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12th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing

November 12–13, 2016 | Beijing, People's Republic of China

Multivariate Big Data Collaborations in Meteorology and Its Interdisciplines 

 

1. The technical issues that this workshop will address

 
The collaborations of multivariate big data is a new hotspot in meteorology and its interdisciplines, which mainly focus on two issues:
1) how to make more accurate forecast in smaller scale(i.e., smaller areas and periods) with data mining and collaboration;
2) and how utilize meteorological data to make benefit for other industries.
 
For the first issue, many new weather forecast approaches employing neural network, collaborative filtering and similarity computing etc. have been proposed and are gaining more and more attentions of researchers.
The second issue is also arresting with the development of big data since the using and collaboration of meteorological data can effectively improve the quality of many other industries such as traffic, agriculture and the increasingly prosperous service recommendations.
 

2. Why the workshop is interesting and timely 

Techniques of mining and analysis big data originating from computer science have been gained extensive attentions in almost every research field. Meteorology may be one of the first research fields dealing with big data, e.g., the first supercomputer of China was used for weather forecast since the weather data is really big. However big data in meteorology are mainly focused for their big volume rather than their mining and analysis techniques, since traditional linear forecasting models have been worked robustly for handed of years, and hence meteorology may be the last one of the fields which adopt mining and analysis techniques of big data, but it is changing dramatically since:
1) peoples are becoming eager for more accurate weather forecast in smaller scale(i.e., smaller areas and periods), and researchers have found that some new approaches such as neural network, collaborative filtering and so on perform well than traditional forecast models;
2) data is becoming bigger and more multivariate in meteorology with more and more data collection tools such as observation stations, radars, and satellites etc., and how to make accurate forecast in smaller scale with the collaboration of such multivariate data is becoming a new hotspot;
3) and it is arresting that the employing of meteorological data can effectively improve the quality of many other industries such as traffic, agriculture and the increasingly prosperous service recommendations, which have brought some interdisciplines of meteorology and other subjects.
 
In conclusion, multivariate big Data collaboration is gaining more and more attentions and therefore this workshop is interesting and timely.
 

3. Draft of call for papers 

Scope: The collaboration of multivariate big data is a new hotspot in meteorology and its interdisciplines. Peoples are becoming eager for more accurate weather forecast in smaller scale (i.e., smaller areas and periods), on the other hand, data is becoming bigger and more multivariate in meteorology with more and more data collection tools such as observation stations, radars, and satellites etc., based on which researchers have found that some new approaches such as neural network, collaborative filtering and so on perform well than traditional linear forecast models. Therefore how to make accurate forecast in smaller scale with the collaboration of such multivariate data is becoming a new hotspot. It is also worth noticed that the employing of meteorological data can effectively improve the quality of many other industries such as traffic, agriculture and the increasingly prosperous service recommendations, which have brought some interdisciplines of meteorology and other subjects, and such interdisciplines are gaining more and more attentions of researchers.
 
This workshop mainly focus on two technical issues: 1) how to make more accurate forecast in smaller scale with data mining and collaboration; 2) and how utilize meteorological data to make benefit for other industries such as traffic, agriculture and the increasingly prosperous service recommendations.
 
Topics of interest include, but are not limited to:
  • Techniques of mining and analysis of big data and spatio-temporal data in meteorology.
  • Assimilations of multivariate meteorological data.
  • Collaborations of multivariate meteorological data.
  • Collaborations of multivariate telemetry data of meteorological satellite, which aims to monitor the working conditions of meteorological satellites.
  • Collaborations of meteorology and other subjects such as traffic, agriculture and the service recommendations etc.
  • Tools for collaborative decision making processes
Important Dates
  • Deadline for paper submissions: September 1st, 2016
  • Paper notification: September 30th, 2016
  • Deadline for camera ready submission: October 10th, 2016
Tentative composition of the organizing and program committees
 
You Ma, National Satellite Meteorological Center
Xiaoliang Fan, Lanzhou University
Xu Li, Lanzhou University
Qibo Sun, Beijing University of posts and Telecom
Ming Xu, Tsinghua University