3.5 Questions 4 Collecting data
Data collection is an important step of the data life cycle as it is the basis of knowledge creation. Data is collected regarding specific methods, settings and instruments. To generate comprehensible and reusable data, it is necessary to document data acquisition using metadata.
It is also possible to reuse already collected data and to integrate it into your own project. However, be aware that data integration can be very tedious. This can be data from your previous research project or data from repositories [1][2]
Since in biology, taxonomic designations can vary depending on the source and concept used, harmonisation is necessary in some cases.
After completing this chapter, you will be able to...
- …select appropriate tools to assist you in the data collection process.
- ...recognise metadata and the benefits of metadata
- ...name important categories of metadata
- ...name selected metadata standards
- ...create your own metadata
- …select a suitable tool for handling with metadata
- ...describe your research data via metadata so that your research data can be used in the future and by machine-reading systems
- …name the important elements of taxonomic information that are necessary to merge different species data sets
[1] ELIXIR converge. (2022b). Data Life Cycle - Collecting. RDMkit. Available at: https://rdmkit.elixir-europe.org/collecting. Last accessed 4 October 2023.
[2] GFBio. (2023c). GFBio Training Materials: Data Life Cycle Fact-Sheet: Data Life Cycle: Collect. GFBio. Available at: https://www.gfbio.org/training/material/data-life-cycle/collect/. Last accessed 27 November 2023.