Full paper available at: http://dx.doi.org/10.1145/3035918.3058730
Title: The VADA Architecture for Cost-Effective Data Wrangling
Abstract: Data wrangling, the multi-faceted process by which the data required by an application is identified, extracted, cleaned and integrated, is often cumbersome and labor intensive. In this paper, we present an architecture that supports a complete data wrangling lifecycle, orchestrates components dynamically, builds on automation wherever possible, is informed by whatever data is available, refines automatically produced results in the light of feedback, takes into account the user’s priorities, and supports data scientists with diverse skill sets. The architecture is demonstrated in practice for wrangling property sales and open government data.
Citation: Nikolaos Konstantinou, Martin Koehler, Edward Abel, Cristina Civili, Bernd Neumayr, Emanuel Sallinger, Alvaro AA Fernandes, Georg Gottlob, John A Keane, Leonid Libkin, Norman W Paton: "The VADA Architecture for Cost-Effective Data Wrangling". Proceedings of the 2017 ACM International Conference on Management of Data (SIGMOD 2017), Chicago, IL, USA, May 14 - 19, 2017, 1599-1602.
03:12 data context
05:34 user context