Data Evaluation Technique and Intelligence Source

Abstract

The aim of this study is presenting to Intelligence intern the judgment of the source (according to the Data Evaluation Technique, TAD, in portuguese), the difficulties in establishing this judgment and possible ways to minimize them. It is known that the Intelligence knowledge is used to reduce the uncertainties of users, and that it has a methodological basis. One of the stages of the process is the verification of both the source and the produced data, which helps to qualify the Intelligence’s knowledge and attest to its veracity. Intelligence data comes from open sources, technological means and human sources. The adequacy of these sources is judged from three aspects: authenticity, reliability, and competence. The credibility of the content is evaluated through the coherence, compatibility and similarity of the data. Issues that may affect the analysis are: taxonomic differences between organizations; different interpretations of technical mean data or partner data; existence of rumor; interference of cognitive biases in the perception of the source; adapting the TAD to both human and technological sources; checking images, voice recordings, video and the like for temporal, geographical or metadata inconsistencies. This is a key area for Intelligence, which requires from the analyst critical thinking and ability to work in horizontal teams, with peer review. It also demands from the organization technological means to improve the analysis, as well as improve the data storage and retrieval system, in order to allow the reassessment of these with a certain historical impartiality.