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67 results for “software management”
NeuroGentoo Presentation - Bringing the Power of Gentoo Package Management to (Neuro)Scientific Software Environments
<p>Neuroscience, one of the most computation-reliant fields in the natural sciences, is dependent upon dozens of highly complex software suites, which scientists are often forced to manage manually. Upstream developers often ship bundled dependencies to better support this flawed workflow, and in the resulting mess documenting and reproducing analysis pipelines is neigh-impossible. We seek to correct these shortcoming of both modern software distribution as well as modern data science, by integrating high-quality ebuilds for neuroscientific software into the Gentoo Science Overlay. We also seek to publish a simple NuroGentoo world file (along with appropriate usage instructions) to allow scientists with access to OpenStack, Amazon Elastic Computing, or Docker to launch up and build a system fit for reproducing data analysis run on other NeuroGentoo systems with minimum effort.</p>
Unveiling Hurdles in Software Engineering Education: The Role of Learning Management Systems
<p>Learning management systems (LMSs) are established tools in higher education, especially in the field of software engineering (SE). The onset of the COVID-19 pandemic further amplified the utilization of these systems, which necessitated their integration into educational curricula for both lecturers and students. However, adopting LMSs within SE education has presented distinctive challenges impeding their seamless incorporation into the courses. This paper aims to scrutinize the challenges and requirements encountered by professors, lecturers, and students in the domain of SE education when using LMSs. We conducted an empirical study that included (i) a survey with 47 professors/lecturers and 133 students, (ii) an analysis of the ensuing data, and (iii) 18 additional interviews conducted with professors and lecturers to delve into nuanced variations in viewpoints. The findings derived from our study reveal that the challenges and requirements pertaining to LMSs are rather specific depending on the scope and size of the respective courses. Nevertheless, many participants have a consensus on numerous challenges and requirements for improving certain features of LMSs in order to improve their usage in SE education. The findings are valuable for advancing research and development in the field of LMSs and provide guidance for lecturers in SE education.</p>
Software and data underlying the article 'A serious game approach for lake modeling and management: the EscapeBLOOM'
<p>Here we share the player version of the EscapeBLOOM, a dummy version showcasing the techniques to create a similar digital escape room, and the anonymized data of the quantitative survey as presented in the publication 'A serious game approach for lake modeling and management: the EscapeBLOOM'.</p> <p>Anyone is free to play or adjust the game for their own educational purposes. The dummy and supplementary material of the publication 'A serious game approach for lake modeling and management: The EscapeBLOOM' <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.envsoft.2024.105941" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.envsoft.2024.105941</a> together provide guides on how to create a new game from the start and may help to adjust the existing game.</p> <p>The data of the survey was used for the analysis of perceived learning in the publication 'A serious game approach for lake modeling and management: the EscapeBLOOM'.</p>
Assessing the sustainability performance of sustainability management software - replication package
<p>This is the replication package for the article "Assessing the sustainability performance of sustainability management software", published in Technologies – SI „Advanced Green Information and Communication Technology“</p> <p><strong>Contents</strong><br> The repository contains the following files:</p> <ul> <li><em>Data_-_Scenario_Hardware_Measurement.csv:</em><br> measurement data acquired during the measurement of the standard usage scenario</li> <li><em>Data_-_Scenario_Log.txt:</em><br> timestamp log file for the measurements of the standard usage scenario</li> <li><em>Data_-_Baseline_Hardware_Measurement.csv:</em><br> baseline meaurements</li> <li><em>Data_-_Baseline_Log.txt:</em><br> baseline timestamp log file</li> <li><em>R_image.Rdata:</em><br> data is also available in an R image dump</li> <li><em>R_Analysis_Script.R:</em><br> analysis script, written in R</li> <li><em>Results_SCSS_WeSustain_ESM.pdf:</em><br> results of the analysis</li> <li><em>Results_and_calculation_for_Indicators_1.2.b_and_1.2.c.ods:</em><br> calculation for indicators 1.1.4.d) 1.2.b) and 1.2.c)</li> <li><em>Usage-scenario_WeSustain_ESM.pdf:</em><br> description of the standard usage scenario</li> </ul> <p><strong>Usage</strong><br> To recreate the analysis, run the R script and, if necessary, modify <em>lines 103 to 115</em> to fit the filenames where to find the data.<br> <em>Lines 193 to 217</em> need to be executed manually, to generate the desired plots and calculations.</p> <p>It is also possible to load the <em>R_image.RData</em> data dump into an R session, import the library `psych` (<em>line 2</em> in the script) and manually execute <em>lines 193 to 217</em> to generate the desired plots and calculations.</p>
BEE-STEWARD: a research and decision support software for effective land management to promote bumblebee populations
<p><span><span>The demand for agent-based models to explore the effects of environmental change on pollinator population dynamics is growing. However, models need a simple yet flexible interface to enable adoption by a wide range of stakeholders. </span></span><span><span>We introduce BEE-STEWARD: a research and decision-support software tool, enabling researchers, policy-makers, land management advisors, and practitioners to predict and compare the effects of bee-friendly management interventions on bumblebee populations over several years. </span></span><span><span>BEE-STEWARD integrates the BEESCOUT and <i>Bumble</i>-BEEHAVE agent-based models of bumblebee behaviour, colony growth and landscape exploration into a user-friendly interface, with reconstructed code, and expanded functionality. Bespoke automatic reports can be created to illustrate how different land management interventions can affect the densities of bumblebees and their colonies over time. </span></span><span><span>BEE-STEWARD could be an important virtual test-bed for scientists exploring the impacts of different stressors on bumblebees and used by those with little or no modelling experience, enabling a shared methodology between research, policy, and practice.</span></span></p>
BEE-STEWARD: a research and decision support software for effective land management to promote bumblebee populations
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Data and Software for "Probabilistic Trade-offs Analysis for Sustainable and Equitable Management of Climate-Induced Water Risks"
<p><span>Research data supporting the study "Probabilistic trade-offs analysis for sustainable and equitable management of climate-induced water risks"</span></p> <p><span>This repository provides data of the Stochastic Dual Dynamic Programming (SDDP) model, and the output results of the simulations of the various policies and climate scenarios considered in this study, as well as the code used for postprocessing and visualizing the results.</span></p> <p><strong><span>Contents</span></strong></p> <ol> <li><strong><span>Data: Model Inputs</span></strong><span><br>This folder contains the physical river network, reservoir and water demand, and economic data derived from the observed database.<br>The key files are:</span></li> <ul> <li><span>Input_HydrologicalData</span></li> <li><span>Input_SystemData</span></li> </ul> <li><strong><span>Results: Model Output Analysis</span></strong><span><br>This folder includes outputs from the Stochastic Dual Dynamic Programming (SDDP) model under various policies and climate scenarios. The results showcase optimized sectoral water use, including irrigated areas, hydropower generation, and allocations for agriculture, energy, and urban demands across spatial locations (upstream and downstream).<br>Key files include:</span></li> <ul> <li><strong><span>SDDP Model Outputs</span></strong><span> (MATLAB format): </span></li> <ul> <li><span>EnergyPriority_Baseline.mat</span></li> <li><span>EnergyPriority_2070.mat</span></li> <li><span>EnergyPriority_2100.mat</span></li> <li><span>AgriculturePriority_Baseline.mat</span></li> <li><span>AgriculturePriority_2070.mat</span></li> <li><span>AgriculturePriority_2100.mat</span></li> </ul> <li><strong><span>Extracted Model Results</span></strong><span> (Excel format): </span></li> <ul> <li><span>Organized for each policy and climate scenario to facilitate analysis.</span></li> </ul> </ul> <li><strong><span>Software: Data Analysis and Visualization</span></strong><span><br>Python scripts designed for outputs data analysis and visualization are included to reproduce the primary figures from the study.<br>Scripts provided:</span></li> <ul> <li><span>CDF_outflow.py</span><span>: Analyzes cumulative distribution functions for river discharge.</span></li> <li><span>CDF_sectors.py</span><span>: Examines sectoral water use distributions.</span></li> <li><span>PCP_SI.py</span><span>: Generates Parallel Coordinate Plots for trade-offs analysis.</span></li> </ul> <li><strong><span>Instructions: README File</span></strong><span><br>A comprehensive README file explains:</span></li> <ul> <li><span>Details of model input data.</span></li> <li><span>Instructions to interpret the SDDP model outputs.</span></li> </ul> </ol> <p><strong><span>Instructions:</span></strong><span><br></span><span>The Python scripts process Excel files from the model output results folder to generate and visualize the figures for the paper. Each step is clearly documented within the scripts.</span></p>
Agile Social Software Engineer: An Empirical Approach to Mitigate and Manage Social Debts in Agile Environments
<p>Replication package description:<br> "DataCollection.xlsx": Survey responses from Agile teams in weeks 1, 2, 3, 4 and 5.<br> <br> "DataAnalysis.xlsx": Analysis of the answers from the survey to answer the research questions proposed in this work.<br> Team-working issues that could lead to community smells can be found in TeamworkingIssues Tab.<br> The root causes of community smells in agile teams over weeks can be found in Rootcauses Tab.<br> Requests for Agile social guardian intervention can be found in Requestagileteams Tab.<br> Recurring needs and concerns in agile teams can be found in Needs_Concerns Tab.</p>
Supplementary Material to SBIE 2024:Achieving Project Management Educational Web-Tool Evolution Using Service-based Software
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A Versatile and Secure Data Management System API facilitating the Interconnection of any software component and Easy Data Access.
<p>In the context of the EU-funded project PILOTING (No. 871542), a versatile Data Management System (DMS) was deployed and facilitated the easy integration of nine different robotic systems and various payloads and the storing of all the data observations produced during the inspections. The DMS is designed under the DMS-Data Model (DMS-DM) and operates on top of a representational state transfer (REST) application programming interface (API) that provides a simplified way to exchange data through HTTP(S) requests from a client to the server. One of its key advantages is that it provides a great deal of flexibility so the model could accommodate extensions if needed. Data is not tied to resources or methods, so REST can handle multiple types of calls, return different data formats and even change structurally with the correct implementation of hypermedia. <br> It supports CRUD operations via GET, POST, PUT, PATCH, and DELETE HTTP methods and stores the data on a PostgreSQL object-relational database system. The REST API has been created with Python's Django (web framework) and Django REST Framework, a powerful and flexible toolkit for building Web APIs. <br> The constructed document presents the communication endpoints (DMS API’s Uniform Resource Identifiers (URIs)) under which an authorized user can have access to the DMS API and subsequently to the collected data. </p>
Study of a Prototype Software to Help Surgical Patients Manage Their Pain Medication
ClinicalTrials.gov study NCT05707247. IPD Sharing: Not stated. Countries: 1. Publications: 1.
SODALITE SOftware Defined AppLication Infrastructures managemenT and Engineering Overview Video
<p>This videos shows a generic description of the project vision, mision and objectives of SODALITE in Software engineering and DevOps world of research.</p>
Towards a Quantitative Model to Deal with Uncertainty Management in Software Projects
<p>The evolution of thinking in project management has raised interest in areas not yet explored by researchers and practitioners of project management, including the management of uncertainties associated with risk management. The correct risk and uncertainty management in software projects can represent a competitive differential for the software development industry. Despite the increasing use of uncertainty management strategies, many projects still fail. Some recent studies show that the current techniques used to manage uncertainties organize the project's known information, but give little or no indication of the unknown information or uncertainties associated with the project. These techniques do not take into account the impact of existing dependency and interdependence relationships between the various sources of uncertainties in the project. This work will apply Action Research to develop a model with a focus on uncertainty quantification techniques. This work aims to present a model with a focus on uncertainty quantification techniques that take into account the relationships of dependencies and interdependence that exist between the sources of risks and uncertainties in software projects and as a result, contribute with the advance of state of the art in the practice of risk and uncertainty management in project software.</p>
Data from: Evaluating conservation and fisheries management strategies by linking spatial prioritisation software and ecosystem and fisheries modelling tools
1. Well-designed marine protected area (MPA) networks can deliver a range of ecological, economic and social benefits, and so a great deal of research has focused on developing spatial conservation prioritization tools to help identify important areas. 2. However, whilst these software tools are designed to identify MPA networks that both represent biodiversity and minimize impacts on stakeholders, they do not consider complex ecological processes. Thus, it is difficult to determine the impacts that proposed MPAs could have on marine ecosystem health, fisheries and fisheries sustainability. 3. Using the eastern English Channel as a case study, this paper explores an approach to address these issues by identifying a series of MPA networks using the Marxan and Marxan with Zones conservation planning software and linking them with a spatially explicit ecosystem model developed in Ecopath with Ecosim. We then use these to investigate potential trade-offs associated with adopting different MPA management strategies. 4. Limited-take MPAs, which restrict the use of some fishing gears, could have positive benefits for conservation and fisheries in the eastern English Channel, even though they generally receive far less attention in research on MPA network design. 5. Our findings, however, also clearly indicate that no-take MPAs should form an integral component of proposed MPA networks in the eastern English Channel, as they not only result in substantial increases in ecosystem biomass, fisheries catches and the biomass of commercially valuable target species, but are fundamental to maintaining the sustainability of the fisheries. 6. Synthesis and applications. Using the existing software tools Marxan with Zones and Ecopath with Ecosim in combination provides a powerful policy-screening approach. This could help inform marine spatial planning by identifying potential conflicts and by designing new regulations that better balance conservation objectives and stakeholder interests. In addition, it highlights that appropriate combinations of no-take and limited-take marine protected areas might be the most effective when making trade-offs between long-term ecological benefits and short-term political acceptability.
Metadata crosswalks for software management plans at NFDI4DS hackathon maSMP 2023
<p>Software Management Plans (SMPs) help formalize a set of structures and goals that ensure the research software is accessible and reusable in the short, medium and long term. Although not as common as the Data Management Plans, SMPs are gaining attention, with different communities providing examples and guidance on around it (e.g., ELIXIR SMPs, eScience Center in the Netherlands SMP Guidance and the Max Plank Digital Libraries SMP).</p><p>Machine-actionable SMPs (maSMPs) aim at providing a semantic layer on top of SMPs in the form of metadata schemas. Based on the <a href="https://doi.org/10.37044/osf.io/k8znb">ELIXIR SMPs</a> and inspired by the work done on the Research Data Alliance (RDA) <a href="https://github.com/RDA-DMP-Common/RDA-DMP-Common-Standard">machine-actionable Data Management Plan (maDMP)</a> application profile, the SemTec team at ZB MED has created an <a href="https://zenodo.org/doi/10.5281/zenodo.7806638">maSMP metadata schema</a> using <a href="https://schema.org/">schema.org</a> as base vocabulary. </p><p>The latest version of such maSMP metadata schema takes advantage of the crosswalks created at the NFDI4DS hackathon on maSMPs 2023.11.28 to 2023-12-01 organized by the SemTec team at ZB MED. The crosswalks data corresponding to Max Plank Digital Library SMP, <a href="https://doi.org/10.37044/osf.io/k8znb">ELIXIR SMPs</a>, and <a href="https://doi.org/10.14454/3w3z-sa82">DataCite Metadata Schema 4.4 - OutputManagementPlan</a> are included in this dataset collection. The files in the dataset collection are:</p><ul><li>"2023.11.29 maSMP crosswalk - NFDI4DS hackathon - Software.csv" - Crosswalk from the maSMP vr 2.0.0 to the Max Plank Digital Library SMP, <a href="https://github.com/KnowledgeCaptureAndDiscovery/somef">SOMEF</a>, and <a href="https://doi.org/10.37044/osf.io/k8znb">ELIXIR SMPs</a></li><li>"2023.11.29 maSMP crosswalk - NFDI4DS hackathon - MngPlan.csv" - Crosswalk from the maSMP to <a href="https://doi.org/10.14454/3w3z-sa82">DataCite Metadata Schema 4.4 - OutputManagementPlan</a> and the Max Plank Digital Library SMP</li><li>"2023.11.29 maSMP crosswalk - NFDI4DS hackathon - RDMO-SMP.csv" - Crosswalk from the Max Plank Digital Library SMP to metadata properties from different vocabularies</li><li>"Tables description.png" - Image showing a crosswalk template</li></ul><p>We acknowledge the feedback provided by other participants in the NFDI4DS hackathon on maSMPs (Esteban Gonzalez <a href="https://orcid.org/0000-0003-4112-6825">ORCID:0000-0003-4112-6825</a>, Yves Vincent Grossmann <a href="https://orcid.org/0000-0002-2880-8947">ORCID:0000-0002-2880-8947</a>, Carlos Utrilla Guerrero <a href="https://orcid.org/">ORCID:0000-0002-9994-1462</a>, Mariaisabel Gonzalez-Ocanto <a href="https://orcid.org/0000-0001-5485-9724">ORCID:0000-0001-5485-9724</a>,Thomas Pronk <a href="https://orcid.org/0000-0001-9334-7190">ORCID:0000-0001-9334-7190</a>, David Wallace <a href="https://orcid.org/0000-0001-8958-4601">ORCID:0000-0001-8958-4601</a>, Jürgen Windeck <a href="https://orcid.org/0000-0003-1909-4353">ORCID:0000-0003-1909-4353</a>).</p><p>The maSMP project is part of the NFDI4DataScience project funded by the German Research Foundation (DFG), project number 460234259. This dataset was created during the NFDI4DS hackathon on maSMPs at ZB MED 2023.</p><p> </p>
[GAS 2022] Software Project Management Anti-Patterns for Video Game Development
<p>This dataset contains an analysis of 440 project management problems described in game postmortems from gamedeveloper.com (formerly Gamasutra). We grouped these problems into candidate anti-patterns, an then we link these candidates with anti-patterns documented in the Software Engineering literature. Specifically, we aim to answer the following research question how video game anti-pattern fits into the software anti-patterns literature? </p>
Corpus of Literature: Approaches to teaching software project management: a systematic literature review
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SECO-RCR: A Tool to Manage Requirements Change in Software Ecosystems
<p>Video de apresentação para a ferramenta SECO-RCR submetido ao SBES Tools 2024.</p>
Technology Acquisition Plans to Foster Supply Chain Risk Management Learning Outcomes in Project-Based Software Development Courses: Raw Data and TAP Template
<p>This is a data set and TAP template to accompany the paper</p> <p>"Technology Acquisition Plans to Foster<span> </span>Supply Chain Risk Management Learning Outcomes in Project-Based Software Development Courses" by Tenbergen and Mead published at the 36th International Conference on Software Engineering Education and Training.</p>
Supplementary material of Investigating User Feedback from a Crowd in Requirements Management in Software Ecosystems
<p>Supplementary material of Investigating User Feedback from a Crowd in Requirements Management in Software Ecosystems.</p>
ScienceDex guides
Understand access before you commit
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.