Nature Data Analysis involves the analysis of multimodal and heterogeneous extreme data sources including data captured by autonomous devices (e.g., drones) and smart sensors at the edge, satellite images, topographical data, official meteorological data, predictions or warnings published on the Web, and geosocial media data (including text, image and videos). Besides being heterogeneous, nature data might be unstructured, sparse/missing, lacking and it is difficult to be simulated or visualized. On top of this complexity, the analysis of natural phenomena needs to be performed very fast, to trigger relevant responses from the local authorities, as they are frequently related to natural disasters, such as forest fires or floods. This workshop aims at gathering experts from academia, industry, government, NGOs in Natural data analysis from the domains of Distributed systems, Machine Learning, Robotics, Text Analysis and Signal Processing for exchanging ideas on big Nature Data collection, processing, simulation and visualization and relevant applications, such as Natural disaster management. This workshop is in conjunction with the 10th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT 2023).
Papers are solicited in all areas of algorithms, systems, platform and architecture of Big Data for nature and environmental data, including, but not restricted to:
Authors are invited to submit papers electronically through the following link: https://cmt3.research.microsoft.com/UCCBDCAT2023, track BigNDA 2023 - Workshop. Submitted manuscripts must represent original unpublished research that is not currently under review for any other conference or journal. Manuscripts are submitted in PDF format and may not exceed six (6) ACM-formatted doublecolumn pages, including figures, tables, and references. All manuscripts undergo a double-blind peer-review process and will be reviewed and judged on correctness, originality, technical strength, rigor in analysis, quality of results, quality of presentation, and interest and relevance to the conference attendees. Your submission is subject to a determination that you are not under any sanctions by ACM. Accepted papers will later be converted into single-column format through the ACM TAPS process, and therefore need to use the new templates that are single-column by default. Switch them to double-column for authoring your paper. This is possible in both the Word and the LaTeX templates.
At least one author of each paper must be registered for the conference in order for the paper to be published in the proceedings. The conference proceedings will be published by the ACM and made available online via the IEEE Xplore Digital Library and ACM Digital Library.