Volunteer Data Warehouse

Abstract

With the maturity of crowdsourcing systems, new analysis possibilities appear where volunteers play a crucial role by bringing the implicit knowledge issued from practical and daily experience. At the same time, data warehouse and OLAP systems represent the first citizen of decision-support systems. They allow analyzing a huge volume of data according to the multidimensional model. The more the multidimensional model reflects the decision-makers' analysis needs, the more the DW project is successful. However, when volunteers are involved in the design of DWs, existing DW design methodologies present some limitations. In this work, the authors present the main features of volunteer data warehouse (VDW) design, and they study the main existing DW design methodology to find out how they can contribute to fulfil the features needed by this particular DW approach. To provide a formal framework to classify existing work, they provide a study of differences between classical DW users and volunteers. The paper also presents a set of open issues for VDW.

Automated heuristic based context dependent ETL process to generate multi‐dimensional model for tabular data

“…The major objective of DAREF was to elicit the requirements of DW using SGAP (Strategic Goal Analytic Process) and Goal Cases for realizing the MD representation. Sakka et al 22 presented a state‐of‐art based on volunteer DW. With the development of CS (Crowdsourcing Systems), possibilities for newer analysis appear in which volunteers emphasize a key role with daily experience.…”