Big Data Initiative Workshop
Registration is closed.
Big data is much more than just data bits and bytes on one side and processing on the other. IEEE, through its Cloud Computing Initiative and multiple Societies have already been taking the lead on the technical aspects of big data. To provide increased value, IEEE will provide a framework for collaboration throughout IEEE.
A two day workshop to facilitate the discussion on the definition, scope and potential structure will be held on the 1st and 2nd October at the Stevens Institute of Technology, located in Hoboken, New Jersey. Stevens Institute is hosting the first IEEE Big Data Initiative Workshop. The Stevens campus is situated high on a bluff overlooking the Hudson River and the Manhattan skyline. http://www.stevens.edu/sit/
Workshop Topics to include, but not limited to the following:
1. Perspectives from various IEEE societies and other organizations.
2. Big Data is much more that bits on one side and processing on the other. As we enter the 5 Vs we are confronted with:
- Volume: can present architectures scale to crunch the volume of data involved.
- Velocity: the rapid and asynchronous change in data over several sources makes consistency a major issue, and replication basically impossible.
- Variety: differences are deeper than the expression of independent values based on different metrics. They relate to differences in the capturing of those values, in their stability, in the credibility of the sources…..
- Value: who is benefiting from the metadata, how are data sources rewarded, who is accountable?
- Virtualization: this might be happening in the IoT where you don’t actually have Volume, nor Velocity, nor Variety in principle since in IoT a lot is happening locally. However the challenge for the future is to consider all of data spread around and look at them as a "virtual Big Data".
- We would like to dedicate a deeper investigation of the Vs' implication and see a small group of discussant bringing different perspectives to the floor to extend the discussion to the audience with a resulting list of actions that this initiative will need to take.
3. How can we better understand Big Data. In the end we, humans, should be able to make sense of Big Data and for that we need to look at meta information and to their visualization rendering.
- What are the technologies for generating metadata (data analytics), what are the technologies for rendering (visualization).
- How can we trust the outcome - Psychology of Perception.
- How does the value shift from data to metadata, who is benefiting?
4. It is about Big or it is about Meta?
- In IEEE, we probably don’t have Big Data based on the first 3 Vs. On the other hand also the genome is not a Big Data with respect to the 3 Vs. But if we look at the set of sets, i.e. correlation, then in both cases we have meta data generation and we can relate to Big Data issues.
- How can we generate meta information from IEEE data?
- What are the changes needed to better exploit the IEEE data ecosystem?
- What are the hurdles to solve? Can we identify a trial?
- How about addressing emerging information, semantics, behaviors?
Time will be given for a lively discussion on all the above topics.
|Wednesday, 1 October 2014|
|9 am||Welcome & Opening Remarks||
George P. Korfiatis, Provost and University Vice President, Stevens Institute of Technology
Mahmoud Daneshmand, Professor, Howe School of Technology Management, Stevens Institute of Technology
|9:15 am||Introductions and IEEE Big Data Initiative||
Roberto Saracco, President of EIT ICTLABS and IEEE Future Directions Committee Chair
Kathy Grise, IEEE Senior Program Director
|9:30 am||Setting the Stage for Big Data||Roberto Saracco, President of EIT ICTLABS and IEEE Future Directions Committee Chair||BC204|
|10 am||23 Computing TechnologiesThat Will Shape the World in 2022: Towards a Seamless Intelligence, by Dejan Milojicic, Jacek Zurada||
Jacek Zurada, University Scholar and Professor, Department of Electrical and Computer Engineering
University of Louisville, IEEE VP – Technical Activities
|10:30 am||Analytics for Big Data||Jose' Moura, Professor, Electrical and Computer Engineering Department, and BioMedical Engineering Department, Carnegie Mellon University||BC204|
|11:15 am||Evolving Big Data Use Cases and Technologies: Opportunities and Challenges||Mark Davis, Distinguished Engineer - Dell||BC104|
|12 pm||Lunch||BC Atrium|
|1 pm||IEEE Engineering in Medicine and Biology Society Big Data Interests||Andrew Laine, Professor of Biomedical Engineering, Columbia University, President-Elect - IEEE Engineering in Medicine and Biology Society (EMBS)||BC204|
|1:45 pm||What’s Next for Big Data||Dave Belanger, Senior Research Fellow, Howe School of Technology Management, Stevens Institute of Technology||BC204|
|2:30 pm||IEEE Computational Intelligence Society Perspectives||Xin Yao, Professor of Computer Science, School of Computer Science, University of Birmingham, Director of the Centre of Excellence for Research in Computational Intelligence and Applications (CERCIA), President - IEEE Computational Intelligence Society||BC204|
|3:15 pm||IEEE Reliability Society Perspectives||Christian Hansen, Head of School of Computing and Engineering Sciences, Eastern Washington University, President - IEEE Reliability Society||BC204|
|4 pm||Dean's Seminar Series: Engineering Problem Solving Beyond Math - Almost||Pete Shainin, CEO and CTO of the Shainin group||BC122|
|6 pm||Networking Reception and Dinner||All||BC Atrium|
|Thursday, 2 October 2014|
|8:30 am||Day 1 Recap||Roberto Saracco, President of EIT ICTLABS and IEEE Future Directions Committee Chair||BC104|
|8:45 am||What's Next for Big Data Analytics and IEEE Sensors Council Perspectives||Mahmoud Daneshmand, Professor, Howe School of Technology Management, Stevens Institute of Technology||BC104|
|9:15 am||Connecting Big Data with Data Analytics and IEEE Computer Society Perspectives||Ling Liu, Professor, College of Computing at Georgia Tech||BC104|
|10 am||Discussion: Big Data is much more that bits on one side and processing on the other. How can we better understand Big Data.||Steve Diamond, General Manager, Industry Standards Office and Global Standards Officer, EMC Corporation||BC104|
|11:15 am||Wrap-up, Next Steps||All||BC104|
|12 pm||Close Workshop||BC104|
Getting to the Workshop: Directions and Logistics
On behalf of IEEE and Stevens Institute of Technology, we are delighted to have you attend the workshop. Please note that the workshop in its entirety will be held at the Babbio Center, located at River Street between 5th Street and 6th Street, Hoboken, NJ 07030. Registration will be located in the Atrium. The workshop will start promptly at 9 am ET, Wednesday, 1 October 2014. We will also have a dinner reception in the Atrium the evening of Wednesday, 1 October 2014.
If you decide to park on the street in Hoboken, pay very close attention to the parking signs. Parking in Resident Only spaces, streets scheduled for cleaning, or parking for over the four-hour visitor limit will result in your car being ticketed, booted or towed.
B (at Second Street, between River and Hudson)
D (at 215 Hudson Street, between 2nd and 3rd)
G (at 315 Hudson Street, between 3rd and 4th)
* Rates are subject to change.
Up to 1 hour: $3.00
Up to 2 hours: $4.00
Up to 4 hours: $7.00
Up to 6 hours: $10.00
Walking Directions to Campus from Hudson Street Parking Garages:
Proceed to Hudson Street and turn right onto Hudson. At Fourth Street, you will come to a park. Cut diagonally through the park, on the other side, on Fifth Street, is the Edwin A. Stevens and McLean Buildings. There is a campus map on River Street side of the Edwin A. Stevens building or click here for a Campus Map.
From New York
Take NJ Transit Bus No. 126, or the Academy Bus, from the Port Authority Bus Terminal at 8th Ave. and 40th Street. The bus goes directly to Hoboken and travels down Washington Street. From New York City, buses stop on even numbered streets. Please exit at 8th Street for main campus or 6th Street for academic buildings and walk east across Washington Street.
Take Port Authority Trans Hudson (PATH) subway, marked Hoboken. Single ride tickets are $2.25. For more information on fares click here. Stations are located on 6th Avenue at 33rd, 23rd, 14th, and 9th Streets, and at Christopher Street. Once in Hoboken, take a local Washington Street bus, taxi ($5) or walk uptown to 6th Street and turn right (east) for the campus.
Take a NYWaterway ferry from Pier A at Battery Park, Pier 11 on Wall Street in Manhattan, the World Financial Center in Downtown Manhattan, or Pier 78 (weekends only) at West 38th Street and 12th Avenue in Manhattan to the Hoboken South Terminal. From the Hoboken South Terminal take a local Washington Street bus, taxi ($5) or walk uptown to 6th Street and turn right (east) for the campus.
Ferries from Pier 78 (everyday) also arrive at the Hoboken North Terminal (13th Street). From the Hoboken North Terminal take a local Washington Street bus, taxi ($5) or walk downtown to 8th Street and turn left (east) for the campus.
From Points West of the Hudson River
Use Newark International Airport. Cabs are available from the airport, and the fares are stated at the Airport terminal taxi stand. Please check with the uniformed taxi dispatcher. A complete list of Ground Transportation Services is also available. Or else take "Airlink" (NJ Transit bus service, 1-800-772-2222) from the airport to Penn Station, Newark. Then go by PATH train to Grove, Jersey City, and switch to the train for Hoboken.
Connections may be made in Journal Square, Jersey City, for Downtown Bus no. 5-6 marked Jersey City-Weehawken, to Washington Street in Hoboken. Northbound buses on Washington Street stop on odd number streets. You would have to exit at 7th Street and walk one block north, or at 9th Street and walk one block south, before turning east on 8th Street and heading up the hill towards the Howe Center.
Many NJ Transit trains stop in Hoboken. Other NJ Transit and Amtrak train lines stop in Newark. From Newark, Mon through Fri, take a PATH train to Grove, Jersey City, and switch to the Hoboken train, as explained above.