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Special Issue "'Big' and Linked Data in Energy and Water Demand Research: Current Practices, Novel Insights and Future Agendas"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "C: Energy and Environment".

Deadline for manuscript submissions: closed (31 July 2021).

Special Issue Editors

Dr. Ben Anderson
E-Mail Website
Guest Editor
Energy and Climate Change Division, Faculty of Engineering & Physical Sciences, School of Engineering, University of Southampton, Southampton SO17 1BJ, UK
Interests: domestic energy and water demand; big data; linked data; open data; reproducible research practices; changing energy-use practices; small area energy demand models
Dr. Thomas Rushby
E-Mail Website
Guest Editor
Energy and Climate Change Division/Sustainable Energy Research Group, Faculty of Engineering and Physical Sciences, University of Southampton, Southampton SO17 1BJ, UK
Interests: household energy use and behaviour change; understanding and modelling household energy ‘needs’; evaluation of energy efficiency and behaviour change trials; understanding and modelling demand for household energy services; spatial and temporal distribution of demand; distributional impact of commercial and regulatory interventions
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Patrick James
E-Mail Website
Guest Editor
Energy and Climate Change Division, School of Engineering, Faculty of Engineering & Physical Sciences, University of Southampton, Southampton SO17 1BJ, UK
Interests: energy demand; sustainable cities and city rezoning; building retrofit; built environment; behaviour change; microgeneration (PV, solar thermal, ASHP); energy for development
Prof. Dr. AbuBakr S. Bahaj
E-Mail Website
Guest Editor
Energy & Climate Change Divisions, Sustainable Energy Research Group, School of Engineering, Faculty of Engineering & Physical Sciences, University of Southampton, Southampton SO17 1BJ, UK
Interests: renewable energy; energy access; cities & infrastructure; buildings & communities; and behaviour & modelling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As in many other fields, energy and water demand researchers are starting to make use of ‘big’ and ‘linked’ data to address challenges critical to the sustainability of human society on our planet. This Special Issue is looking for papers that review or present state-of-the-art big and linked data practices, novel and actionable insights from the use of such data and grounded, review-based agendas for future research. All papers, but especially the latter, should include nuanced discussions of conceptual and practical definitions of ‘big’ and/or ‘linked’ data and also situate themselves in ongoing discussions of the benefits, disadvantages, limitations and appropriate granularities of such data. 

Papers may cover any aspect of:

  • Big & linked data collection, sampling, processing, cleaning, bias, consent and ethics in energy & water demand research;
  • Novel big & linked data research practices aimed at embedding open research, reproducibility, data sharing and data re-use in energy & water demand research;
  • Conceptual and practical aspects of linking ‘big’ transactional data with ‘small’ qualitative data to deepen and contextualise insights in energy & water demand research;
  • Novel analysis methods that use big and linked data at appropriate scales to address challenging energy & water demand research questions;
  • New insights for net-Zero energy & water demand strategies and policies based on empirical research with big & linked data; and,
  • Case studies of the commercial and/or practical application of these methods to key challenges in the energy and water sectors.

Papers that take a post-disciplinary approach to interweave different forms of knowing and interpreting are especially welcome.


Dr. Ben Anderson
Dr. Thomas Rushby
Prof. Dr. Patrick James
Prof. Dr. AbuBakr S. Bahaj
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • big data
  • linked data
  • energy demand
  • water demand
  • post-disciplinary
  • methods
  • research practices

Published Papers (3 papers)

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Research

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Article
Exploring Public Opinions on Renewable Energy by Using Conventional Methods and Social Media Analysis
Energies 2021, 14(11), 3089; https://doi.org/10.3390/en14113089 - 26 May 2021
Cited by 1 | Viewed by 1031
Abstract
Renewable energy is one of the most discussed topics nowadays, more so than traditional combustible energy sources and nuclear energy. There is an apparent need to study its public acceptance and the general public’s knowledge about it, especially in the context of more [...] Read more.
Renewable energy is one of the most discussed topics nowadays, more so than traditional combustible energy sources and nuclear energy. There is an apparent need to study its public acceptance and the general public’s knowledge about it, especially in the context of more advanced inventions, such as smart grids, energy storage, or photovoltaic inverters. In this research, the results of a custom survey and those of several types of public social media datasets were processed to gain insights into the acceptance and awareness of these technologies. The second aim was to investigate technologies and related public opinions about manufacturers. One social media dataset was processed by a novel technology based on automatic data collection from popular social media sources, blogs, forums and public news. All the collected and anonymized data were restored in a custom-made data lake (unstructured database) and analyzed by a natural language processing (NLP) engine to extract the required information. The results showed that the Hungarian public’s knowledge differs from the European reference values by a very high percentage. A further goal for new research in the investigated area will be to achieve a business intelligence rated system in order to predict future trends and events. Since different methods provide results from different viewpoints, the conclusion is that combined analyses have to be used for investigating popular topics related to energy, such as various technologies, issues related to energy transition, or even car sharing services for a sustainable future. Full article
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Review

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Review
Carbon-Responsive Computing: Changing the Nexus between Energy and Computing
by , and
Energies 2021, 14(21), 6917; https://doi.org/10.3390/en14216917 - 21 Oct 2021
Viewed by 659
Abstract
While extensive research has gone into demand response techniques in data centers, the energy consumed in edge computing systems and in network data transmission remains a significant part of the computing industry’s carbon footprint. The industry also has not fully leveraged the parallel [...] Read more.
While extensive research has gone into demand response techniques in data centers, the energy consumed in edge computing systems and in network data transmission remains a significant part of the computing industry’s carbon footprint. The industry also has not fully leveraged the parallel trend of decentralized renewable energy generation, which creates new areas of opportunity for innovation in combined energy and computing systems. Through an interdisciplinary sociotechnical discussion of current energy, computer science and social studies of science and technology (STS) literature, we argue that a more comprehensive set of carbon response techniques needs to be developed that span the continuum of data centers, from the back-end cloud to the network edge. Such techniques need to address the combined needs of decentralized energy and computing systems, alongside the social power dynamics those combinations entail. We call this more comprehensive range “carbon-responsive computing,” and underscore that this continuum constitutes the beginnings of an interconnected infrastructure, elements of which are data-intensive and require the integration of social science disciplines to adequately address problems of inequality, governance, transparency, and definitions of “necessary” tasks in a climate crisis. Full article
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Other

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Data Descriptor
The SERL Observatory Dataset: Longitudinal Smart Meter Electricity and Gas Data, Survey, EPC and Climate Data for over 13,000 Households in Great Britain
Energies 2021, 14(21), 6934; https://doi.org/10.3390/en14216934 - 21 Oct 2021
Cited by 2 | Viewed by 664
Abstract
The Smart Energy Research Lab (SERL) Observatory dataset described here comprises half-hourly and daily electricity and gas data, SERL survey data, Energy Performance Certificate (EPC) input data and 24 local hourly climate reanalysis variables from the European Centre for Medium-Range Weather Forecasts (ECMWF) [...] Read more.
The Smart Energy Research Lab (SERL) Observatory dataset described here comprises half-hourly and daily electricity and gas data, SERL survey data, Energy Performance Certificate (EPC) input data and 24 local hourly climate reanalysis variables from the European Centre for Medium-Range Weather Forecasts (ECMWF) for over 13,000 households in Great Britain (GB). Participants were recruited in September 2019, September 2020 and January 2021 and their smart meter data are collected from up to one year prior to sign up. Data collection will continue until at least August 2022, and longer if funding allows. Survey data relating to the dwelling, appliances, household demographics and attitudes were collected at sign up. Data are linked at the household level and UK-based academic researchers can apply for access within a secure virtual environment for research projects in the public interest. This is a data descriptor paper describing how the data were collected, the variables available and the representativeness of the sample compared to national estimates. It is intended to be a guide for researchers working with or considering using the SERL Observatory dataset, or simply looking to learn more about it. Full article
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