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A powerful large capacity database for raw and validated water quality data

Automated monitoring stations and state-of-the-art instrumentation allow monitoring water bodies at high frequency and generating large amounts of relevant data. However, all these data are only useful if they are well documented and their quality is assured. Thus, the tasks of storage and validation of these collected data are crucial for further analysis, interpretation and efficient exchange.

A successful management of the data requires a proper database to store and document ALL relevant data. However, when a long-term database is to be established, some data management challenges are identified: the lack of standardization of data formats used in the field, the continuous growth of the data set, modifications to the database such as the addition of variables or a change in sensor characteristics, change of the personnel involved, and documenting metadata (data about data) about the monitoring setup. Hence, an ideal database structure should permit to store a wide range of data: raw, filtered and validated time series, individual lab measurements and the links between them as well as the corresponding metadata that document these data well. For each data point, these metadata provide detailed information about what has been measured, when, where, how and why the value has been measured, and who has collected the value.

The objective of the datEAUbase project is to develop a central data storage which is able to deal with these challenges, i.e. it provides uniformity in the data format, flexibility for further modifications, relevant metadata storage, and documentation regarding the monitoring activity. The result is a robust tool to manage large amounts of data that are supplemented with a wide range of relevant information (metadata) and data quality information.

Publications :
    Conference proceedings
  • Plana, Q., Kraft, T., Alferes, J., Maruéjouls, T. and Vanrolleghem, P. A. (2016) datEAUbase: A powerful large capacity database for raw and validated water quality data with emphasis on their metadata. In: Proceedings 10th National Monitoring Conference (NWQMC) - Working Together for Clean Water. Tampa, FL, USA, May 2-6 2016.  

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Faculty of Science and Engineering - Université Laval
Peter Vanrolleghem - Department of civil engineering and water engineering - Pavillon Adrien-Pouliot - 1065, Médecine avenue, Office 2974
Québec (Québec) - Canada - G1V 0A6 - Telephone : +1-418-656-5085 Email : peter.vanrolleghem@gci.ulaval.ca
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