Quarry: A User-centered Big Data Integration Platform
| Autor: | Besim Bilalli, Alberto Abelló, Petar Jovanovic, Sergi Nadal, Oscar Romero |
|---|---|
| Přispěvatelé: | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació, Universitat Politècnica de Catalunya. Doctorat Erasmus Mundus en Tecnologies de la Informació per a la Intel·ligència Empresarial, Universitat Politècnica de Catalunya. inSSIDE - integrated Software, Service, Information and Data Engineering, Universitat Politècnica de Catalunya. IMP - Information Modeling and Processing |
| Rok vydání: | 2020 |
| Předmět: |
Computer Networks and Communications
Computer science Informàtica::Sistemes d'informació [Àrees temàtiques de la UPC] Interface (computing) Visualització de la informació Big data 02 engineering and technology computer.software_genre Theoretical Computer Science Data modeling Information visualization 020204 information systems 0502 economics and business 0202 electrical engineering electronic engineering information engineering Metadata business.industry Macrodades 05 social sciences Integration platform Data-intensive flows Data science Visualization Variety (cybernetics) Data integration 050211 marketing business computer Software Information Systems |
| Zdroj: | UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) |
| ISSN: | 1572-9419 1387-3326 |
| Popis: | Obtaining valuable insights and actionable knowledge from data requires cross-analysis of domain data typically coming from various sources. Doing so, inevitably imposes burdensome processes of unifying different data formats, discovering integration paths, and all this given specific analytical needs of a data analyst. Along with large volumes of data, the variety of formats, data models, and semantics drastically contribute to the complexity of such processes. Although there have been many attempts to automate various processes along the Big Data pipeline, no unified platforms accessible by users without technical skills (like statisticians or business analysts) have been proposed. In this paper, we present a Big Data integration platform (Quarry) that uses hypergraph-based metadata to facilitate (and largely automate) the integration of domain data coming from a variety of sources, and provides an intuitive interface to assist end users both in: (1) data exploration with the goal of discovering potentially relevant analysis facets, and (2) consolidation and deployment of data flows which integrate the data, and prepare them for further analysis (descriptive or predictive), visualization, and/or publishing. We validate Quarry’s functionalities with the use case of World Health Organization (WHO) epidemiologists and data analysts in their fight against Neglected Tropical Diseases (NTDs). This work is partially supported by GENESIS project, funded by the Spanish Ministerio de Ciencia, Innovación y Universidades under project TIN2016-79269-R. |
| Databáze: | OpenAIRE |
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