Best data handling practices in water-related research

Zusammenfassung

Data play an important role in water-related research. In the field of limnology, monitoring data are needed to assess the ecological status of water bodies and understand the bio-geochemical processes that affect this status. In wastewater management, measured or simulated data are the basis for planning and control of sewer networks. Given the importance of data in water-related research makes them a valuable resource, which should be handled in an adequate way. Based on experiences in data collection and data processing in water-related research this paper proposes – both from a computer scientist’s and an environmental engineer’s point of view – a set of rules for data handling: Rule 1: Protect raw data. Rule 2: Save metadata. Rule 3: Use databases. Rule 4: Separate data from processing. Rule 5: Use programming. Rule 6: Avoid redundancy. Rule 7: Be transparent. Rule 8: Use standards and naming conventions. Applying these rules (i) increases the quality of data and results, (ii) allows to prepare data for long-term usage and make data accessible to different people, (iii) makes data processing transparent and results reproducible, and (iv) saves – at least in the long run – time and effort. With this contribution the authors would like to start a discussion about best data handling practices and present a first checklist of data handling and data processing for practitioners and researchers working in the water sector.

Publikation
Water Practice & Technology Vol 8 (No 3-4): 390-398 10.2166/wpt.2013.039
Sonnenberg, H.
Sonnenberg, H.
Researcher
Rustler, M.
Rustler, M.
Data scientist

My research interests include reproducible research, data management and programming (R & Python).

Riechel, M.
Riechel, M.
Researcher
Caradot, N.
Caradot, N.
Researcher
Matzinger, A.
Matzinger, A.
Researcher
Rouault, P.
Rouault, P.
Deputy Director, Head of Department “Urban Systems”