A Typology of Temporal Data Imperfection

Nassira Achich (1) , Fatma Ghorbel (2, 1) , Fayçal Hamdi (2) , Elisabeth Metais (2) , Faiez Gargouri (1)

1 MIRACL - Multimedia, InfoRmation systems and Advanced Computing Laboratory
2 CEDRIC - ISID - CEDRIC. Ingénierie des Systèmes d'Information et de Décision

Temporal data may be subject to several types of imperfection (e.g., uncertainty, imprecision..). In this context, several typologies of data imperfections have been already proposed. However, these typologies cannot be applied to temporal data because of the complexity of this type of data and the specificity that it contains. Besides, to the best of our knowledge, there is no typology of temporal data imperfections. In this paper, we propose a typology of temporal data imperfections. Our typology is divided into direct imperfections of both numeric temporal data and natural language based temporal data, indirect imperfections that can be deduced from the direct ones and granularity (i.e., context - dependent temporal data) which is related to several factors that can interfer in specifying the imperfection type such as person’s profile and multiculturalism. We finish by representing an example of imprecise temporal data in PersonLink ontology.

Keywords: Data Imperfections; Typology of Temporal Data Imperfection; Direct and Indirect Imperfections; Natural Language based Temporal Data; Context -Dependent Temporal Data

Domains: Artificial Intelligence [cs.AI]; Web

Nassira Achich, Fatma Ghorbel, Fayçal Hamdi, Elisabeth Metais, Faiez Gargouri. A Typology of Temporal Data Imperfection. 11th International Conference on Knowledge Engineering and Ontology Development (KEOD 2019), Sep 2019, Vienna, Austria. pp.305-311, ⟨10.5220/0008168403050311⟩. ⟨hal-02465298⟩