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13,276 results for “IT management”
Dataset for: Exploring the experiences of academic libraries with research data management: a meta-ethnographic analysis of qualitative studies
<p><strong>Overview</strong></p> <p>This dataset contains the raw data for the manusript:<br> Perrier L, Blondal E, MacDonald H. Exploring the experiences of academic libraries with research data management: a meta-ethnographic analysis of qualitative studies. 2018; 40(3-4): 173-183. doi: 10.1016/j.lisr.2018.08.002</p> <p>Full-text available at: <a href="https://doi.org/10.1016/j.lisr.2018.08.002">https://doi.org/10.1016/j.lisr.2018.08.002</a> </p> <p><strong>Data and Documentation Files</strong></p> <p>Five files make up the dataset:</p> <ol> <li>Data Dictionary: RDMMetaEthnography_DataDictionary_v1.pdf</li> <li>Data Abstraction Sheet: RDMMetaEthnography_StudyCharacteristics.csv</li> <li>Data Abstraction Sheet: RDMMetaEthnography_ParticipantCharacteristics.csv</li> <li>Data Abstraction Sheet: RDMMetaEthnography_Outcomes.csv</li> <li>Data Abstraction Sheet: RDMMetaEthnography_COREQ,csv</li> </ol> <p>Contact: Laure Perrier: <a href="https://orcid.org/0000-0001-9941-7129">orcid.org/0000-0001-9941-7129</a></p>
Data Management Plan
<p>Video of a presentation for the training seminars in Research Data Management of the FoDaKo-project: <a href="https://fodako.de/">https://fodako.de</a></p>
ISO TR 21965 Information and documentation -- Records management in enterprise architecture - Archi tool project file
<p>This file is a project file, in XML format, of the freeware too Archi (version 4.2.0) modeling the ArchiMate diagrams present in the ISO/DTR 21965:2019.</p> <p>Archi tool is freely available from https://www.archimatetool.com</p> <p>The purpose of the ISO/TR 21965:2019 is to provide a common reference for Records managers (or information managers in general) and Enterprise architects about requirements for records processes and systems. The goal is to establish the Records manager as a key stakeholder in Enterprise Architecture, by expressing the related Records Management Viewpoint.</p> <p>This viewpoint makes use of the concepts of “concerns” and “system of concerns” as defined in ISO/IEC/IEEE 42010:2011, and of the concepts of “stakeholders”, “viewpoint, “view” and “model” as also defined coherently in that standard and in the main Enterprise Architecture references of TOGAF and ArchiMate. With reference to ArchiMate, the main scope of this viewpoint is the Motivational aspect and the layers Strategy and Business, with minor considerations for the layers of Application and Implementation. The Open Group Architecture Framework (TOGAF) is used to inform how this Records Management Viewpoint relates to the Architecture Development Method (ADM).</p> <p>The edition of the file is work of the author, but the intelectual content of the file is the resulting of the work of the ISO working group responsible by the production of the Technical Report: ISO/TC 46/SC 11/WG 14 - Records requirements in Enterprise Architecture</p> <p> </p>
Plankton Temperature Measurements - Data Management - University of Tennessee - Mock Data
<p><strong>Comparison of conochilus unicornis (CONI) and conochilus hippocrepus (CHIP) depth and colony size over time at three different locations. </strong></p> <p>This contains colony size, depth, and density measurements from Name Pond and the data on which these data were gathered wereTHESE DATES.</p> <p><a href="https://zenodo.org/api/files/984109f0-dde8-46b7-bf8c-5556ac8b76b2/SEH_PlanktonNamePond_v7.27.2012.csv">SEH_PlanktonNamePond_v7.27.2012.csv </a></p> <p>This contains time, temperature, colony size, depth, and density measurements from Name Pond and the data on which these data were gathered wereTHESE DATES.</p> <p><a href="https://zenodo.org/api/files/984109f0-dde8-46b7-bf8c-5556ac8b76b2/SEH_PlanktonTempB_v.7.27.2012.csv">SEH_PlanktonTempA_v.7.27.2012.csv </a></p> <p>This contains time, temperature, colony size, depth, and density measurements from site A and the data on which these data were gathered wereTHESE DATES.</p> <p><a href="https://zenodo.org/api/files/984109f0-dde8-46b7-bf8c-5556ac8b76b2/SEH_PlanktonTempB_v.7.27.2012.csv">SEH_PlanktonTempB_v.7.27.2012.csv </a></p> <p>This contains time, temperature, colony size, depth, and density measurements from Site B and the data on which these data were gathered wereTHESE DATES.</p> <p><strong>Metadata</strong></p> <p>Date: Day that samples were collected</p> <p>Time_Day_Night: Gives time that the sample was gathered in the day</p> <p>Temp_C: Temperature of the water containing the plankton.</p> <p>CONI: Conochilus unicornis - species of plankton</p> <p>CHIP: Conochilus hippocrepis - plankton</p> <p>XXXX_ColonySize_mm: Average diameter (mm) of 5 randomly chose plankton colonies in the sample </p> <p>Temp: TemperatureYSI probe taken once at each depth</p> <p>ChlorophyllA_Units: Chlorophyll A values</p>
Quantitative assessment of research data management practice
<p>This survey aims to investigate research data management practices in academic institutions. The survey comprises questions common to all institutions as well as institution-specific ones. Common questions were drafted in the frame of a collaboration between several RDM services: Tu Delft (team effort), EPFL (team effort), University of Cambridge (notably Marta Busse) and University of Illinois (notably Heidi Imker). The first survey was run by TU Delft and EPFL only end of 2017. In total, 1263 responses where collected (680 from TU Delft, 235 from EPFL and 348 from the University of Cambridge) and are published here. The results of each institution are provided in Microsoft Excel 2007 (XLSX) format. Consolidated results are provided in CSV format</p> <p>The first lines of the CSV file contains the question asked to researchers. Each further line contains the response of a researcher; answers to institution-specific questions are set to N/A for researchers of the other institutions. Column delimiters are commas(,), quote chars are double-quotes (") and subfield separators are semi-columns (;). The text encoding is UTF-8.</p> <p>More information about this survey as well as the exact survey questions and a detailed description how the survey might be re-used by other institutions is available on the project page on the Open Science Framework: htts://osf.io/mz3fx/ For any questions contact datastewards@tudelft.nl or researchdata@epfl.ch</p>
Data set for risk management in the allocation of vehicles to tasks in transport companies using a heuristic algorithm
<p>The purpose of this dataset is to enable the replication of the research results presented in the article: Izdebski, M. (2023). Risk management in the allocation of vehicles to tasks in transport companies using a heuristic algorithm. Archives of Transport, 67(3), 139-153. https://doi.org/10.5604/01.3001.0053.7463 - published online: 2023-09-30, which discusses the allocation problem of vehicles to tasks, taking into account risk issues.</p> <p>Dataset contains:</p> <ul> <li>Readme.txt: description of the dataset</li> <li>InputData.xlsx: Contains the input data used in the model</li> <li>DistributionFit.xlsx: Compliance testing and distribution parameters for road accidents of any type and collision-type</li> <li>OutputAssignment.xlsx: Results of assignment and alghoritm tests</li> </ul> <p>The dataset was created as part of the E-Laas project (Energy optimal urban logistics As A Service).<br>Project implemented as part of the call ERA-NET Cofund Urban Accessibility and Connectivity (ENUAC China Call) organized by JPI Urban Europe and the National Natural Science Foundation of China (NSFC). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 875022.<br> E-Laas project is carried out in an international consortium. Project coordinator in Europe: Chalmers University of Technology (Sweden), project coordinator in China: Shanghai University (China), consortium members: Tsinghua University (China), Warsaw University of Technology (Poland), cooperation partners: Stockholms stad, Trafikkontoret (Sweden), ParkUnload (Spain), Metropolis GZM (Poland), Shanghai Urban-Rural Construction and Transportation Department (China), Volvo Group Trucks Technology and Operations (Sweden).<br>- The Chinese part of the project is funded by National Natural Science Foundation of China.<br>- The Swedish part of the project is funded by Swedish Energy Agency.<br>- The Polish part of the project is funded by the National Science Centre, Poland (project no. 2022/04/Y/ST8/00134). The value of the co-financing is PLN 878,107.00. Project duration 27/04/2023 - 26/04/2026 (36 months).</p>
Respondents' perspectives on the impact of digital data-based health services on disaster risk management in Indonesia.
<p>This data contains respondents' perspectives on the impact of digital data-based health services on disaster risk management. Digital health services are the implementation of digital, information, and communication technologies in the context of health services. Digital health services include: mHealth, Health Information Technology, Wearable Devices, Telehealth and Telemedicine, and Personalized Medicine. </p> <p>Data was collected and processed as part of the ODDEA (Overcoming Digital Divide Between Europe and Southeast Asia) EU research project (Project ID: HORIZON MSCA-SE 101086381) would be advisable.</p>
Demo of the alpha version of MEMORISE Document Manager
<p>Video demonstration showing the basic workflow of the MEMORISE Document Manager</p>
SHEERM: Sustainable Household Energy and Environment Resources Management dataset
<p>This dataset represents a novel and extensive dataset featuring comprehensive cross-sectional data of household electrical load, energy cost, and on-premises solar energy production, directly linked to solar radiation and weather parameters. <br>The SHEERM dataset is essential for understanding and optimizing energy utilization to achieve Sustainable Development Goals (SGD) 7, 9, 11 and 13. It provides data about solar energy production, weather conditions, residential energy needs, and market prices. The combination of these variables facilitates multifaceted analysis, fostering advancements in renewable energy forecasting, climate-sensitive environments, grid management, and energy policy formulation.<br>Together with the SHEERM dataset, there is a paper that details the data collection process, including the sources and methodologies employed. Adhering to established literature, we developed and implemented machine learning models that comprehensively validate the data. Furthermore, as usage notes, we offer additional results by applying various machine-learning approaches to the provided data.<br>The SHEERM dataset aims to help design new energy systems that enhance sustainable energy strategies and demonstrate their potential to accelerate the transition towards renewable energy and carbon neutrality.</p>
Research data management consulting requests at Charité - Universitätsmedizin Berlin
<p><strong>The dataset documents</strong> <strong>consulting requests and corresponding consultations on topics related to research data management </strong>at the Charité - Universitätsmedizin Berlin, a university hospital and large biomedical research institution. Version v2.0 includes requests between late 2018 and October 2024.</p> <p>Please note that the documentation is not complete. Sometimes it is detailed, sometimes very brief, and rarely notes are completely absent. In many cases, I made detailed notes outside of this table, and these are not included in the dataset.</p> <p>The shared files all contain the same information or a subset of it. Different file formats have been shared to facilitate reuse and text search.</p> <p>See the readme file for detailed description of data fields and further disclaimers.</p>
US Smart Fleet Management Market 2024 - 2033
<p><a href="https://www.custommarketinsights.com/report/us-smart-fleet-management-market/" target="_blank" rel="noopener">US Smart Fleet Management Market</a> Size, Trends and Insights By Mode of Transport (Automotive, Rolling Stock, Marine, Others), By Hardware (Tracking, Optimization, Advanced Driver Assistance Systems (ADAS), Remote Diagnostics, Others), By Connectivity (Short Range Communication, Long Range Communication, Cloud), By Solutions (Vehicle Tracking, Fleet Optimization), and By Region - Industry Overview, Statistical Data, Competitive Analysis, Share, Outlook, and Forecast 2024–2033</p>
Video Series: Integrated Pest Management focusing on disease control in cereals
<p>Welcome to this video series on IPM, focusing on disease control in cereals. </p> <p>The challenge of IPM is to make the control methods we use appropriate to the circumstances, and to balance between the productivity of the crop and minimising the impact on the environment. The control decisions we make on one field or in one season may not be appropriate in another set of circumstances – there is no ‘blue print’. In these videos we delve into the physiology of the crop, the epidemiology of the diseases and how different control methods work. By understanding the biology of the systems we're trying to control, we're better equipped to make appropriate decisions. Going into depth means we can’t cover all aspects of IPM. In practice, decisions about disease control are being made alongside decisions about invertebrate pests and weeds, and in the wider context of integrated crop management. In the UK, information on those topics is available from organisations such as LEAF, AHDB and the Voluntary Initiative. Nevertheless, disease control is still a big topic, so we have broken it down into bite size chunks - although each video is still a pretty substantial bite and will need some digesting.</p> <p>The videos can be viewed in any order that interests you, but they'll make most logical sense viewed in the order in the menu.</p> <p>Links to the videos can be found in the summary document. </p> <p>PDF versions of the video presentations are provided. </p>
Data and statistical code for "Reconciling biodiversity with timber production and revenue via an intensive forest management experiment"
<p><strong>Abstract</strong></p> <p>Understanding how land-management intensification shapes the relationships between biodiversity, yield and economic benefit is critical for managing natural resources. Yet, manipulative experiments that test how herbicides affect these relationships are scarce, particularly in forest ecosystems where considerable time lags exist between harvest revenue and initial investments. We assessed these relationships by combining 7 years of biodiversity surveys (>800 taxa) and forecasts of timber yield and economic return from a replicated, large-scale experiment that manipulated herbicide application intensity in operational timber plantations. Herbicides reduced species richness across trophic groups (-18%), but responses by higher-level trophic groups were more variable (0–38% reduction) than plant responses (-40%). Financial discounting, a conventional economic method to standardize past and future cashflows, strongly modified biodiversity-revenue relationships caused by management intensity. Despite a projected 28% timber yield gain with herbicides, biodiversity-revenue tradeoffs were muted when opportunity costs were high (i.e., economic discount rates ≥7%). Although herbicides can drive biodiversity-yield tradeoffs, under certain conditions, financial discounting provides opportunities to reconcile biodiversity conservation with revenue.</p>
Carbon emission and lifecycle costs supporting digital twins for managing railway maintenance and resilience
<p>The development of railway construction increases the system complexity, which results in difficulty in management with traditional methods. Building Information Modelling (BIM) as an interoperable concept is benefits via whole life-cycle assessment (LCA) of the project, and it has been widely adopted in architecture, construction, and engineering (ACE) fields. This dataset of lifecycle cost and carbon footprint supports the digital twins for managing railway maintenance and resilience.</p>
Data from: Species delimitation in endangered groundwater salamanders: implications for aquifer management and biodiversity conservation
Groundwater-dependent species are among the least-known components of global biodiversity, as well as some of the most vulnerable because of rapid groundwater depletion at regional and global scales. The karstic Edwards–Trinity aquifer system of west-central Texas is one of the most species-rich groundwater systems in the world, represented by dozens of endemic groundwater-obligate species with narrow, naturally fragmented distributions. Here, we examine how geomorphological and hydrogeological processes have driven population divergence and speciation in a radiation of salamanders (Eurycea) endemic to the Edwards–Trinity system using phylogenetic and population genetic analysis of genome-wide DNA sequence data. Results revealed complex patterns of isolation and reconnection driven by surface and subsurface hydrology, resulting in both adaptive and non-adaptive population divergence and speciation. Our results uncover new cryptic species diversity and refine the borders of several threatened and endangered species. The U.S. Endangered Species Act has been used to bring state regulation to unrestricted groundwater withdrawals in the Edwards (Balcones Fault Zone) Aquifer, where listed species are found. However, the Trinity and Edwards–Trinity (Plateau) aquifers harbor additional species with similarly small ranges that currently receive no protection from regulatory programs designed to prevent groundwater depletion. Based on regional climate models that predict increased air temperature, together with hydrologic models that project decreased springflow, we conclude that Edwards–Trinity salamanders and other co-distributed groundwater-dependent organisms are highly vulnerable to extinction within the next century.
Doctoral Students' Educational Needs in Research Data Management: Quantitative Data of Perceived Importance and Current Competencies
<p>These data sets include numerically coded answers to Likert-like scale questions concerning the importance and perceived current research data management competencies of doctoral students. Interviewees were 35 doctoral students and faculty members. Interview forms are attached. The data is connected with the research article: https://doi.org/10.2218/ijdc.v16i1.684</p>
Dataset for review on innovative contracts for the promotion of biodiversity and ecosystem services in agricultural management: contract design and governance characteristics
<p>Dataset for H2020 project Contracts2.0 (GA No 818190), WP2, Task 2.1, Deliverable 2.1.</p> <p>This dataset contains the information needed to reproduce the results in:<br> Bredemeier, Birte; Herrmann, Sylvia; Sattler, Claudia; Prager, Katrin; van Bussel, Lenny, Rex, Julia (submitted): Can the greater integration of biodiversity and ecosystem services into agricultural management be achieved through innovative contract design? Submitted to Ecosystem Services.<br> <br> The Contracts2.0 project aims to develop novel contract-based approaches to incentivise farmers for the increased provision of environmental public goods alongside private goods.<br> Based on a literature review and integration of expert knowledge, we identified a comprehensive set of approaches to innovative contracts deviating from mainstream AECM contracts, and provide an overview of the variety of contracts currently being tested and experimented with. This includes different contract types like innovative Payments for Ecosystem Services (PES) approaches, value chain approaches and land tenure contracts, as well as their hybrids.</p> <p><br> We analysed 62 cases providing insights into characteristics of contract design and contract governance and the wider policy framework.</p> <p><br> The present dataset contains information on the criteria and specifications used to describe the cases studied, as well as the evaluation of each case.</p> <p><br> This information has been compiled to the best of our knowledge based on the sources available.<br> <br> For further information on the project Contracts2.0, please visit our website www.project-contracts20.eu. </p>
Data and Code from: On-farm land management strategies and production challenges in United States Organic Agricultural Systems.
<p>This repository contains data and code used in:</p> <p>Isaac Mpanga, Russel Trondstad, Jessica Guo, David LeBauer, and John Omololu, 2021. On-farm land management strategies and production challenges in United States Organic Agricultural Systems. Current Research in Environmental Sustainability.</p> <p>It provides USDA Surveys of Agricultural Production from 2008-2019 to investigate state and national trends by state in organic farm area, number, and sales, as well to evaluate national trends in on-farm land-use practices and challenges facing US organic production.</p> <p>It also includes code used to transform, visualize, and analyze the data, and derived data products - notably organic farm area and sales with values imputed to correct for redacted state level measures.</p>
Data From: Toward a Better Data Management Plan: The Impact of DMPs on Grant Funded Research Practices
<p>Researchers from Montana State University analyzed 186 National Science Foundation (NSF) data management plans, using the Data Management Plans As a Research Tool (DART) rubric.</p>
Research Beyond the Lab, Spring Term 2022, Global Health Engineering, ETH Zurich. Raw data and analysis-ready derived data on waste management in public spaces in Zurich, Switzerland.
<p>This repository contains all raw and derived data produced as part of the <a href="https://rbtl-fs22.github.io/website/">ETH Zurich course "Research Beyond the Lab: Open Science and Research Methods for a Global Engineer" (151-8102-00L)</a> offered in spring term 2022.</p> <p>Students were assigned teams of four to conduct a collaborative research project broadly addressing the theme of “Trash in the Public Spaces of Zurich” in collaboration with <a href="https://www.stadt-zuerich.ch/ted/de/index/entsorgung_recycling.html">Entsorgung & Recycling Zürich (ERZ)</a>, the waste management department at Stadt Zürich.</p> <p>Research methods and design are taught in the first half of the course. Surveys and a waste characterisation study are then designed based on the research questions students have developed in their respective teams. The collected raw data is used in the course to teach principles of research data management, tidy data structures, reproducible research with R & RStudio, and collaboration and version control with Git & GitHub.</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.