Open Data and Energy Analytics
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,...
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| Format: | Book Chapter |
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Basel, Switzerland
MDPI - Multidisciplinary Digital Publishing Institute
2020
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| Online Access: | Get Fullteks DOAB: description of the publication |
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| LEADER | 05126naaaa2201141uu 4500 | ||
|---|---|---|---|
| 001 | doab_20_500_12854_68684 | ||
| 005 | 20210501 | ||
| 020 | |a books978-3-03936-219-6 | ||
| 020 | |a 9783039362189 | ||
| 020 | |a 9783039362196 | ||
| 024 | 7 | |a 10.3390/books978-3-03936-219-6 |c doi | |
| 041 | 0 | |a English | |
| 042 | |a dc | ||
| 072 | 7 | |a GP |2 bicssc | |
| 100 | 1 | |a Nastasi, Benedetto |4 edt | |
| 700 | 1 | |a Manfren, Massimiliano |4 edt | |
| 700 | 1 | |a Noussan, Michel |4 edt | |
| 700 | 1 | |a Nastasi, Benedetto |4 oth | |
| 700 | 1 | |a Manfren, Massimiliano |4 oth | |
| 700 | 1 | |a Noussan, Michel |4 oth | |
| 245 | 1 | 0 | |a Open Data and Energy Analytics |
| 260 | |a Basel, Switzerland |b MDPI - Multidisciplinary Digital Publishing Institute |c 2020 | ||
| 300 | |a 1 electronic resource (218 p.) | ||
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a 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. | ||
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
| 546 | |a English | ||
| 650 | 7 | |a Research & information: general |2 bicssc | |
| 653 | |a data envelopment analysis | ||
| 653 | |a Kohonen self-organizing maps | ||
| 653 | |a factor analysis | ||
| 653 | |a multiple regression | ||
| 653 | |a energy efficiency | ||
| 653 | |a social media | ||
| 653 | |a energy-consuming activities | ||
| 653 | |a energy consumption | ||
| 653 | |a machine learning | ||
| 653 | |a ontology | ||
| 653 | |a energy performance certificate | ||
| 653 | |a heating energy demand | ||
| 653 | |a buildings | ||
| 653 | |a data mining | ||
| 653 | |a classification | ||
| 653 | |a regression | ||
| 653 | |a decision tree | ||
| 653 | |a support vector machine | ||
| 653 | |a random forest | ||
| 653 | |a artificial neural network | ||
| 653 | |a open data | ||
| 653 | |a electrification modelling | ||
| 653 | |a Malawi | ||
| 653 | |a OnSSET | ||
| 653 | |a MESSAGEix | ||
| 653 | |a reproducibility | ||
| 653 | |a collaborative work | ||
| 653 | |a open modelling and data | ||
| 653 | |a data-handling | ||
| 653 | |a integrated assessment modelling | ||
| 653 | |a data pre- and post-processing | ||
| 653 | |a space heating | ||
| 653 | |a domestic hot water | ||
| 653 | |a market assessment | ||
| 653 | |a EU28 | ||
| 653 | |a district heating | ||
| 653 | |a data analytics | ||
| 653 | |a big data | ||
| 653 | |a forecasting | ||
| 653 | |a energy | ||
| 653 | |a polygeneration | ||
| 653 | |a clustering | ||
| 653 | |a kNN | ||
| 653 | |a pattern recognition | ||
| 653 | |a heating | ||
| 653 | |a building stock | ||
| 653 | |a heat map | ||
| 653 | |a spatial analysis | ||
| 653 | |a heat density map | ||
| 653 | |a building performance simulation | ||
| 653 | |a parametric modelling | ||
| 653 | |a energy management | ||
| 653 | |a model calibration | ||
| 653 | |a Passive House | ||
| 653 | |a energy planning | ||
| 653 | |a energy potential mapping | ||
| 653 | |a urban energy atlas | ||
| 653 | |a urban energy transition | ||
| 653 | |a energy data | ||
| 653 | |a data-aware planning | ||
| 653 | |a spatial planning | ||
| 653 | |a open data analytics | ||
| 653 | |a smart cities | ||
| 653 | |a open energy governance | ||
| 653 | |a urban database | ||
| 653 | |a energy mapping | ||
| 653 | |a building dataset | ||
| 653 | |a energy modelling | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/2449 |7 0 |z Get Fullteks |
| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/68684 |7 0 |z DOAB: description of the publication |