Datasamling

Datasamling, or data collection, is the process of gathering, measuring, and analyzing information from various sources to describe, explain, or predict phenomena. It is used across research, industry, and public administration. The term covers both primary data collection (collecting new data) and secondary data collection (using existing data).

Common methods include surveys and interviews, experiments, observations, and the collection of digital traces such as log files, sensor readings, and administrative records. Primary data collection focuses on designing instruments (questionnaires, protocols) to capture relevant variables. Secondary data uses already available datasets, often compiled for other purposes.

Key design considerations include defining the target population, sampling frame, sampling method, and sample size. Sampling aims to approximate the population while controlling cost and bias. Data quality challenges include measurement error, nonresponse, and coverage error. Data cleaning, validation, and documentation (metadata) are essential.

Ethical and legal aspects emphasize privacy and protection of personal data. Practices include informed consent where appropriate, data minimization, anonymization or pseudonymization, secure storage, and compliance with laws such as GDPR. Data governance ensures proper access, usage, and retention policies.

Applications span scientific research, policy making, market research, quality assurance, and public services. Limitations include cost, time, potential biases, and data incompleteness. Good datasamling relies on transparent methods, clear objectives, and rigorous quality control.