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Presentations - 2014 NIST Data Science Symposium

Challenges and Gaps in Data Science Technologies

Doug Cutting

Chief Architect, Cloudera

The Future of Data

Pak Chung Wong

Chief Scientist, Pacific Northwest National Laboratory

Top Challenges of Extreme-Scale Visual Analytics

Volker Markl

Professor, TU Berlin

Data Science from a Data Management Perspective


Data and Use Cases for Data Science Research

Philip Ashlock

Chief Architect,, GSA

Datasets that Enable Rigorous Data Science Research

Michael Hurley

Technical Staff, MIT Lincoln Laboratory

Information Theoretic Evaluation of Data Processing Systems

Chesley Richards

CDC Deputy Director for Public Health Scientific Services

Public Health Data, Challenges and Opportunities

The NIST Data Science Program and Symposium Objectives

Ashit Talukder and Craig Greenberg

Data Science Program

Data Science Benchmarking and Measurement

Thomas Karl

Director, NOAA's National Climatic Data Center

Climate Archives in NOAA: Challenges and Opportunities

Shahram Ghandeharizadeh

Director of Database Lab Computer Science Department, University of Southern California

Benchmarking Interactive Social Networking Actions

Shashi Shekhar

McKnight Distinguished University Professor

Spatial Data Science: Challenges & Opportunities

Milind Bhandarkar

Chief Scientist, Pivotal Software

Deep Analytics Pipeline: A Benchmark Proposal


Francine Berman

Chair, Research Data Alliance / U.S.

Got Data? Sustaining the Engine for Data-Driven Innovation

Government panel

Michael Huerta

Associate Director, National Library of Medicine

The NIH Big Data to Knowledge Initiative

Lucy Nowell

Program Manager, Department of Energy

Science & Data at Extreme Scale

Stephen Dennis

Innovation Director, HSARPA

Department of Homeland Security Science & Technology - Big Data Analytics

Xiaoming Huo

NSF Program Director

NSF Funding Opportunities in Data Science


Breakout reports

Data Science Benchmarking & Performance Measurement

Datasets and Use Cases for Data Science Research

Challenges and Gaps in Data Science Technologies 

Poster Session

Focus Group: Automated Metadata and Ontologies for Heterogeneous Data

Focus Group: HCI and Data Science

Focus Group: Big Data Analytics for Smart Manufacturing Systems

Created March 7, 2014, Updated May 8, 2014