Open Data and Energy Analytics

Open Data and Energy Analytics
Author :
Publisher : MDPI
Total Pages : 218
Release :
ISBN-10 : 9783039362189
ISBN-13 : 3039362186
Rating : 4/5 (186 Downloads)

Book Synopsis Open Data and Energy Analytics by : Benedetto Nastasi

Download or read book Open Data and Energy Analytics written by Benedetto Nastasi and published by MDPI. This book was released on 2020-06-25 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Open data and policy implications coming from data-aware planning entail collection and pre- and postprocessing as operations of primary interest. Before these steps, making data available to people and their decision-makers is a crucial point. Referring to the relationship between data and energy, public administrations, governments, and research bodies are promoting the construction of reliable and robust datasets to pursue policies coherent with the Sustainable Development Goals, as well as to allow citizens to make informed choices. Energy engineers and planners must provide the simplest and most robust tools to collect, process, and analyze data in order to offer solid data-based evidence for future projections in building, district, and regional systems planning. This Special Issue aims at providing the state-of-the-art on open-energy data analytics; its availability in the different contexts, i.e., country peculiarities; and its availability at different scales, i.e., building, district, and regional for data-aware planning and policy-making. For all the aforementioned reasons, we encourage researchers to share their original works on the field of open data and energy analytics. Topics of primary interest include but are not limited to the following: 1. Open data and energy sustainability; 2. Open data science and energy planning; 3. Open science and open governance for sustainable development goals; 4. Key performance indicators of data-aware energy modelling, planning, and policy; 5. Energy, water, and sustainability database for building, district, and regional systems; 6. Best practices and case studies.


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