Researchers often consider the full range of possibilities for collecting data and organising methods when conducting scientific research. These methods help determine the degree to which the nature of research data to be collected may be predetermined, the use of close-ended and open-ended questioning, and their focus on numeric and non-numeric data analysis. In research data management (RDM), researchers often begin by completing a data management plan, which outlines strategies and tactics they intend to adopt for collecting research data. This article is focused on the ‘data collection’ phase of the research data lifecycle and builds on the previous blog post titled ‘Research data management planning @SU’ which explains the significance of the RDM plan and further outlines the support services provided by the SU Library.
Research data collection can be grouped into two main techniques, namely, documentation and data organisation. Documentation can be understood as the process of writing up descriptive information about research data during the data collection process with the aim of ensuring that research data can easily be understood by other researchers and future-self. Data organisation on the other hand explains how research data will be kept in order using appropriate organisational systems and file naming conventions. At a basic level this entails creating folders for digital files, copying and pasting, and moving everything around with the click of a computer mouse. For developing a more advanced organisational system, the SU library may provide such support on request to help researchers design an organisational system that works for a group or individual researchers. Documentation may be created in various formats, however, all formats should always remain consistent in terms of the descriptive contents. This entails that all documentation regardless of the format needs to have basic information about the research data that enable correct interpretation and reuse by other researchers and future-self.
Documentation can include anything from using lab notebooks, field notes, metadata, protocols, as well as other useful documentation formats such as README.txt files, codebooks, data dictionaries, and/or templates. Researchers from Stellenbosch University (SU) come from various educational backgrounds making it somewhat difficult to develop a single format or approach for documenting research data. To address this, the SU library often encourages researchers to ensure that their documentation includes adequate information on their data detailing ‘what’ type of data was collected, ‘how’ was it collected, ‘why’ was it collected, ‘when’ was data collected, ‘where’ was data collected, and ‘who’ collected the data. Given that RDM services at SU are still in a developmental phase, the SU Library does provide support for all previously mentioned documentation formats with README.txt files being the preferred documentation method.
Author: Sizwe Ngcobo
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