Navigating the Data Landscape
Wed-01
Presented by: Sonja Bayer
In recent years, there has been a push towards open science, and there is a growing emphasis on the significance of open data and data sharing in scientific research (Nosek et al., 2015; van der Zee & Reich, 2018). Effective data sharing is a crucial principle in fostering transparency, reproducibility, and collaboration in scientific research, making it a vital topic in the context of Open Science. The abundance of information and the increasing availability of research data have created both opportunities and challenges to the scientific community.
On the one hand, access to a wealth of information can lead to new discoveries and advancements in knowledge (Nosek et al., 2015). On the other hand, it can be difficult to find the relevant data for one's research amidst the large volume of information. For instance, a study on researchers' perspectives on data reuse found that approximately 40% of researchers in social, behavioural, and economic fields reported difficulty in finding suitable data for secondary analysis (Bayer et al. 2022).
Open Science, with its emphasis on transparency and reproducibility, provides a solution to this problem by promoting the Findable, Accessible, Interoperable, and Reusable (FAIR) data principles (Wilkinson et al., 2016). These principles ensure that data is well-documented and easily discoverable for both humans and computers. Research data infrastructures promote FAIR principles and support researchers in publishing their data according to these principles. Additionally, research data infrastructures implement standards and structures to access data.
As demonstrated by the Network of Research Data Centers in Germany (Verbund Forschungsdaten Bildung), we show how standardization and harmonized metadata can create a “single point of access” for research data across different data centers and repositories. This includes harmonizing the data preparation and indexing processes of the research data centers participating in the VerbundFDB and developing a metadata core set as a quality standard for describing educational research studies. In addition, the network collaborates with applications such as the DOI registration agency daIra and the National Research Data Infrastructure Germany (NFDI) to ensure the widest possible access to research data in the field of educational research. In this way, data users are provided with a transparent search system for available research data in educational science that covers all Research Data Cencters.
References
Bayer, S., Loesch, T. & Hasche, G. (2022, August). (Re-)Using Research data: Researchers’ Perspectives on Potentials and Challenges. European Conference on Educational Research. Yerevan, Armenia. https://osf.io/zp436
Nosek, B. A., Alter, G., Banks, G. C., Borsboom, D., Bowman, S. D., Breckler, S. J., et al. (2015). Promoting an open research culture. Science, 348(6242), 1422–1425. https://doi.org/10.1126/science.aab2374.
Wilkinson, M. D. et al. (2016). The FAIR guiding principles for scientific data management and stewardship. Scientific Data, 3 (160018), doi: 10.1038/sdata.2016.18 (2016).
van der Zee, Tim; Reich, Justin (2018): Open education science. In: AERA Open 4 (3), 233285841878746. DOI: 10.1177/2332858418787466.
On the one hand, access to a wealth of information can lead to new discoveries and advancements in knowledge (Nosek et al., 2015). On the other hand, it can be difficult to find the relevant data for one's research amidst the large volume of information. For instance, a study on researchers' perspectives on data reuse found that approximately 40% of researchers in social, behavioural, and economic fields reported difficulty in finding suitable data for secondary analysis (Bayer et al. 2022).
Open Science, with its emphasis on transparency and reproducibility, provides a solution to this problem by promoting the Findable, Accessible, Interoperable, and Reusable (FAIR) data principles (Wilkinson et al., 2016). These principles ensure that data is well-documented and easily discoverable for both humans and computers. Research data infrastructures promote FAIR principles and support researchers in publishing their data according to these principles. Additionally, research data infrastructures implement standards and structures to access data.
As demonstrated by the Network of Research Data Centers in Germany (Verbund Forschungsdaten Bildung), we show how standardization and harmonized metadata can create a “single point of access” for research data across different data centers and repositories. This includes harmonizing the data preparation and indexing processes of the research data centers participating in the VerbundFDB and developing a metadata core set as a quality standard for describing educational research studies. In addition, the network collaborates with applications such as the DOI registration agency daIra and the National Research Data Infrastructure Germany (NFDI) to ensure the widest possible access to research data in the field of educational research. In this way, data users are provided with a transparent search system for available research data in educational science that covers all Research Data Cencters.
References
Bayer, S., Loesch, T. & Hasche, G. (2022, August). (Re-)Using Research data: Researchers’ Perspectives on Potentials and Challenges. European Conference on Educational Research. Yerevan, Armenia. https://osf.io/zp436
Nosek, B. A., Alter, G., Banks, G. C., Borsboom, D., Bowman, S. D., Breckler, S. J., et al. (2015). Promoting an open research culture. Science, 348(6242), 1422–1425. https://doi.org/10.1126/science.aab2374.
Wilkinson, M. D. et al. (2016). The FAIR guiding principles for scientific data management and stewardship. Scientific Data, 3 (160018), doi: 10.1038/sdata.2016.18 (2016).
van der Zee, Tim; Reich, Justin (2018): Open education science. In: AERA Open 4 (3), 233285841878746. DOI: 10.1177/2332858418787466.