1,720,970 research outputs found
Smart Energy Research Lab Observatory Data, 2019-2021: Secure Access (Edition 3)
No full textThe vision of the Smart Energy Research Lab (SERL) is to deliver a unique data resource harnessing the benefits of smart meter data for research. The portal will transform Great Britain's energy research through the long-term provision of high quality, high-resolution energy data that will support the development of a reliable evidence base for intervention, observational and longitudinal studies across the socio-technical spectrum.
The goals of the Smart Energy Research Lab are to provide:
A trusted data resource for researchers to utilise large-scale, high-resolution energy data
An effective mechanism for collecting and linking energy data with other contextual data
High quality data management to ensure fit-for-purpose data are provisioned to researchers
Participant recruitment began in August 2019. Approximately 1,700 participants were recruited from central and southern England and from Wales as part of a pilot study that tested different recruitment strategies. The second recruitment wave took place in August-September 2020, and the third wave at the start of 2021. SERL aims to recruit around 10,000 households to be regionally representative across England, Scotland and Wales. Recruitment is also designed to be representative of each Index of Multiple Deprivation (IMD) quintile; an area-based relative measure of deprivation.
26 April 2021: For the latest edition (April 2021) all SERL data up to and including 31 October 2020, which includes participant households recruited in Waves 1 and 2 were made available. </span
Smart Energy Research Lab Observatory Data, 2019-2020: Secure Access (Edition 2)
No full textThe vision of the Smart Energy Research Lab (SERL) is to deliver a unique data resource harnessing the benefits of smart meter data for research. The portal will transform Great Britain's energy research through the long-term provision of high quality, high-resolution energy data that will support the development of a reliable evidence base for intervention, observational and longitudinal studies across the socio-technical spectrum. The first edition of the Smart Energy Research Lab Observatory Data, 2019-2020: Secure Access relates to 1,700 participant households recruited during SERL’s pilot phase in August-September 2019</span
Smart Energy Research Lab: Statistical Data, 2019-2021: Safeguarded Access
No full textThe Smart Energy Research Lab (SERL) Observatory facilitates a broad range of energy demand research and is a unique data resource for research where access to high resolution, large scale energy data linked to relevant contextual data is required. Further information about SERL can be found on the Smart Energy Research Lab website.
This dataset of aggregated statistics is available under standard Safeguarded (End User Licence) access conditions. It contains around 110,000 rows and describes domestic gas and electricity energy use in Great Britain in 2021 based on data from the Smart Energy Research Lab (SERL) Observatory, which consists of smart meter and contextual data from approximately 13,000 homes that are broadly representative of the GB population in terms of region and Index of Multiple Deprivation (IMD) quintile. This aggregated dataset can be used, for example, to show how residential energy use in GB varies over time (monthly over the year and half-hourly over the course of the day); and can be broken down by occupant characteristics (number of occupants, tenure), property characteristics (age, size, form, and Energy Performance Certificate (EPC)), by type of heating system, presence of solar panels and of electric vehicles, and by weather, region and IMD quintile. </span
Smart Energy Research Lab Observatory Data, 2019-2021: Secure Access (Edition 4)
No full textThe vision of the Smart Energy Research Lab (SERL) is to deliver a unique data resource harnessing the benefits of smart meter data for research. The portal will transform Great Britain's energy research through the long-term provision of high quality, high-resolution energy data that will support the development of a reliable evidence base for intervention, observational and longitudinal studies across the socio-technical spectrum.
The goals of the Smart Energy Research Lab are to provide:
A trusted data resource for researchers to utilise large-scale, high-resolution energy data
An effective mechanism for collecting and linking energy data with other contextual data
High quality data management to ensure fit-for-purpose data are provisioned to researchers
Participant recruitment began in August 2019. Approximately 1,700 participants were recruited from central and southern England and from Wales as part of a pilot study that tested different recruitment strategies. The second recruitment wave took place in August-September 2020, and the third wave at the start of 2021. SERL aims to recruit around 10,000 households to be regionally representative across England, Scotland and Wales. Recruitment is also designed to be representative of each Index of Multiple Deprivation (IMD) quintile; an area-based relative measure of deprivation.
For the latest (4th) edition (October 2021) all SERL data up to and including 31 May 2021, which includes participant households recruited in Waves 1, 2 and 3, were made available.</span
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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