@inproceedings{d4e3355ca6c8415ba78e1bf5c73bd4f7,
title = "SIMDMS: Data management and analysis to support decision making through large simulation ensembles",
abstract = "Data- and model-driven computer simulations are increasingly critical in many application domains. These simulations may track 100s or 1000s of inter-dependent parameters, spanning multiple layers and spatial-temporal frames, affected by complex dynamic processes operating at different resolutions. Because of the size and complexity of the data and the varying spatial and temporal scales at which the key processes operate, experts often lack the means to analyze results of large simulation ensembles, understand relevant processes, and assess the robustness of conclusions driven from the resulting simulations. Moreover, data and models dynamically evolve over time requiring continuous adaptation of simulation ensembles. The simDMS platform aims to address the key challenges underlying the creation and use of large simulation ensembles and enables (a) execution, storage, and indexing of large ensemble simulation data sets and the corresponding models; and (b) search, analysis, and exploration of ensemble simulation data sets to enable ensemble-based decision support.",
keywords = "Multivariate time series, Simulation ensembles",
author = "Silvestro Poccia and Sapino, {Maria Luisa} and Sicong Liu and Xilun Chen and Yash Garg and Shengyu Huang and Kim, {Jung Hyun} and Xinsheng Li and Parth Nagarkar and Kasim Candan",
note = "Funding Information: Research is supported by NSF#1318788 “Data Management for Real-Time Data Driven Epidemic Spread Simulations”, NSF#1339835 “E-SDMS: Energy Simulation Data Management System Software”, NSF#1610282 “DataStorm: A Data Enabled System for End-to-End Disaster Planning and Response”, NSF#1633381 “BIGDATA: Discovering Context-Sensitive Impact in Complex Systems”, and “FourCmodeling”: EU-H2020 Marie Sklodowska-Curie grant agreement No 690817. Publisher Copyright: {\textcopyright} 2017, Copyright is with the authors.; 20th International Conference on Extending Database Technology, EDBT 2017 ; Conference date: 21-03-2017 Through 24-03-2017",
year = "2017",
doi = "10.5441/002/edbt.2017.75",
language = "English (US)",
series = "Advances in Database Technology - EDBT",
publisher = "OpenProceedings.org",
pages = "582--585",
editor = "Bernhard Mitschang and Volker Markl and Sebastian Bress and Periklis Andritsos and Kai-Uwe Sattler and Salvatore Orlando",
booktitle = "Advances in Database Technology - EDBT 2017",
}