@article{fdi:010065025,
  title = {{A} quality-aware spatial data warehouse for querying hydrogeological data : case study},
  author = {{B}errahou, {L}. and {L}alande, {N}. and {S}errano, {E}. and {M}olla, {G}. and {B}erti-{E}quille, {L}aure and {B}imonte, {S}. and {B}ringay, {S}. and {C}ernesson, {F}. and {G}rac, {C}. and {I}enco, {D}. and {L}e {B}er, {F}. and {T}eisseire, {M}.},
  editor = {},
  language = {{ENG}},
  abstract = {{A}ddressing data quality issues in information systems remains a challenging task. {M}any approaches only tackle this issue at the extract, transform and load steps. {H}ere we define a comprehensive method to gain greater insight into data quality characteristics within data warehouse. {O}ur novel architecture was implemented for an hydroecological case study where massive {F}rench watercourse sampling data are collected. {T}he method models and makes effective use of spatial, thematic and temporal accuracy, consistency and completeness for multidimensional data in order to offer analysts a "€oedata quality"€ oriented framework. {T}he results obtained in experiments carried out on the {S}a{\^o}ne {R}iver dataset demonstrated the relevance of our approach.},
  keywords = {},
  booktitle = {},
  journal = {{C}omputers and {G}eosciences},
  volume = {85},
  numero = {},
  pages = {126--135},
  ISSN = {0098-3004},
  year = {2015},
  DOI = {10.1016/j.cageo.2015.09.012},
  URL = {https://www.documentation.ird.fr/hor/fdi:010065025},
}