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620 results for “sector”
Interviews on Current Practices for Describing and Providing Access to UK Public Sector Web Archives
<p>This dataset contains qualitative interview data which investigated current practice for describing and providing access to UK Public Sector Web Archives. Participants included staff responsible for the management and curation of the following web archives:</p><ul><li>UK Web Archive (four of the six Legal Deposit libraries: the British Library, Bodleian Libraries, Cambridge University Library, and the National Library of Scotland)</li><li>UK Government Web Archive (The National Archives)</li><li>UK Parliament Web Archive (Parliamentary Archives)</li><li>NRS Web Archive (National Records of Scotland) and</li><li>PRONI Web Archive (Public Record Office Northern Ireland).</li></ul><p>Available to the public are the University of Dundee (UoD) ethics application for this study, including the research data management plan and information provided to organisations before participating in the study. The report of interview codes and code groups (the 'Codebook') demonstrates the connections made across responses. This is supplemented by a redacted report of quotations by code, organised by code group and document.</p><p>This qualitative interview data, and subsequent analysis, forms the basis of the Masters thesis 'Web Archives for All? Towards Equitable Access to UK Public Sector Web Archives' submitted as part of the MLitt Archives and Records Management at the University of Dundee. </p>
Mejora de control de inventario usando QR: Sistema Web para el sector Metalmecánico
Open the record for dataset details and reuse information.
Figure 4 in Conservation gaps identification through patterns of species richness established from species niche models of mammals in a sector of Chaco Seco ecoregion
Figure 4. Response graphs of habitat suitability (ordinate axis) according to the explanatory variables that intervened in the adjustment of the model for brown brocket deer (A, B, C). The temperature is expressed in degrees Celsius.Source of bioclimatic variables (bio), site https://www.worldclim.org/data/bioclim.html.
Figure 8 in Conservation gaps identification through patterns of species richness established from species niche models of mammals in a sector of Chaco Seco ecoregion
Figure 8. Species richness maps obtained using three algorithms, (A) "fuzzy union″, (B) "species richness″ and (C) "total beta″.
Figure 7 in Conservation gaps identification through patterns of species richness established from species niche models of mammals in a sector of Chaco Seco ecoregion
Figure 7. Response graphs of habitat suitability (ordinate axis) according to the explanatory variables that intervened in theadjustment of themodel for collared peccary (A,B, C).Temperature is expressed in degrees Celsius and altitude in meters.Source of bioclimatic variables (bio), site https://www.worldclim.org/data/bioclim.html.
Correspondence table between UNFCCC CRF and EXIOBASE industry sectors
<p>This repository contains a correspondence table (CT) that maps the UNFCCC Common Reporting Format (CRF) to the EXIOBASE v3 industry classification. The CT was compiled for our study on "Estimating the uncertainty of the greenhouse gas emission accounts<br>in Global Multi-Regional Input-Output analysis" submitted to the Journal of Earth System Science Data (ESSD): <a href="https://essd.copernicus.org/preprints/essd-2023-473/">https://essd.copernicus.org/preprints/essd-2023-473/</a></p> <p>In the UNFCCC CRF (2019 revision) emission sources are grouped in <strong>categories</strong> and <strong>classifications</strong>, in a hierarchical order. The highest ranked categories - also called sectors - are 1) Energy, 2) Industrial Processes and Product Use, 3) Agriculture, 4) Land use, land-use change, and forestry (LULUCF), 5) Waste and 6) Other. Those sectors are further broken down into sub-categories, e.g. 1.A.1.a.i. The sub-categories of the sectors Energy, Agriculture and LULUCF are further broken down by the classification. The classification distinguishes different fuel types (in case of emission from "Energy') and animal types (in case of emissions from "Agriculture"). Like the categories, the classification also follows a hierarchical structure.</p> <p>Parties report their emissions to the UNFCCC at different levels of resolution depending on national characteristics and data availability. </p> <p>Here, we provide two tables: </p> <ul> <li><a href="../api/records/10046372/draft/files/correspondence_CRFdetailed_to_EXIOBASE_root.xlsx/content">correspondence_CRFdetailed_to_EXIOBASE_root.xlsx</a>: Lists the correspondences only for the most detailed level (with regard to both category and classfication).</li> <li><a href="../api/records/10046372/draft/files/correspondence_CRFdetailed_to_EXIOBASE_coherent.xlsx/content">correspondence_CRFdetailed_to_EXIOBASE_coherent.xlsx</a>: List the correspondences for all levels (automatically compiled from the 'root' table).</li> </ul> <p><strong>Collaboration in checking, revising and refining the correspondence table is appreciated. Please contact me if you have a revised version so that I can upload it to this repository. </strong></p> <p> </p> <p> </p> <p> </p>
Blockchain Topics in energy sector from CoinDesk
<p>This dataset includes articles related to blockchain technology used in energy application. The dataset includes section, title, timestamp, author, and corpus. This dataset is used to spot relevant topics discussed on CoinDesk. Please consider that this dataset will be extended with more information from other forum.</p>
PyPSA-PL: Sectorally-integrated modelling of the Polish energy system until 2040
<p>This record contains all the scripts and data from the PyPSA-PL modelling exercise that supported the report:</p><ul><li>Kubiczek, P., Smoleń, M., Żelisko, W. (2023). Polska prawie bezemisyjna. Cztery scenariusze transformacji energetycznej do 2040 r. Instrat Policy Paper 06/2023. <a href="https://www.instrat.pl/polska-2040">https://www.instrat.pl/polska-2040</a></li></ul><p>The record structure is based on the PyPSA-PL repository <a href="https://github.com/instrat-pl/pypsa-pl">https://github.com/instrat-pl/pypsa-pl</a> (v2.1).</p>
Large-Scale Traveling Ionospheric Disturbances over the European sector during the geomagnetic storm on March 23-24, 2023: energy deposition in the source regions and the propagation characteristics
<p>IMAGE 2D Ionospheric Equivalent Currents for 23 and 24 March 2023 (https://space.fmi.fi/image/). </p> <p><em>We thank the institutes who maintain the IMAGE Magnetometer Array (<a href="https://space.fmi.fi/image/">https://space.fmi.fi/image/</a>): Tromsø Geophysical Observatory of UiT the Arctic University of Norway (Norway), Finnish Meteorological Institute (Finland), Institute of Geophysics Polish Academy of Sciences (Poland), GFZ German Research Centre for Geosciences (Germany), Geological Survey of Sweden (Sweden), Swedish Institute of Space Physics (Sweden), Sodankylä Geophysical Observatory of the University of Oulu (Finland), DTU Technical University of Denmark (Denmark), and Science Institute of the University of Iceland (Iceland). The provisioning of data from AAL, GOT, HAS, NRA, VXJ, FKP, ROE, BFE, BOR, HOV, SCO, KUL, and NAQ is supported by the ESA contracts number 4000128139/19/D/CT as well as 4000138064/22/D/KS. The authors would like to thank Dr. Liisa Juusola for providing the IMAGE 2D Ionospheric Equivalent Currents data.</em></p>
New Evidence on Employee Noncompete, No Poach, and No Hire Agreements in the Franchise Sector
<p>This repository holds data, replication files, and a machine learning classifier to detect no poach clauses for "New Evidence on Employee Noncompete, No Poach, and No Hire Agreements in the Franchise Sector<strong>,</strong>" forthcoming at Research in Labor Economics. </p> <p><strong>Abstract</strong>. This paper presents new evidence on anti-competitive practices in the franchise sector. Drawing from a corpus of Franchise Disclosure Documents (FDDs) filed by 3,716 franchise brands in years 2011- 2023 (partial), I report new information on franchise brands’ use of inter-firm non-solicitation (“no poach”) clauses barring recruitment between firms, no hire clauses barring employment, and franchisor requirements that franchisees use employee non-compete clauses barring workers from joining competitors. Regulatory actions that restricted the enforceability of anti-competitive clauses began to appear in FDDs in 2018. While non-solicitation and no hire clauses have declined in use, the use of non-competes remained stable over time. While prior evidence on anti-competitive practices largely draws from individual complaints, survey data, and limited hand-coded samples, this paper spotlights new methods for finding barriers to worker mobility in large, unstructured text corpora.</p> <p>The process to create the machine learning classifier from unstructured text is described in "<a href="https://arxiv.org/abs/2301.08549"><strong>Creating Data from Unstructured Text with Context Rule Assisted Machine Learning (CRAML)</strong></a>" with Stephen Meisenbacher.</p> <p>Replication materials are released under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. </p> <p>CRAML software is at <a href="https://github.com/sjmeis/CRAML_Beta/">https://github.com/sjmeis/CRAML_Beta/</a>.</p> <p>To acccess the text files used, I request you complete a <a href="https://forms.gle/KBJec1S6qNzt9KeU6">short form</a>. You may also use this form to notify the author of any issues/ questions. </p> <p>PDFs uploaded to DocumentCloud are available by searching documentcloud.org: +user:peter-norlander-103369 +access:public .</p> <p>I am grateful for support from the Economic Security Project Anti-Monopoly Fund; Loyola Rule of Law Institute; Loyola Quinlan School of Business; and Loyola University Chicago. I thank: Stephen Meisenbacher for development of the CRAML software, document collection, and computational assistance; Patricia Tabarani, Chloe Clark, Kayleigh Currier, Zach Nelson, and Damian Orozco for research assistance; Kate Bahn, Michael Lipsitz, Ioana Marinescu, Eric Posner, Todd Sorensen, Evan Starr, Spencer Weber Waller, David Weil, and two anonymous reviewers and the editors for feedback on earlier versions of the manuscript; participants at the 86th Midwest Economic Association Annual Meeting, the 74th Annual Labor and Employment Relations Association, 42nd Annual Strategic Management Society, the 82nd Academy of Management, and at Michigan State University School of Human Resources and Labor Relations. Errors are mine.</p> <p> </p> <p> </p> <p> </p>
GENDER DIVERSITY AND ITS IMPACT ON THE WOMEN PARTICIPATION IN THE WORKFORCE: WITH REFERENCE TO INDIAN CORPORATE SECTOR. (HRM: PARTICIPATION OF WOMEN IN THE WORK FORCE
<p>Gender roles have been two different sized fruits on the same tree branch since olden times. <br>The distinguished rule book for both males and females which had been followed for since <br>long still has its effects widely seen in the Indian corporate sector also. With the recurrent <br>fluctuation experienced in the women participation in the Indian workforce, the main pulling <br>back factor always has been Gender Diversity issues. There are many workplace factors <br>which infuse more power to this aspect called gender diversity; some of which are out of <br>one’s control while many of which are manageable. These factors include salary range, job <br>positions, promotional opportunities, workplace behavior and many more. The list is endless, <br>but the impact of all the gamut of such aspects has to be borne by the female employees. This <br>paper is a descriptive analysis on the effect of various factors on the gender diversity issues in <br>Indian Corporate sector. Secondary data has been used in order to correlate the factors like <br>salary, promotional opportunities, and other factors in the corporate sector with the gender <br>diversity issues. The statistical evidences have been depicted with the help of graphs and pie <br>charts which would contribute in making the whole situation of diversity issues more crystal <br>clear and transparent for the readers. The paper is an attempt towards finding the in-depth <br>causes for the ups and downs in the women participation in the nations’ workforce and also to <br>bring about a change in the current plight of female workers in Indian Corporate sector</p>
Old model, sector 2000 -2016
[Scientific Project](http://www.icac.cat/recerca/projectes-de-recerca/projecte/20942/) [Archaeological report 2016](https://www.researchgate.net/publication/311705780_Archaeological_report_-2016-_of_excavation_in_the_visigothic_settlement_of_Valencia_la_Vella_Riba-roja_del_Turia_Valencian_Country_Spain?_iepl%5BviewId%5D=XzB9abVr2fOR1kpvvnyc8cX4&_iepl%5Bcontexts%5D%5B0%5D=projectUpdatesLog&_iepl%5BtargetEntityId%5D=PB%3A311705780&_iepl%5BinteractionType%5D=publicationTitle) Source: Objaverse 1.0 / Sketchfab
Replication Data for: Methane emissions decreased in fossil fuel exploitation and sustainably increased in microbial source sectors during 1990–2020
<p>Model and observation data, used to prepare the figures in the main text, are submitted at this repository.</p>
The data for The Simulation of the Equinox Asymmetry of Ionospheric Electrodynamics at East-Asian Sector
<p>The data is used to describe the figure in the paper "The Simulation of the Equinox Asymmetry of Ionospheric Electrodynamics at East-Asian Sector"</p>
Reference Energy System for the Residential Sector
<p>This diagram illustrates a reference energy system designed for the residential sector.</p> <p>This visual aid can support the development of models on OSeMOSYS, LEAP, TIMES, or other energy modelling tools, as well as facilitate the integration of energy planning models like MAED and OSeMOSYS, or others.</p> <p>This material has been produced with support from the Climate Compatible Growth (CCG) programme. CCG is funded by UK aid from the UK government. However, the views expressed herein do not necessarily reflect the UK government's official policies. </p>
Reference Energy System for the Industry Sector
<p>This diagram illustrates a reference energy system designed for the industry sector.</p> <p>This visual aid can support the development of models on OSeMOSYS, LEAP, TIMES, or other energy modelling tools, as well as facilitate the integration of energy planning models like MAED and OSeMOSYS, or others.</p> <p>This material has been produced with support from the Climate Compatible Growth (CCG) programme. CCG is funded by UK aid from the UK government. However, the views expressed herein do not necessarily reflect the UK government's official policies. </p>
Reference Energy System for the Services Sector
<p>This diagram illustrates a reference energy system designed for the services sector.</p> <p>This visual aid can support the development of models on OSeMOSYS, LEAP, TIMES, or other energy modelling tools, as well as facilitate the integration of energy planning models like MAED and OSeMOSYS, or others.</p> <p>This material has been produced with support from the Climate Compatible Growth (CCG) programme. CCG is funded by UK aid from the UK government. However, the views expressed herein do not necessarily reflect the UK government's official policies. </p>
Reference Energy System for the Transport Sector
<p>This diagram illustrates a reference energy system designed for the transport sector.</p> <p>This visual aid can support the development of models on OSeMOSYS, LEAP, TIMES, or other energy modelling tools, as well as facilitate the integration of energy planning models like MAED and OSeMOSYS, or others.</p> <p>This material has been produced with support from the Climate Compatible Growth (CCG) programme. CCG is funded by UK aid from the UK government. However, the views expressed herein do not necessarily reflect the UK government's official policies. </p>
Carbon emission and NPV data of hydrogen system in transport and building sector
<p>The dataset contains the simulation environment data, including meteorological data, renewable energy system configuration, grid energy structure data, and energy balance data of the hydrogen systems; the comparison on the lifecycle carbon emissions between different vehicles; and results of the building-transportation energy sharing model, including the calculation process and results of net present value and carbon intensity of the hydrogen system.</p>
Análisis del sector inmobiliario: Propiedades en venta en la Región de Murcia.
<p>El conjunto de datos extraído se compone de información detallada sobre diversas propiedades inmobiliarias disponibles en la web de Arena Homes. Cada entrada en el dataset representa una propiedad específica y contiene atributos relevantes como la referencia, el precio, el número de habitaciones y de aseos, la ubicación y el tipo de propiedad. Además, se incluye un enlace a la imagen asociada con cada propiedad para una referencia visual. Este conjunto de datos proporciona una visión general de la oferta actual de inmuebles ofrecidos por Arena Homes, lo que puede resultar útil para analizar tendencias del mercado inmobiliario y tomar decisiones informadas sobre la compra o alquiler de propiedades.</p> <p>Nuestro dataset extraído incluye los siguientes campos:</p> <p>-Referencia: Identificador único de cada propiedad.</p> <p>-Precio: Precio de venta de la propiedad.</p> <p>-Habitaciones: Número de habitaciones en la propiedad.</p> <p>-Aseos: Número de baños en la propiedad.</p> <p>-Ubicación: Ubicación de la propiedad, incluyendo el nombre de la ciudad o barrio.</p> <p>-Tipo de propiedad: Categorización del tipo de propiedad, como piso, chalet, apartamento, etc.</p> <p>-Enlace de la imagen: URL de la imagen asociada con la propiedad.</p> <p>El período de tiempo al que pertenecen los datos no está indicado en el dataset. Los datos son actuales en el momento de la extracción, lo que significa que representan la oferta actual de propiedades inmobiliarias disponibles en el sitio web de Arena Homes.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.