on Energy Data and Analytics
ACM e-Energy Workshop 2018
June 12, 2018 – Karlsruhe, Germany
- Paper Registration and Submission:
February 26, 2018 March 2, 2018 7:59:59am EST
- Final Manuscript Due: April 20, 2018
"Improving and Combining Multivariate Measurement and Prediction Data"
Optimal Reconfiguration of Real Low-Voltage Grids Based on Probabilistic Simulation
HIPE – An Energy-Status-Data Set from Industrial Production
Numerical Weather Prediction Data Free Solar Power Forecasting with Neural Networks
Energy Disaggregation for SMEs using Recurrence Quantification Analysis
SCiBER: A new public data set of municipal building consumption
Data Economy for Prosumers in a Smart Grid Ecosystem
Hybrid Day-ahead Load Forecasting with Atypical Residue based Gaussian Process Regression
Scope and Topics
The design of future energy systems that are efficient, ecologically friendly, robust and scalable is a core concern of our societies. Further, in recent years there has been a major shift towards a data-oriented perspective on system design. In the context of energy systems, a broad variety of data, often huge in volume, is available. For instance, each smart meter generates data streams, which are often recorded and archived. The questions on how such data can be captured and processed, and what can be learned from it are fundamentally important. This includes predictions of various kinds of supply and demand, predictive maintenance of energy infrastructures, the processing of energy-consumption data in a way that respects the privacy of the individuals involved as well as business secrets etc.
This workshop is interdisciplinary in nature, i.e., it brings together individuals interested in both data management/data analytics and energy systems. Its objectives are the following:
- To draw attention to the fact that data-oriented approaches often are possible and tend to be promising when designing and operating energy systems.
- To give researchers in databases/KDD communities the opportunity to present their ideas, concepts and solutions to a critical perspective of experts from energy systems.
- To help bringing researchers on energy systems close to the state-of-the-art on what data-oriented approaches can do for the design and operation of such systems. It wants to provide support to individuals who want to broaden their perspective on data-management and analytics methods.
- To serve as a networking platform, with an eye on funding opportunities in particular.
The workshop solicits submissions on the following topics – all of them specific to energy data/energy systems and their characteristics:
- New approaches and techniques to analyze energy data
- data reduction
- data science for energy data
- infrastructures for/techniques/best principles for the administration, management and archiving of energy data
- data from simulations of energy systems
- synthetic data generation
- data integration and data quality
- data privacy and anonymization
- modeling and representing energy-specific knowledge
On a methodological level, the workshop is open to any kind of submission:
- research papers
- vision papers
- comparative studies
- case studies and experience reports.
Two types of contributions are solicited:
- Full papers, up to 8 pages in 9-point ACM double-column format (i.e., excluding references) and unlimited number of pages for appendices and references, single-blind.
- Short papers, up to 4 pages in 9-point ACM double-column format (i.e., excluding references) and unlimited number of pages for appendices and references, single-blind.
The submission must be in PDF format and be formatted according to the official ACM Proceedings format. Papers that do not meet the size and formatting requirements may not be reviewed. Word and LaTeX templates are available at http://www.acm.org/publications/article-templates/proceedings-template.html. The proceedings of the workshop will be published by ACM Digital Library along with the e-Energy conference proceedings.
Submission site: https://eenergy18eda.hotcrp.com/
- Klemens Böhm, KIT, Germany
- Manish Marwah, Micro Focus, US
- Martin Arlitt, University of Calgary/Micro Focus, Canada
- Gowtham Bellala, C3 IoT, USA
- Mario Berges, CMU, USA
- Daniel Gmach, Linkedin, USA
- Lukasz Golab, University of Waterloo, Canada
- Stephen Haben, University of Oxford, UK
- Mahmud Shahriar Hossain, University of Texas at El Paso, USA
- Ralf Mikut, KIT, Germany
- Dirk Neumann, University of Freiburg, Germany
- Jorge Ortiz, IBM Research, USA
- Torben Bach Pedersen, Aalborg University, Denmark
- Naren Ramakrishnan, Virginia Tech, USA
- Rebecca Schwerdt, KIT, Germany
Please turn to Klemens Böhm (klemens dot boehm at kit dot edu) for any questions or comments.