Digital Library

In the era of Open Science, there is a considerable emphasis on the dissemination of research data to optimize their utilization. Funding agencies like NWO, SIA, and ZonMw expect researchers to ensure that data derived from their funded projects are made accessible to a broad audience, adhering to the FAIR data principles. It should be also a standard practice in the preparation phase of any research project to critically assess whether creating new data is absolutely necessary and to evaluate existing datasets for their relevance to the new research project.

Frist, you have the option to reuse the data for your own research, utilizing both the complete dataset or specific segments of it. Furthermore, you can employ alternative data as points of reference for comparing your findings. In addition to the data, you may reuse established and validated research tools, such as questionnaires. Depending on copyright permissions, you can choose to reuse the questionnaires in their entirety, amalgamate selected sections with questions from other surveys, integrate them with your own questions, or simply draw inspiration from them.

Sometimes you may want to replicate, review or reinterpret the results of someone else's research in order to provide a foundation or context for your own. So you might consider extending the literature review by reviewing the datasets on which the publications in your bibliography are based.

Published datasets are primarily housed in data repositories or data archives. The THUAS library provides access to Data Citation Index (DCI). This is multidisciplinary index of scientific research data launched in 2012  within Web of Science. It allows for search and discovery of the data and links them to the published literature with appropriate citation. It focuses on repositories that publish metadata in English or, at the very least, allow provision of sufficient descriptive (metadata) information in English.

In the Netherlands, there exist 79 data repositories, with two of notable international standing – DANS data stations and 4TU.ResearchData - holding the prestigious CoreTrustSeal quality seal. A global search for data repositories can be conducted through the Re3data registry. Open Access Directory also provides a directory of major data repositories. In addition to these repositories, there are various avenues for discovering suitable datasets. Initiating a query within your professional network is one approach. Information regarding published datasets is also accessible through scholarly literature. Beyond conventional journals, there are specialized data journals dedicated to discussing datasets. Details about accessing data collected by public institutions are typically available on the respective organizations' websites.

• First, you assess the dataset’s relevance to your research question by considering thematic, geographic and temporal coverage. 
• The purpose of data reuse is equally crucial, requiring attention to the various types of data. For example, you may require raw data for reanalysis, processed data or data documentation to validate others' results, or a blank questionnaire for new research. 
• The reuse of data must be allowed by the license. Just because the data is published does not automatically mean that you may reuse the data. 
• Technical constraints may also play a role; for example, if the data are not shared in open formats, their use may be complicated due to specific software requirements. 
• Furthermore, comprehensive metadata at the level of the project, files, and data are essential for proper understanding of the data. It is necessary to verify that the data possess complete documentation or are linked to associated publications that offer more insights into the dataset.

Once you have found and used the appropriate data, don't forget to cite the dataset. Data citation instructions can usually be found with each dataset in a data repository. Adapt the citation style you use in your manuscript. A data citation generally consists of the following components: author, title, publication year, publisher, version, and persistent identifier.

In addition to data, you can also reuse validated research instruments in your study that have been developed by other researchers. These include, for example, a questionnaire, a structured interview, or an observation schedule. 

Where can you find research instruments? 

You can find research instruments—just like data—in data repositories, such as DANS Data Stations, 4TU.ResearchData, or the OSF platform. Information about research instruments, translations, and adaptations of existing questionnaires, as well as reviews of tools, can be found in scientific articles. Besides reading the texts of publications, you should also pay attention to appendices where instruments might be included and citations where they may be mentioned. You can also ask colleagues or other experts in the field about instruments they have designed. 

What should you consider? 

It is important to realize that searching for instruments and obtaining permission takes time. Some instruments are freely available, but there are also commercial tools for which you will have to pay. Even if a research instrument is published and accessible, it does not automatically mean that you can reuse it; you need to check the copyright. When assessing instruments, you should determine whether they are reliable and valid. A validated research instrument is a tested tool that clearly measures what it is intended to measure and that indeed measures what it should. If you want to translate a questionnaire originally developed in another language, it is necessary to follow a formal translation procedure, which also includes adaptation to a new cultural and societal context.