Successful collaboration begins with a shared language, hence the need for a glossary. This joint effort of contributors from several teams ensures, on the one hand, terminological and conceptual coherence across not only our theoretical approaches, but also the qualitative case studies and quantitative research conducted in OPPORTUNITIES. On the other hand, our glossary facilitates communication between the academic side of the project and the fieldwork conducted by NGOs, uniting our teams working from Austria, Belgium, France, Germany, Ghana, Italy, Mauritania, the Netherlands, Portugal, Romania and Senegal.

For more information about the Structure and Objectives of the Glossary, click here...)

Data is a piece of information which can be in numerical or other forms. In order to know how many migrants (defined as those who were born in a different place) live in a city, researchers ask the residents of this city (i.e. the subjects of study) about their ‘place of birth.’ If data is collected from a subject without identifying him or her, it is called anonymous data; otherwise the data is called personal data. All personal data contain sensitive information that people may not wish to share with others and therefore data protection measures such as the removal of any references to names, addresses, and the like must be put in place in order to protect peoples’ information and privacy. This process is called anonymization of data. Researchers distinguish between primary and secondary data collection. Primary data collection refers to ‘original’ collection of data – the researcher collects data directly from a person (e.g. by asking people directly about their place of birth) or indirectly (e.g. by asking a family member about the place of birth of all family members). Secondary data collection refers to the collection of data from an agency/entity that has previously collected this data directly from subjects of study and is now in possession of this data. One of the most commonly used sources of secondary data is a census.

⇢ see also: Data mining

References and further reading:

Makkonen, Timo. 2007. Measuring Discrimination: Data Collection and EU Equality Law. Luxembourg: European Communities. URL:

Category: A

Work Package: 2, 4, 5