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Learning objectives
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Summary
This chapter will start by providing a range of practical recommendations for data management, which refers to the ingesting, processing, securing and storing of data so that it can be used for decision-making purposes. The reliability, completeness and coverage of migration data can be ensured at the data collection stage by addressing language barriers, choosing the right interviewing format (e.g., computer-assisted person-interviewing, computer-assisted web-interviewing, etc.), assigning appropriate enumerators/first responders and cultivating relationships for gaining access to the field.
At the data processing stage, reliability and completeness of the data can be improved by circulating predefined coding schemes, developing tools and platforms for recording data electronically, establishing a clear chain of reporting from lower to higher levels of administration, restricting data modification rights, assigning an information management officer to sub-offices and linking records with an institutional personal identification number (PIN) that can only be linked to data subjects via a secured internal database.
When it comes to storage, data management officers will be responsible for choosing the right storage medium, developing a clear labelling system and folder structure, using easily accessible data file formats and securing data files through firewalls and password encryption. Lower-income country face several challenges, including restricted access to data processing and storage facilities, limited network access at border points and lack of interoperability between data systems, both within and across countries. Potential solutions for strengthening the data infrastructure of lower-income countries are creating data exchange points and colocation centres, securing on-ramps to global clouds and investing in ICT human resources.
One of the main challenges to disseminating migration data is that they are often scattered across multiple agencies that collect different kinds of data, define migration in different ways and either do not communicate with each other or do not have formal mechanisms in place for sharing data with each other. Therefore, stakeholders might invest in creating an enabling data sharing environment by listing all relevant data producers and users, identifying focal points for each agency, nominating a national coordinator or key statistical authority, conducting a data and ICT needs assessment, developing a core set of indicators based on harmonized definitions in line with international standards and drafting MoUs on data sharing.
Finally, another challenge to sharing data is the potential misuse of data, which may result in (un)intended harm to data subjects. Data privacy and protection principles can be enforced by anonymizing personal data, obtaining respondents’ informed consent (for data that is not required for administrative processes), setting up firewalls and password encryption, specifying the purpose of data collection and regulating third party access.