In the late 1960’s, simple data assimilation revolutionarily transformed science in fields based on satellite data. Both NASA and NCAR produced stunningly revolutionary applications. The oil and gas industry jumped on this concept in the early to mid 1970’s creating commercial data assimilation pipeline products by multiple vendors that were used in more than 165 countries in short order. This led to intelligent data assimilation being the normal way to operate a reservoir or pipeline networks by the 1990’s by all of the major oil producers. Since the early 2000’s, government grant agencies (e.g., the National Science Foundation) applied this concept to update numerous fields creating astonishing improvements in simulations that continue to this day in many application areas.
A data-driven computational system is the integration of a simulation with dynamically and intelligently assimilated data, multiscale modeling, computation, and a two way interaction between the model execution and the data acquisition methods (see the DDDAS Scientific Community Web Site, http://www.1dddas.org). The workshop will present opportunities as well as challenges and approaches in technology needed to enable Data-Driven Computational Science capabilities in applications, relevant algorithms, and software systems. All related areas in Data-Driven Sciences are included in this workshop, including CyberPhysical Systems like HealthKit on iPhones and iPads as well as similar systems developed by Intel, Google, and Microsoft for phones and tablets, Internet of Things (IoT), Cloud of Things (CoT), and Data Intensive Scientific Discovery (DISD).
A recent example is a tranformative way of landing airplanes on time and reduce delays and cancellations is a process known as Time Based Flow Systems (TBFS) [UKNATS]. It spaces planes by space instead of by time. The first of these systems was developed for Heathrow Airport by Lockheed Martin for the British National Air Traffic Services and fully deployed in May, 2015. It has reduced flight cancellations due to wind by exactly 100% and flight delays by approximately 40% during the period of May – August, 2015.
From 2004 through 2014 there was a Dynamic Data-Driven Application System (DDDAS) Workshop at ICCS. In 2015 the workshop split into 1) for projects funded by the U.S. Air Force Office of Scientific Research (AFOSR), and 2) for more general papers. The current workshop is open to all and strongly encourages new developments related to large data, streaming data, machine learning and data reduction strategies. We will accept great research in all of data driven computional sciences based on 2-3 unbiased referee reports.
Important Dates*: Note that for the past conferences that the dates have been extended by the ICCS organizers.
|18 December 2020||Creation of paper title and abstract on ICCS 2020 conference web site|
|26 February 2021||Submission of full paper|
|10 March 2021||Notification of acceptance or revision requirements for acceptance|
|5 April 2021||Camera ready version of paper submitted|
|15 March – 5 April 2021||Author registration (your accepted paper will be dropped on 6 April 2021 if you are not registered)|
|16-18 June 2021||ICCS 2021 (DDDAS 2021 Workshop on June ?, 2021)|
* Last updated on 24 February 2021. Date changes coming in 2020-2021.
Abani Patra (Tufts University, USA)
Ana Cortés (Universitat Autònoma de Barcelona, Spain)
Robert Lodder (University of Kentucky, USA)
Han Yu (Nanjing University of Posts & Telecommunications, China)
Hiroshi Fujiwara (Kyoto University, Japan)
Li Douglas (Kyoto University, Japan)