SemStats

SemStats 2014 Call for Challenge

Document ID
http://semstats.org/2014/call-for-challenge
Published
Modified
License
CC BY 4.0

Hashtags

  • ISWC2014
  • SemStats
Event
2nd International Workshop on Semantic Statistics co-located with 13th International Semantic Web Conference (ISWC 2014)
Location
Riva del Garda, Italy
Date

Abstract

The SemStats Challenge is back with more action! It is organized in the context of the SemStats 2014 workshop. Participants are invited to apply statistical techniques and semantic web technologies within one of two possible tracks, namely the Census Data Track and Open Track. Following up on the success of last year’s Challenge, this year, the Census Data Track will have data from France, Italy, and Ireland. We would also like to introduce the new Open Track, where any type of statistical data of your choice may be used in the challenge.

The challenge will consist in the realization of mashups or visualizations, but also on comparisons, analytics, alignment and enrichment of the data and concepts involved in statistical data (see below for the data made available and additional requirements).

The deadline for participants to submit their short papers and application is Sun 7thTue 30 September, 2014, 23:59pm Hawai Time. Submission is done via EasyChair by selecting the Challenge paper category.

It is strongly suggested to all challenge participants to send contact informations to semstats2014@easychair.org in order to be kept informed in case of any changes in the data provided.

Census Data Track

We would like to point you to plenty of raw data. The conversion process will be considered as part of the challenge.

Open Data Track

There is one essential requirement for the Open Track: papers must describe a publicly available application. We would love to see everyone play and learn from what you have created. You are welcome to use any statistical data whether it is already in Linked Data shape or not! While you are at it, why not combine it with data from other domains?

Here are some statistical linked dataspaces (off the top of our heads):