Any kind of development is incomplete without the development in agriculture and in absence of natural resources. What will happen, if we have a developed the society in terms of information and infrastructure but no access to food or natural resources? We are experiencing a tremendous technology growth and evolution of innovative applications using Data Science and Big Data Analytics (BDA). Internet of Agriculture Things (AgThings) helps us to capture big data and in upcoming decade the farms will be a great source of data. The data obtained from farms can be used for precision agriculture and will help farmers or end users to take better decisions. The objective of workshop is to discuss the potential application areas of Data Science in Agriculture and Natural Resource Management domain. This workshop will demonstrate how data integration and analytics using data science can help farmers to increase their earnings and enable them to take better decisions. The agriculture and natural resource management sector needs keen attention of data science research community for finding innovative solutions to the problem of best utilization of natural resources and to increase the yield of agro-produces. Today, we are witnessing the information age and we have best time to make use of available voluminous, dynamic, and real time data for taking most efficient decisions for the management of natural resources and agricultural development. The objective of workshop is to provide a platform where researchers, academicians, professionals and practitioners can share state of the art technology for best utilization of natural resources and a highly productive environment for agriculture. The workshop is in conjunction with Big Data Analytics 2017 and it aims:

• To provide a forum where experts can discuss important contributions towards or research activities in the area of data science in Agriculture and Natural Resource Management.
• To discuss experimental research work in the area of Data Science, Big Data Analytics and Machine learning using any software libraries as well as BDA frameworks.
• To attract agro-experts and professionals to discuss hidden agriculture and farming patterns for the use of data in related domains.
• To discuss available datasets, acquisition, cleaning, integration and data analytics in agriculture and natural resource management.
• To discuss and identify relevant research issues for big data analytics and data science for agriculture and natural resource management.

The potential outcome of the workshop is to address challenges and issues related to Data Science in Agriculture and Natural Resource Management, data mining of weather or crop production data for estimation or prediction of disease, tools, data mining for the prediction models to solve the problem and develop frameworks for data mining in a specific domain of agricultural databases. We welcome the applications of data mining in spatial or agriculture as well as commodity market data analysis. We invite all researchers, scientists, professionals and academicians to share their interesting research, ideas, experience and results. The major topics related to large, complex, big data analytics and knowledge discovery are invited.

Submission Guidelines

Prospective authors are invited to submit original research papers (not being considered for publication elsewhere) from 15 to 20 pages in length in the LNCS style. Unformatted papers and papers beyond the page limit will not be reviewed. The submissions will be accepted through https://easychair.org/conferences/?conf=dsanrm2017

Each paper should contain an abstract of approximately 300 words having a page limit of 20 pages including the title page, references and appendix. For preparing the manuscript, please see instructions for authors by Springer, in the Lecture Notes in Computer Science series (LNCS) http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0.

LaTeX and Word Templates & Submission Guidelines:

http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0

All submitted papers will be peer-reviewed by at least three program committee members. At least one author of each accepted paper is required to register at the workshop and present the paper. Accepted and presented papers will appear in the online workshop proceedings.

List of Topics

The workshop invites original research papers in the areas related to ‘Data Science in Agriculture and Natural Resource Management’. Topics include but are not limited to:

• Agricultural Data Model including sensing and reliability
• Algorithm Designing and implementation in Agriculture Databases
• Big data analytics and social media for agriculture
• Cloud and grid computing for agriculture
• Data Mining tools for analysis of Spatial Agriculture Data
• Data mining with relevance to prognosis of disease
• Data mining, graph mining and data science for agriculture
• Data science applications in agriculture
• Data science for decision support system for natural resource management
• Data Warehousing and Integration for Agriculture
• Exogenous parameters estimation for increasing crop yield
• Framework for mining complex and large data, e.g. a combination of experimentation, images, and use cases
• Innovations in agriculture and sensing devices used in farming
• Knowledge based agriculture data models
• Managing water resources by data analytics
• Models and tools for smart computing in agriculture
• Online Algorithms and Analytics for data generated by Sensors and Machines used by green houses and precision agriculture
• Ontology based study in context to data mining
• Precision agriculture and smart farming
• Security and privacy for big data in agriculture
• Smart devices and hardware for precision agriculture
• Smart farming and big data
• Smart location-based services for agriculture recommendations
• Smart use of natural resources by using data science
• Spatial, Temporal and Sequential Agriculture Data Mining
• Standards for big data and spatial data in agriculture
• Various scalability techniques for processing of large databases
• Visualization and analytics of agriculture data

Committees

Workshop Chair

• Dr. Sanjay Chaudhary, Professor and Associate Dean, School of Engineering and Applied Science, Ahmedabad University, India
• Dr. Leisa Armstrong, School of Science, Edith Cowan University, Australia

Program committee

• Prof. Athula Ginige, Professor, School of Computing, Engineering & Mathematics, Western Sydney University, Australia
• Dr. Devesh Jinwala, Professor, Department of Computer Engineering, S V National Institute of Technology, Surat, India
• Prof. Dean Diepeveen, Professor of Agriculture and Genomics, Murdoch University, Australia
• Dr. Mehul Raval, Associate Professor, School of Engineering and Applied Science, Ahmedabad University, India
• Dr. Saravanan Raj, Director (Agricultural Extension), MANAGE, Hyderabad, India
• Dr. Anil Roy, Associate Professor, DA-IICT, India
• Prof. Rajender Parsad, ICAR – Indian Agricultural Statistics Research Institute, New Delhi, India
• Dr. R. Uday Kiran, University of Tokyo, Japan

Technical Program Committee

• Prof. M V Joshi, Professor, DA-IICT, Gandhinagar, India
• Prof. C V Jawahar, Professor, Centre for Visual Information Technology (CVIT), IIIT Hyderabad, India
• Dr Vasala Madhava Rao, National Institute of Rural Development and Panchayati Raj, India
• Dr. Rushi Bhatt, LinkedIn, Bengaluru, India
• Dr. Ranendu Ghosh, Professor, DA-IICT, India
• Dr. Avital Bechar, The Institute of Agricultural Engineering, Israel
• Dr. P Rajalakshmi, Associate Professor, Department of Electrical Engineering, Indian Institute of Technology Hyderabad, India
• Dr. Shashikant Sharma, Scientist-SG & Group Head,  VRG/EPSA, Space Applications Centre (ISRO), INDIA
• Dr. Amit Ganatra, Dean, Faculty of Technology and Engineering, CHARUSAT, Gujarat, India
• Prof. M. T. Savaliya, Vishwakarma Government Engineering College, Ahmedabad, India
• Dr. Sanjay Garg, Institute of Technology, Nirma University, Ahmedabad, India
• Dr. Chandra B. Singh, GRDC Associate Professor, Stored Grains Engineering,  School of Engineering, University of South Australia, Australia
• Dr. Dileepkumar Guntuku, Global Program Leader, Iowa State University, USA
• Dr. Ratnik Gandhi, School of Engineering and Applied Science, Ahmedabad University, India
• Dr. Pankesh Patel, Research Scientist, Fraunhofer Inc., USA
• Dr. Saurabh Srivastava, Research Scientist & Project Manager, Conduent Labs, Bengaluru, India
• Dr. Shaik Rehana, IIIT Hyderabad, India

Program Schedule (Tentative)

Venue

International Institute of Information Technology (IIIT, Hyderabad)
Gachibowli, Hyderabad 500 032, Telangana, INDIA

Contact

All questions about submissions should be emailed to vikas.tyagi@ahduni.edu.in