NDLI: SourceSight: Enabling Effective Source Selection

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SourceSight: Enabling Effective Source Selection

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SourceSight: Enabling Effective Source Selection

Content Provider	ACM Digital Library
Author	Rekatsinas, Theodoros Srivastava, Divesh Deshpande, Amol Dong, Xin Luna Getoor, Lise
Abstract	Recently there has been a rapid increase in the number of data sources and data services, such as cloud-based data markets and data portals, that facilitate the collection, publishing and trading of data. Data sources typically exhibit large heterogeneity in the type and quality of data they provide. Unfortunately, when the number of data sources is large, it is difficult for users to reason about the actual usefulness of sources for their applications and the trade-offs between the benefits and costs of acquiring and integrating sources. In this demonstration we present \textsc{SourceSight}, a system that allows users to interactively explore a large number of heterogeneous data sources, and discover valuable sets of sources for diverse integration tasks. \textsc{SourceSight}~uses a novel multi-level source quality index that enables effective source selection at different granularity levels, and introduces a collection of new techniques to discover and evaluate relevant sources for integration.
Starting Page	2157
Ending Page	2160
Page Count	4
File Format	PDF
ISBN	9781450335317
DOI	10.1145/2882903.2899403
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-06-26
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Sourcesight
Content Type	Text
Resource Type	Article

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