ABSTRACT
Data exploration encompasses a variety of interaction types and data functionality, such as search, data analysis, curation, constraint satisfaction, data mining, and visualization. Data exploration naturally begins when a user is given a set of data and ends when the user extracts all information and knowledge hidden in the data. Although a plethora of systems have been developed to tackle different data exploration aspects, there is no framework devoted to it as a whole. In this paper, we claim that "any" user-data interaction is essential for data exploration and sketch a prototype with both automated and user-induced functionality.
- Kandel, S., Paepcke, A., Hellerstein, J., and Heer, J. Wrangler: Interactive Visual Specification of Data Transformation Scripts. CHI, May 2011. DOI=http://doi.acm.org/10.1145/1979444. Google ScholarDigital Library
- Trifacta, http://www.trifacta.com/Google Scholar
- Stonebraker, M., et al. Data Curation at Scale: The Data Tamer System. Proc. of the 6th Biennial Conf. on Innovative Data Systems Research, Jan 2013.Google Scholar
- Tamr Inc., http://www.tamr.com/Google Scholar
- Dallachiesa, M., et al. NADEEF: A Commodity Data Cleaning System. SIGMOD Conference, (Jun. 2013). DOI=http://doi.acm.org/10.1145/2465327. Google ScholarDigital Library
- Ebaid, A., et al. NADEEF: A Generalized Data Cleaning System. Proc. of the VLDB Conf, Aug. 2013. DOI=http://doi.acm.org/10.1145/2536280. Google ScholarDigital Library
- Chu, X., et al. KATARA: A Data Cleaning System Powered by Knowledge Bases and Crowdsourcing. Proc. SIGMOD Conf., June 2015. DOI=http://doi.acm.org/10.1145/2749431. Google ScholarDigital Library
- Chu, X., et al. KATARA: Reliable Data Cleaning with Knowledge Bases and Crowdsourcing. Proc. VLDB Conf., Aug. 2015. DOI=http://doi.acm.org/10.1145/2824109. Google ScholarDigital Library
- OpenRefine, http://openrefine.org/Google Scholar
- Google Sheets, https://www.google.com/sheets/about/Google Scholar
- Ioannidis, Y., et al. Profiling Attitudes for Personalized Information Provision. IEEE Data Eng. Bulletin, 34(2), 2011. DOI=http://sites.computer.org/debull/A11june/Yannis.pdfGoogle Scholar
Index Terms
- Data exploration: a roll call of all user-data interaction functionality
Recommendations
Overview of Data Exploration Techniques
SIGMOD '15: Proceedings of the 2015 ACM SIGMOD International Conference on Management of DataData exploration is about efficiently extracting knowledge from data even if we do not know exactly what we are looking for. In this tutorial, we survey recent developments in the emerging area of database systems tailored for data exploration. We ...
A RESTful architecture for data exploration as a service
SAC '19: Proceedings of the 34th ACM/SIGAPP Symposium on Applied ComputingData analysis process typically starts in an exploration phase, where the goal is to gain an understanding of the underlying data. In this phase, analysts make multiple queries and expect answers from the data services. Existing data services do not ...
Interactive data exploration using semantic windows
SIGMOD '14: Proceedings of the 2014 ACM SIGMOD International Conference on Management of DataWe present a new interactive data exploration approach, called Semantic Windows (SW), in which users query for multidimensional "windows" of interest via standard DBMS-style queries enhanced with exploration constructs. Users can specify SWs using (i) ...
Comments