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EnGeoData - JDSA 2017 : Special Issue on Environmental and Geospatial Data Analytics - International Journal of Data Science and Analytics, Springer

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Link: http://www.springer.com/cda/content/document/cda_downloaddocument/SI_Environmental+and+Geospatial+Data+Analytics.pdf?SGWID=0-0-45-1578169-p177383280
 
When N/A
Where N/A
Submission Deadline Feb 1, 2017
Notification Due May 1, 2017
Final Version Due Jul 30, 2017
Categories    geographic information systems   big data   data mining   data science
 

Call For Papers

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CALL FOR PAPERS

International Journal of Data Science and Analytics
http://www.springer.com/41060

Special Issue on Environmental and Geospatial Data Analytics

http://www.springer.com/cda/content/document/cda_downloaddocument/SI_Environmental+and+Geospatial+Data+Analytics.pdf?SGWID=0-0-45-1578169-p177383280

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Environmental and more generally geospatial information is now provided by crowdsourcing but also by public administrations in the context of the open data policies. Analyses of such data are still challenging because of their heterogeneity (structural, semantic, spatial and temporal) and because of the difficulty in choosing the "best" knowledge discovery process to apply, according to the needs of the experts in the field. This special issue aims to provide high quality research covering all or part of the challenges mentioned above, from a theoretical or experimental point of view. Challenge about data science deals with creation, storage, search, sharing, modelling, analysis, and visualization of data, information, and knowledge. In Data Science context, spatio-temporal aspects are crucial in order to manage and mine data, to index and retrieve information, and finally to discover and visualize knowledge. By taking into account these spatio-temporal aspects, original methods have to be proposed for processing real and complex data from different domains, e.g., environment, agriculture, health, urban, and so forth.

Topics and scope of the proposed special issue
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- Pre and post processing of environmental data
- Geographical information retrieval
- Spatial data mining and spatial data warehousing
- Knowledge discovery use-cases dedicated to environmental data
- Spatial text mining
- Spatial ontology
- Spatial recommendations and personalization
- Visual analytics for geospatial data
- Dedicated applications:
* Spatio-temporal analytics platform
* Urban traffic systems
* Trajectory analysis
* Land-use and urban policies
* Land-use and urban planning analysis
* Spatio-temporal analysis in Ecology and Agriculture
* and so forth

Important Dates
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- Manuscript submission due: 1st February 2017
- First round decision made: 1st May 2017
- Revised manuscript due: 1st June 2017
- Final decision made: 1st July 2017
- Final paper due: 30th July 2017

Submission Guidelines
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Please submit your paper via Springer’s Editorial System at https://www.editorialmanager.com/jdsa/ by February 1, 2017.
Papers submitted to this special issue for possible publication must be original and must not be under consideration for publication in any other journal or conference. Previously published or accepted conference/workshop papers must contain at least 30% new material to be considered for the special issue (for workshop 50% new content is required). All papers are to be submitted by referring to http://www.springer.com/41060. During submission please select “S.I.: Environmental and Geospatial DA” under Manuscript Category.
All manuscripts must be prepared according to the journal publication guidelines which can also be found on the website (http://www.springer.com/41060). Papers will be reviewed following the journal standard review process. International Journal of Data Science and Analytics: Data-driven scientific discovery is a key emerging paradigm driving research innovation and industrial development in domains such as business, social science, the Internet of Things, and cloud computing. The field encompasses the larger areas of data analytics, machine learning, and managing big data, while related new scientific challenges range from data capture, creation, storage, search, sharing, analysis, and visualization, to integration across heterogeneous, interdependent complex resources for real-time decision-making, collaboration, and value creation. The journal welcomes experimental and theoretical findings on data science and advanced analytics along with their applications to real-life situations.

Guest Editors
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- Diana Inkpen
University of Ottawa, Canada
http://www.site.uottawa.ca/~diana/

- Mathieu Roche
La Recherche Agronomique pour le Développement (Cirad), Montpellier, France
http://textmining.biz/Staff/Roche

- Maguelonne Teisseire
Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (Irstea), Montpellier, France
http://textmining.biz/Staff/Teisseire

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