Datankeräys

Datankeräys is a Finnish term referring to the systematic process of collecting data for analysis, decision making, or monitoring. It encompasses primary data gathered directly from sources as well as secondary data obtained from existing datasets. Datankeräys is used across scientific research, public administration, business analytics, and journalism.

Data collection is carried out through various methods. Primary data collection includes surveys, interviews, focus groups, experiments, and direct observation. Digital traces from apps or devices, sensor networks, and log files also contribute. Secondary data comes from administrative records, official statistics, published datasets, and web-sourced information such as metadata or publicly accessible databases. The choice of method depends on research questions, resources, and ethical considerations.

Planning and quality are central. Key steps include defining variables, determining the study design, selecting a sampling strategy, and estimating an appropriate sample size. Data quality concerns include validity, reliability, bias, nonresponse, and measurement error. Careful documentation and the use of metadata standards support reproducibility and data integration.

Ethics and legal aspects are important. Datankeräys must respect privacy and consent requirements, protect sensitive information, and comply with data protection laws (such as GDPR in the European Union). Anonymization or pseudonymization, secure storage, access controls, and clear data retention policies are common safeguards. Data governance frameworks may govern data provenance and usage rights.

Challenges and best practices include addressing nonresponse bias, ensuring representativeness, handling missing data, and maintaining data quality over time. Transparent methodology, data sharing where appropriate, and thorough documentation aid reliability and reuse.