Given the explosion of data production, storage capabilities, communications technologies, computational power, and supporting infrastructure, data science is now recognized as a highly-critical growth area with impact across many sectors including science, government, finance, health care, manufacturing, advertising, retail, and others. Since data science technologies are being leveraged to drive crucial decision making, it is of paramount importance to be able to measure the performance of these technologies and to correctly interpret their output. The NIST Information Technology Laboratory is forming a cross-cutting data science program focused on driving advancements in data science through system benchmarking and rigorous measurement science.
Ashit Talukder (NIST), John Garofolo (NIST), Mark Przybocki (NIST), Craig Greenberg (NIST)
Call For Abstracts:
Participants who wish to give presentations of their technical perspectives or present posters (potentially with technical demonstrations) that address symposium topics should submit a brief one-page abstract and brief one-paragraph bio to firstname.lastname@example.org by February 21st, 2014 (those abstracts received after January 10th, 2014 will only be considered for poster presentations). Those who submit abstracts by January 10th will be notified whether their perspectives have been selected for plenary or poster presentation by January 31st. Those submitting abstracts after January 10th and prior to February 21st will be notified whether their perspectives have been selected for a poster presentation on a rolling basis sometime between February 1st and March 1st. Speakers, panelists, and poster presenters will be selected by the organizers based on relevance to symposium objectives and workshop balance. Due to the technical nature of the symposium, no marketing will be permitted.
Understanding the Data Science Technical Landscape:
Improving Analytic System Performance via Measurement Science
Datasets to Enable Rigorous Data Science Research
The inaugural NIST Data Science Symposium will convene a diverse multi-disciplinary community of stakeholders to promote the design, development, and adoption of novel measurement science in order to foster advances in Big Data processing, analytics, visualization, interaction, and lifecycle management. It is set apart from related symposia by our emphasis on advancing data science technologies through:
Start Date: Tuesday, March 4, 2014
End Date: Wednesday, March 5, 2014
Location: NIST campus in Gaithersburg, MD.
Registration to attend the NIST Data Science Symposium is now open. Registration is free, but it is necessary to register in order to attend. The deadline for registration will be on or before Friday, February 21st. Registration may close once the capacity of the venue is reached. Please note that only registered participants will be permitted to enter the NIST campus to attend the symposium. To register, please go to: https://www-s.nist.gov/CRS/conf_disclosure.cfm?conf_id=6631
The main NIST campus is located in Gaithersburg, MD approximately 20 miles outside of Washington, DC. Useful travel information, including transportation to NIST as well nearby hotels and restaurants, can be found here: http://www.nist.gov/public_affairs/visitor/index.cfm.
Several local hotels are listed here: http://www.nist.gov/public_affairs/visitor/hotels.cfm.
Note, both the Hilton and Holiday Inn offer buses to and from NIST. There is not a conference hotel associated with this symposium.
Access to NIST: ·
All symposium registrants will be pre-approved for access to NIST. 2-3 days prior to the event NIST Conference Facilities will send by e-mail conference “dash-passes”. Please print and bring the dash-pass with you on March 4 & 5 for easy entrance to the NIST campus. This forthcoming e-mail will provide everything a visitor needs to know in order to arrive, enter, park, and find their way to the NIST Red Auditorium.
Presenters are asked to provide presentation materials and to identify special presenting needs to NIST by 2/21. These materials may be sent directly to email@example.com. All posters should be designed to be no greater than 45 (width) x 65 (height). Additional guidelines for poster and oral session presenters will be made available shortly.
Please address additional logistic questions to firstname.lastname@example.org.
NIST maintains a general mailing list for our Data Science Measurement and Evaluation program. To join this list, please email us using mailto:email@example.com?subject=subscribe
Relevant information is posted to this list. If you have any question for NIST related to our data science program, please email us at: