Collaborative Data Analytics with DataHub

By Anant P. Bhardwaj, Amol Deshpande, Aaron J. Elmore, David R Karger, Samuel Madden, Aditya G. Parameswaran, H. Subramanyam, Eugene Wu, Rebecca Zhang. 2015

57 citations recorded by the source corpus.

While there have been many solutions proposed for storing and analyzing large volumes of data, all of these solutions have limited support for collaborative data analytics, especially given the many individuals and teams are simultaneously analyzing, modifying and exchanging datasets, employing a number of heterogeneous tools or languages for data analysis, and writing scripts to clean, preprocess, or query data. We demonstrate DataHub, a unified platform with the ability to load, store, query, collaboratively analyze, interactively visualize, interface with external applications, and share datasets. We will demonstrate the following aspects of the DataHub platform: (a) flexible data storage, sharing, and native versioning capabilities: multiple conference attendees can concurrently update the database and browse the different versions and inspect conflicts; (b) an app ecosystem that hosts apps for various data-processing activities: conference attendees will be able to effortlessly ingest, query, and visualize data using our existing apps; (c) thrift-based data serialization permits data analysis in any combination of 20+ languages, with DataHub as the common data store: conference attendees will be able to analyze datasets in R, Python, and Matlab, while the inputs and the results are still stored in DataHub. In particular, conference attendees will be able to use the DataHub notebook — an IPython-based notebook for analyzing data and storing the results of data analysis.

Subfields: Computer Networks and Communications, Information Systems, Information Systems and Management

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Yuji Roh
2. Geon Heo
3. Steven Euijong Whang
4. Peter Christen

In Information Systems

1. Geon Heo
2. Yuji Roh
3. Steven Euijong Whang

Citations in the corpus

• A Survey on Data Collection for Machine Learning: A Big Data - AI Integration Perspective (2018, background): “Data discovery Sharing Collaborative Analysis [9], [10], [11] Web [12], [13], [14], [15], [16], [17] Collaborative and Web [18]”
• Goods: Organizing Google's Datasets (2016, unknown): “DataHub [8, 9, 10] is a collaborative version-management system for datasets that is similar in spirit to software version control”