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The MEIRU data department is responsible for building and maintaining data systems and providing data products to support MEIRU research goals. It supports researchers throughout the data lifecycle (Figure 1) from research design, data collection, data processing, data archiving, analytics, and visualisation, sharing, evaluation and re-purposing. 

The goal of the data section is to develop MEIRU data into Findable, Accessible, Interoperable and Reusable (FAIR) data resources in line with open data principles. 

The data section provides input during proposal development mainly developing an appropriate data management plan for a given project and advising on data structures, sample selection, data collection tools and data sharing plans.

Data collection 

MEIRU mainly uses Open Data Kit (ODK) for data collection. Paper-based forms are used to complement the electronic forms as necessary.  SurveyCTO and REDCap have also been used when collection is led by collaborators who prefer those tools. A wide variety of the questionnaires are available in the MEIRU data repository.

The data team works closely with the field team providing data collection instruments to the interviewers and addressing queries that may arise while interviewers are in the field.

Data uploading, validation, cleaning, and storage

Any data collected using paper forms are double entered. Data collected using ODK are uploaded onto the secure servers at the end of each day. Once in the databases, validation routines are run against the data and errors are resolved. The cleaned data are then stored in the databases. 

Data extraction and analysis support

Data are regularly extracted during data collection for monitoring and preliminary analyses, which enables real-time modifications of sampling strategies and data collection tools if required. Once data collection is complete, the data are extracted and combined into analysis-ready datasets, as required by the study team.

Meet the team

The MEIRU lead database programmer Baltazar Mtenga has the oversight of the data team and works closely with colleagues who specialise on various aspects as outlined on the individual profiles.