Resources
- Identity Use Cases & Scenarios.
- FIDIS Deliverables.
- Identity of Identity.
- Interoperability.
- Profiling.
- D7.2: Descriptive analysis and inventory of profiling practices.
- D7.3: Report on Actual and Possible Profiling Techniques in the Field of Ambient Intelligence.
- D7.4: Implications of profiling practices on democracy.
- D7.6 Workshop on AmI, Profiling and RFID.
- D7.7: RFID, Profiling, and AmI.
- D7.8: Workshop on Ambient Law.
- D7.9: A Vision of Ambient Law.
- D7.10: Multidisciplinary literature selection, with Wiki discussion forum on Profiling, AmI, RFID, Biometrics and Identity.
- D7.11: Kick-off Workshop on biometric behavioural profiling and Transparency Enhancing Technologies.
- Forensic Implications.
- HighTechID.
- Privacy and legal-social content.
- Mobility and Identity.
- Other.
- IDIS Journal.
- FIDIS Interactive.
- Press & Events.
- In-House Journal.
- Booklets
- Identity in a Networked World.
- Identity R/Evolution.
D7.2: Descriptive analysis and inventory of profiling practices
Glossary:
correlation
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
see http://www.elook.org/dictionary/correlation.html
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
see http://www.elook.org/dictionary/correlation.html
data subject:
data processing:
computer science:
see http://www.elook.org/dictionary/correlation.html
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
KDD:
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).
see: http://en.wikipedia.org/wiki/Ontology_(computer_science)
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.
www.en.wikipedia.org/wiki/Ontology_(computer_science)#Semantic_web
(end) user:
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