required particularly because with the free availability of the university’s open data repository, researchers should rest assured that their datasets will be securely curated and accessed when needed.


Future plans for RDM

RDM is still new at the university. We have just started and we will continue tracking and harvesting University-affiliated datasets and engaging our users by consulting them on further use cases and how we can provide support. We will also look at developing an integration where postgraduate students are required to submit datasets for their thesis submission before they graduate. We will also create a requirement to submit a data management plan as part of the grant application process.


Tips for how to engage your researchers in open data sharing practices

The following are a few common problems or challenges that survey participants said they faced with sharing datasets in this year’s State of Open Data survey. We have provided some tips and examples of how to overcome these challenges based on our experiences at the University of Pretoria.


Misuse for commercial use or misinterpretation

Institutions should create awareness (training, advocacy) for researchers in areas pertaining to reuse of data — for example, the Creative Commons licenses. The library worked on a roll-out strategy by hosting RDM Repository roadshows, workshops, creating awareness across faculties. 

The library hosted webinars on RDM for early career and well-established researchers on how to discover, manage and share data, how to upload data, how to create Data Management Plans, and RDM in general.

Researchers and postgraduate students received training and were guided on how to secure their data by generating DOIs to enable attribution and discoverability. Our repository has features to protect datasets either privately or publicly. User guidelines and data dictionaries are provided. Researchers should also provide as much information as possible in the metadata; this will make it easy for other researchers to understand and interpret data.


Graphic from the survey: What problems/concerns. if any, do you have with sharing datasets?



Unsure about copyright and data licensing

Libraries should play an active role in providing training and guidance on copyright ownership and data licenses. Our library provides copyright services such as training researchers on copyright and fair use. The library also offers copyright compliance awareness lunch hour sessions for lecturers and students. The aim is to engage and educate users on copyright and the importance of complying with the legislation.


Not receiving appropriate credit or acknowledgement

Institutions can implement research data recognition grant awards for researchers who are not receiving appropriate credit or acknowledgement or who do not have the desire to share data. This reward tool can be expanded to include postgraduate students, as well. This can also form part of the research(er) data performance evaluation. 

Researchers can be recognized in many ways; for instance, have Researcher of the Month through university websites, social platforms, or have University Researcher Month where researchers will be acknowledged and prizes won or certificates of merit issued.

In South Africa, researchers are rewarded for generating, preserving, sharing and/or re-using research data by the National Science and Technology Forum (NSTF-South32 Awards). The call for nominations recently came out and we will nominate researchers who are sharing data in our research data repository.


Organizing data in a presentable and usable way

Researchers should use data management plans (DMPs) and archive their data in trusted repositories. An RDM policy, as well as funders, encourages researchers to create DMPs; this can be done using something such as DMPTool. The library assisted in the establishment of a national Data Management Plan (DMP) tool in South Africa. Recently, the library had a stakeholder engagement and a DMPTool roll-out strategy.


Another lab may make a different interpretation of my data

If the data is not described properly, others are likely to misinterpret it. Descriptive metadata plays an integral part in ensuring that data is interpreted correctly. Data sharing fosters collaboration both locally and internationally.


Others may find errors in my data

Data is for reuse and sharing data allows others to correct those errors and collaborate with the researcher. When data is publicly open it fosters collaboration with other researchers in the same field or in adjacent fields. Lack of complete information may result in errors and libraries should guide researchers on the use of good data management tools and data quality standards.


I have no problems/concerns about sharing data

Positive researchers can educate other researchers; this is the practice that institutions should adopt. During workshops, we use existing researcher profiles to educate others. During International Open Access Week, we showcase some of our institution’s researchers whose works are open so as to encourage others. We have recently started a research(er) visibility and impact project where we support researchers to enhance their profiles on our institutional data repository.



Read next:

Many respondents are putting in the hard work of data sharing:

74% are making data management plans

76% curate their data for sharing

66% are familiar with the FAIR principles that underpin data sharing

How open data can help validate research and combat scientific misinformation

Prof Ginny Barbour - Queensland University of Technology

The 2021 State of Open Data survey provides valuable insights into data sharing globally. Though it can’t capture what researchers everywhere think of data sharing, this survey of nearly 4,500 researchers offers helpful perspectives, some reasons to be hopeful, and some key takeaways that can support discussions on how open data can help validate research and combat scientific misinformation.

The decision to share data and the mechanisms necessary to support sharing don’t exist in a vacuum. In many ways, the problems of how to share data are reflective of both the culture of science and of current logistical challenges playing out across research globally. How can we move to a more open world?

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