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ORCIDBig Data, Volume 1
Volume 1, Number 1, March 2013
- Edd Dumbill:
Making Sense of Big Data. 1-2
- Robert Kirkpatrick:
Big Data for Development. 3-4
- Edd Dumbill:
The Human Face of Big Data: An Interview with Rick Smolan. 5-9 - Edd Dumbill:
Big Data and Thought Crime: An Interview with Jim Adler. 10-13
- Dino Citraro:
On Visualization. 14-17 - Jim Hendler
:
Broad Data: Exploring the Emerging Web of Data. 18-20
- Edd Dumbill, Elizabeth D. Liddy, Jeffrey M. Stanton, Kate Mueller, Shelly Farnham:
Educating the Next Generation of Data Scientists. 21-27
- Jimmy Lin:
Mapreduce is Good Enough?If All You Have is a Hammer, Throw Away Everything That's Not a Nail! 28-37 - Bob DuCharme:
What Do RDF and SPARQL bring to Big Data Projects? 38-41 - Roger Higdon, Winston Haynes, Larissa Stanberry, Elizabeth Stewart, Gregory Yandl, Chris Howard, William Broomall, Natali Kolker, Eugene Kolker:
Unraveling the Complexities of Life Sciences Data. 42-50 - Foster J. Provost, Tom Fawcett:
Data Science and its Relationship to Big Data and Data-Driven Decision Making. 51-59 - Chaitanya K. Baru, Milind A. Bhandarkar, Raghunath Nambiar, Meikel Poess, Tilmann Rabl:
Benchmarking Big Data Systems and the BigData Top100 List. 60-64
- Daniel Tunkelang, Robert Capra, Gene Golovchinsky, Bill Kules, Catherine L. Smith, Ryen White:
Symposium on Human-Computer Information Retrieval. 65-70
Volume 1, Number 2, June 2013
- Edd Dumbill:
Big Data is Rocket Fuel. 71-72
- Edd Dumbill:
A Revolution That Will Transform How We Live, Work, and Think: An Interview with the Authors of Big Data. 73-77 - Dino Citraro:
Expanding Real-Time Data Insight at PARC. 78-81
- Jim Hendler:
Peta Vs. Meta. 82-84
- Melanie Swan:
The Quantified Self: Fundamental Disruption in Big Data Science and Biological Discovery. 85-99
- Michael Hausenblas, Jacques Nadeau:
Apache Drill: Interactive Ad-Hoc Analysis at Scale. 100-104 - Michael Gold, Ryan G. McClarren, Conor Gaughan:
The Lessons Oscar Taught Us: Data Science and Media & Entertainment. 105-109 - Brian Dalessandro:
Bring the Noise: Embracing Randomness Is the Key to Scaling Up Machine Learning Algorithms. 110-112
Volume 1, Number 3, September 2013
- Edd Dumbill, Sophie Mohin:
Opportunities at the Intersection of Health and Data. 115-116
- Gina Neff:
Why Big Data Won't Cure Us. 117-123 - Salvatore Iaconesi:
La Cura, An Open Source Cure for Cancer. 124-129 - Kim Rees, Dino Citraro:
When the Battle Doesn't End at Home. 130-133
- Edd Dumbill:
Big Data in Aging Research: An Interview with Aubrey de Grey. 134-136
- K. Krasnow Waterman, Jim Hendler:
Getting the Dirt on Big Data. 137-140
- Ajit Narayanan, Michael Greco, Helen Powell, Louise Coleman:
The Reliability of Big "Patient Satisfaction" Data. 141-151 - Paul S. Bradley:
Implications of Big Data Analytics on Population Health Management. 152-159 - Shawndra Hill, Raina M. Merchant, Lyle H. Ungar:
Lessons Learned About Public Health from Online Crowd Surveillance. 160-167
- Meredith A. Barrett, Olivier Humblet, Robert Hiatt, Nancy E. Adler:
Big Data and Disease Prevention: From Quantified Self to Quantified Communities. 168-175
- Vijay Srinivas Agneeswaran, Joydeb Mukherjee, Ashutosh Gupta, Pranay Tonpay, Jayati Tiwari, Nitin Agarwal:
Real-Time Analytics for the Healthcare Industry: Arrhythmia Detection. 176-182
- Meghan F. Coakley, Maarten R. Leerkes, Jason Barnett, Andrei E. Gabrielian, Karlynn Noble, Nick Weber, Yentram Huyen:
Unlocking the Power of Big Data at the National Institutes of Health. 183-186 - Elizabeth Stewart, Todd Smith, Andrea De Souza, Jack Faris, Lennart Martens, Sophie Mohin, Vural Özdemir, Courtney MacNealy-Koch, Eugene Kolker:
Delsa Workshop IV: Launching the Quantified Human Initiative. 187-190
Volume 1, Number 4, December 2013
- Edd Dumbill:
The End of Data, and Its Beginning. 191-192
- Gregory Piatetsky-Shapiro:
Comment on "A Revolution That Will Transform How We Live, Work, and Think: An Interview with the Authors of Big Data". 193 - Abe Gong:
Comment on "Data Science and its Relationship to Big Data and Data-Driven Decision Making". 194
- Edd Dumbill, Eugene Kolker:
Introducing a Metadata Checklist for Omics Data. 195
- Eugene Kolker, Vural Özdemir, Lennart Martens, William Hancock, Gordon A. Anderson, Nathaniel Anderson, Sukru Aynacioglu, Ancha V. Baranova, Shawn R. Campagna, Rui Chen, John Choiniere, Stephen P. Dearth, Wu-Chun Feng, Lynnette Ferguson, Geoffrey C. Fox, Dmitrij Frishman, Robert Grossman, Allison P. Heath, Roger Higdon, Mara H. Hutz, Imre Janko, Lihua Jiang, Sanjay Joshi, Alexander E. Kel, Joseph W. Kemnitz, Isaac S. Kohane, Natali Kolker, Doron Lancet, Elaine Lee, Weizhong Li, Andrey Lisitsa, Adrian Llerena, Courtney MacNealy-Koch, Jean-Claude Marshall, Paola Masuzzo, Amanda May, George Mias, Matthew E. Monroe, Elizabeth Montague, Sean D. Mooney, Alexey I. Nesvizhskii, Santosh Noronha, Gilbert S. Omenn, Harsha Rajasimha, Preveen Ramamoorthy, Jerry Sheehan, Larry Smarr, Charles V. Smith, Todd Smith, Michael Snyder, Srikanth Rapole, Sanjeeva Srivastava, Larissa Stanberry, Elizabeth Stewart, Stefano Toppo, Peter Uetz, Kenneth Verheggen, Brynn H. Voy, Louise Warnich, Steven W. Wilhelm, Gregory Yandl:
Toward More Transparent and Reproducible Omics Studies Through a Common Metadata Checklist and Data Publications. 196-201 - Michael Snyder, George Mias, Larissa Stanberry, Eugene Kolker:
Metadata Checklist for the Integrated Personal Omics Study: Proteomics and Metabolomics Experiments. 202-206
- Vijay Srinivas Agneeswaran, Pranay Tonpay, Jayati Tiwary:
Paradigms for Realizing Machine Learning Algorithms. 207-214
- Enric Junqué de Fortuny, David Martens, Foster J. Provost:
Predictive Modeling With Big Data: Is Bigger Really Better? 215-226 - Élénie Godzaridis, Sébastien Boisvert, Fangfang Xia, Mikhail Kandel, Steve Behling, Bill Long, Carlos P. Sosa, François Laviolette, Jacques Corbeil:
Human Analysts at Superhuman Scales: What Has Friendly Software To Do? 227-236
- Roger Higdon, Elizabeth Stewart, Jared C. Roach, Caroline Dombrowski, Larissa Stanberry, Holly Clifton, Natali Kolker, Gerald van Belle, Mark A. Del Beccaro, Eugene Kolker:
Predictive Analytics In Healthcare: Medications as a Predictor of Medical Complexity. 237-244 - Lauren E. Sweet, Heather Lea Moulaison:
Electronic Health Records Data and Metadata: Challenges for Big Data in the United States. 245-251
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