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D7.2: Descriptive analysis and inventory of profiling practices

Appendix  Foreword





general:a reciprocal relation between two or more things

in statistics: a statistic representing how closely two variables co-vary; it can vary from -1 (perfect negative correlation) through 0 (no correlation) to +1 (perfect positive correlation);

a statistical relation between two or more variables such that systematic changes in the value of one variable are accompanied by systematic changes in the other

non linear:any correlation in which the rates of change of the variables is not constant; also called curvilinear correlation



data controller:


data mining:data processing using sophisticated data search capabilities and statistical algorithms to discover patterns and correlations in large pre-existing databases; a way to discover new meaning in data



data subject:


data processing:

computer science:


legal:any operation or set of operations which is performed upon personal data, whether or not by automatic means, such as collection, recording, organisation, storage, adaptation or alteration, retrieval, consultation, use, disclosure by transmission, dissemination or otherwise making available, alignment or combination, blocking, erasure or destruction

Directive 95/46 EU on Data Protection, concerning processing of personal data, art. 2 sub b




ontology:In computer science, an ontology is the product of an attempt to formulate an exhaustive and rigorous conceptual schema about a domain. An ontology is typically a hierarchical data structure containing all the relevant entities and their relationships and rules within that domain (eg. a domain ontology).



profile:set of correlated data that identifies and represents a data subject. If the data subject is a group/a category/or a cluster we speak of a group profiles, when the data subject is a single person we speak of a personalised profile


profiling:the process of constructing profiles (correlated data), that identify and represent a data subject (either a person or a group/catogory/cluster), and/or the application of profiles (correlated data) to identify and represent a person as a specific person or as member of a specific group/category/cluster, aiming at the assessment of risks and/or opportunities for the data user (inferred from risks and opportunities concerning the data subject)


semantic web:Although the term ‘ontology’ has been used very loosely to label almost any conceptual classification scheme, among practising computational ontologists, a true ontology should besides the subsumption relation (also: ‘is a’, ‘subtype’ or ‘subclass’), also describe entities by other ‘semantic relations’ that specify how one concept is related to another.



(end) user:





Appendix  fidis-wp7-del7.2.profiling_practices_03.sxw  References:
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