LabBook: Metadata-driven Social Collaborative Data Analysis

被引:0
作者
Kandogan, Eser [1 ]
Roth, Mary [1 ]
Schwarz, Peter [1 ]
Hui, Joshua [1 ]
Terrizzano, Ignacio [1 ]
Christodoulakis, Christina [2 ]
Miller, Renee J. [2 ]
机构
[1] IBM Res Almaden, San Jose, CA USA
[2] Univ Toronto, Dept Comp Sci, Toronto, ON, Canada
来源
PROCEEDINGS 2015 IEEE INTERNATIONAL CONFERENCE ON BIG DATA | 2015年
关键词
metadata; collaboration; data discovery; data analytics; VISUALIZATIONS; ENTERPRISE;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Open data analysis platforms are being adopted to support collaboration in science and business. Studies suggest that analytic work in an enterprise occurs in a complex ecosystem of people, data, and software working in a coordinated manner. These studies also point to friction between the elements of this ecosystem that reduces user productivity and quality of work. LabBook is an open, social, and collaborative data analysis platform designed explicitly to reduce this friction and accelerate discovery. Its goal is to help users leverage each other's knowledge and experience to find the data, tools and collaborators they need to integrate, visualize, and analyze data. The key insight is to collect and use more metadata about all elements of the analytic ecosystem by means of an architecture and user experience that reduce the cost of contributing such metadata. We demonstrate how metadata can be exploited to improve the collaborative user experience and facilitate collaborative data integration and recommendations. We describe a specific use case and discuss several design issues concerning the capture, representation, querying and use of metadata.
引用
收藏
页码:431 / 440
页数:10
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