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Bits 'n Pieces on Big Data
Innovative information and insight into Big Data (if you like the content, please consider donating to my bitcoin address #3Pjof6N9xRAYXXSPZ4EAFLfHGn51ZdPcxi)
Curated by onur savas
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The LinkedIn Economic Graph Challenge

The LinkedIn Economic Graph Challenge | Bits 'n Pieces on Big Data |
How would you use data from LinkedIn to solve the world's economic challenges and create economic opportunities for people? Submit your proposals to the LinkedIn Economic Graph Challenge.
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Web Science 2014 Data Challenge

Web Science 2014 Data Challenge | Bits 'n Pieces on Big Data |

The web has generated huge amounts of data at massive
scale, but making sense of these datasets and representing them in a
compact and easily-interpretable way remains very difficult. The goal
of this challenge is to encourage innovative visualizations of web
data.  To enable this visualization, the following several large-scale, easy-to-use, publicly-available datasets are prepared:

1. Web traffic data, including more than 200 million HTTP requests
from browsers to servers;
2. Twitter data, including a sample of more than 22 million tweets;
3. Social bookmarking data, consisting of about 430,000 bookmarked pages;
4. Co-authorship of academic papers, consisting of about 21.5 million papers
and 10.8 million authors

onur savas's insight:

1. For fairness, the visualization must be primarily based on the data
that we provide. Other datasets may be used to augment ours, but these
datasets must be publicly-available and described in detail in the
documentation (see #4 below).

2. The visualization must be a static image, and must be submitted as
a PDF. In addition to the main PDF, please submit a PNG version at a
resolution of about 640x480, for display on web pages, social media
sites, mobile devices, etc. This PNG version need not contain the full
visualization, but should be an appropriate representation (e.g. a
subset of the full PDF).

3. Please include a separate PDF file containing a description of the
visualization, including: (1) name(s), affiliation(s), and contact
information of the creator(s), (2) the purpose of the visualization,
(3) which dataset(s) were used, (4) a brief description of how the
visualizations was created, and (5) any other information you would
like to share with the judges.

4. By submitting your visualization, you agree to allow us to display
your visualization at the conference and on the Web Science website
and social media channels. (We will give proper attribution, of
course.) You also certify that you are the copyright holder of the
visualization and are authorized to give us this permission.

5. Entries are due by 11:59PM Hawaii time on April 15, 2014. Please
e-mail your entry to David Crandall. (If you do not receive a
confirmation email within 24 hours, your entry has not been received
and should be re-sent.)

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Flight Optimization Challenge ($250k for 1st place)

Flight Optimization Challenge ($250k for 1st place) | Bits 'n Pieces on Big Data |
Think you can change the future of flight?

Did you know airlines are constantly looking for ways to make flights more efficient? From gate conflicts to operational challenges to air traffic management, the dynamics of a flight can change quickly and lead to costly delays.

There is good news. Advancements in real-time big data analysis are changing the course of flight as we know it. Imagine if the pilot could augment their decision-making process with “real time business intelligence” — information available in the cockpit that would allow them to make adjustments to their flight patterns. 

onur savas's insight:

Started at Aug 5, 2013. Very simple optimization function! Minimize the cost function, which is a superposition of the quantity of fuel burned, the fuel cost, the time in flight, and other costs including hourly cost rates related to crew, passenger and overhead costs. Milestone deadline is on Sep 25.

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Chikungunya threat inspires new DARPA challenge

Chikungunya threat inspires new DARPA challenge | Bits 'n Pieces on Big Data |
Defense Department announces prize for infectious disease forecasting model
onur savas's insight:

The DARPA Challenge:


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Yelp Dataset Challenge | Yelp

Yelp Dataset Challenge | Yelp | Bits 'n Pieces on Big Data |

How well can you guess a review's rating from its text alone? Can you take all of the reviews of a business and predict when it will be the most busy, or when the business is open? Can you predict if a business is good for kids? Has Wi-Fi? Has Parking? What makes a review useful, funny, or cool? Can you figure out which business a user is likely to review next? How much of a business's success is really just location, location, location? What businesses deserve their own subcategory (i.e., Szechuan or Hunan versus just "Chinese restaurants"), and can you learn this from the review text? What makes a tip useful? There is a myriad of deep, machine learning questions to tackle with this rich dataset.

onur savas's insight:

Targeted for academic research though. The deadline is Thursday, July 31, 2014.

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