Małgorzata Grodzińska-Jurczak

Secondary data comprise resources collected in various sectors of social life, independently from the researcher undertaking their analyses. Collecting such data is usually less time consuming and less costly compared to reactive studies, thus, each time when planning a research study, inclusion of secondary data should be considered. This specifically requires: 1) usage of systematic, multi-criteria evaluation methods; 2) separate evaluation of certain categories of secondary data; 3) separate reference to each of the research specific aims.
The following paper presents an example of such an evaluation that meets all the criteria mentioned above. Using a point grading technique we assessed usefulness of three categories of secondary data (scientific literature, data used in content analysis and content of the public statistics) to meet all three specific aims of an interdisciplinary research project conducted by the same authors. Each of the aims differs in a) spatial scale of analyses (regional, local and topological) and b) dominant form of enquiry (quantitative, qualitative and qualitative accompanied with the use of GIS techniques). The results suggest usefulness of the technique in the context of multifaceted research projects: final evaluation scores for particular secondary data categories differed substantially depending on the specific aim. However, we suggest all the analysts to perform a deep insight into the evaluation process itself before deciding to replace reactive research with secondary data analyses. Among others, this is because weights assigned to certain criteria of the evaluation process are often dependent on organisational capacity of a particular research project. At the same time, exemption of the proposed stage of research planning may result in various negative consequences, e.g. 1) reduction in funding perspectives due to weak justification of the planned costs, or 2) lowering research scientific value of the study due to a lack of critical insight into the data, which are out of actual analyses.