Saturday, January 25, 2014

Nist data symposium

Nist is looking into Big data and measurement thereof. Upcoming is a symposium in March. Symposium Topics:
Understanding the Data Science Technical Landscape:
Primary challenges in and technical approaches to complex workflow components of Big Data systems, including ETL, lifecycle management, analytics, visualization & human-system interaction.
Major forms of analytics employed in data science.
Improving Analytic System Performance via Measurement Science
Generation of ground truth for large datasets and performance measurement with limited or no ground truth.
Methods to measure the performance of data analytic workflows where there are multiple subcomponents, decision points, and human interactions.
Methods to measure the flow of uncertainty across complex data analytic systems.
Approaches to formally characterizing end-to-end analytic workflows.
Datasets to Enable Rigorous Data Science Research
Useful properties for data science reference datasets.
Leveraging simulated data in data science research.
Efficient approaches to sharing research data.

http://www.nist.gov/itl/iad/data-science-symposium-2014.cfm

Saturday, January 11, 2014

IBM shows its plan to move Watson forward

The IBM Watson supercomputer has garnered a lot of attention in recent years, but it's entering a particularly critical passage now. What happens next could influence the future paths of data analytics generally, and IBM specifically -- for better or for worse. This week, IBM showed its plan to move Watson forward. Virginia Rometty, the company's chairman, president and CEO, said IBM would invest more than $1 billion in a new business group dedicated to commercializing Watson. That figure includes $100 million for venture investments to create an ecosystem of application developers and other business partners. The challenge, though, will be to take highly technical machine learning software from the lab -- and the game show milieu -- to the business mainstream.

 http://searchdatamanagement.techtarget.com/opinion/For-IBM-Watson-no-easy-answers-on-commercial-cognitive-computing