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1,146 results for “collaboration;”
FAIRmat Tutorial 4: NOMAD Oasis and FAIR data collaboration and sharing
<p>FAIRmat further develops NOMAD from a central publishing service to a federated data management platform. The NOMAD Oasis is part of this. Institutes, universities, and research groups use NOMAD Oasis as a local repository to manage their research data. Each method is different and requires ways of data acquisition, different data formats, different analysis tools, but FAIR-ness requires that all data is well described with rich specific metadata.</p> <p>In this tutorial, we focus on how to get started with NOMAD Oasis and adapt it to your research. One the first day, two talks will introduce you the general FAIRmat strategy and its "bottom-up" approach to manage heterogenous but FAIR data. On the second day, we will give the practical, step-by-step guides to get started with an Oasis: How you can install NOMAD Oasis, create example data, add schemas, and create ELNs.</p> <p> </p> <p><strong>Disclaimer:</strong> NOMAD is being continuously developed based on input and feedback from the scientific community. Hence the features, services or interface may have changed since the time of recording of this video. For up-to-date information please consult our latest tutorials and the NOMAD documentation <a href="https://nomad-lab.eu/prod/v1/docs/">https://nomad-lab.eu/prod/v1/docs/</a></p> <p><strong> </strong></p>
Diversity's Role in Collaboration and Conflict: A Case-Study of React.js
Open the record for dataset details and reuse information.
Open Access in the Global South: Perspectives from the Open and Collaborative Science in Development Network
<p>As with science in general, the discussion around open access has generally been driven by the institutions and perspectives of western or global North countries. However, approaches to open access are far more diverse and there are alternative approaches that have not gained visibility, especially in historically marginalized communities. This presentation will present some key lessons of the OCSDNet http://ocsdnet.org. The OCSDNet is a research network that engaged in participatory research and consultation with scientists, development practitioners, community members and activists from 26 countries in Latin America, Africa, the Middle East and Asia to understand the values at the core of open science in development. What we learned is that there is not one right way to do open science, and “openness” requires constant negotiation and reflection, and the process will always differ by context due to historical and socio-political factors. The set of seven values and principles at the core of the OCSDNet manifesto will be discussed for a more inclusive open science in development. More important, we will discuss the implications of these values in relation to the aspirations and features of COAR’s Next Generation Repository.</p>
Results of "Collaborative Spatial Reuse in Wireless Networks via Selfish Multi-Armed Bandits"
<p>This dataset contains the results obtained for the article "Collaborative Spatial Reuse in Wireless Networks via Selfish Multi-Armed Bandits", authored by Francesc Wilhelmi, Cristina Cano, Gergely Neu, Boris Bellalta, Anders Jonsson and Sergio Barrachina. The article has been sent to Elsevier Ad-hoc Networks.</p> <p>The content of this dataset has been obtained by means of the code allocated in the following GitHub repository: <a href="https://github.com/fwilhelmi/collaborative_sr_in_wns_via_selfish_mabs">https://github.com/fwilhelmi/collaborative_sr_in_wns_via_selfish_mabs</a></p> <p>Contact information: francisco.wilhelmi@upf.edu</p>
Collaboration with the Researchers – Content, Presentation systems and Techniques (10min)
<p>10minute version of the virtual presentation of "Collaboration with the Researchers – Content, Presentation systems and Techniques"</p>
Semantic Triples from "A Collaborative, Realism-Based, Electronic Healthcare Graph: Public Data, Common Data Models, and Practical Instantiation"
<p>These RDF triples (<a href="https://zenodo.org/api/files/3d3308cb-8221-4a17-abc5-0ae32bb33f26/synthea_graph_exportable.nq.zip?versionId=7aff7c4a-bb0c-46ae-b006-7a80bcec0925">synthea_graph_exportable.nq.zip</a>) are the result of modeling electronic health records (<a href="https://zenodo.org/api/files/3d3308cb-8221-4a17-abc5-0ae32bb33f26/synthea_csv_output_turbo_cannonical.zip">synthea_csv_output_turbo_cannonical.zip), </a>that were synthesized with the Synthea software (https://github.com/synthetichealth/synthea). Anyone who loads them into a triplestore database is encouraged to provide feedback at https://github.com/PennTURBO/EhrGraphCollab/issues. The following abstract comes from a paper, describing the semantic instantiation process, and presented to the ICBO 2019 conference (https://drive.google.com/file/d/1eYXTBl75Wx3XPMmCIOZba-8Cv0DIhlRq/view).</p> <p>ABSTRACT: There is ample literature on the semantic modeling of biomedical data in general, but less has been published on realism-based, semantic instantiation of electronic health records (EHR). Reasons include difficult design decisions and issues of data governance. A collaborative approach can address design and technology utilization issues, but is especially constrained by limited access to the data at hand: protected health information.</p> <p>Effective collaboration can be facilitated by public EHR-like data sets, which would ideally include a large variety of datatypes mirroring actual EHRs and enough records to drive a performance assessment. An investment into reading public EHR-like data from a popular common data model (CDM) is preferable over reading each public data set’s native format.</p> <p>In addition to identifying suitable public EHR-like data sets and CDMs, this paper addresses instantiation via relational-to-RDF mapping. The completed instantiation is available for download, and a competency question demonstrates fidelity across all discussed formats.</p>
Enhancing Collaborative Care in Schizophrenia: A Comparative Analysis of ICF Core Sets Assessments by Occupational Therapy and Mental Health Social Work Students
<p>This repository contains the R code, dataset, and README file for the network analysis of ICF (International Classification of Functioning, Disability, and Health) assessments. The study compares the assessments conducted by occupational therapy students and mental health social work students, analyzing centrality measures and Bridge Expected Influence within their respective networks.</p>
Data for the Reproducibility of the Report: Collaboration between IRCC Candiolo and OSR TIGET, 2024
<p>Collection of processed <code>.Robj</code> files (primarily Seurat spatial transcriptomics datasets) and the original publicly available data for reproducibility of the report generated in collaboration between OSR-TIGET and IRCC Candiolo (academic year 2024). For complete reproduction, visit: https://github.com/carloelle/Report_OSR_Candiolo_2024 .</p> <p>All data provided here is publicly available, and no data leakage has occurred.</p>
Dataset: Towards a Knowledge Management Framework for LLM-Generated Personas in Collaborative Systems
Open the record for dataset details and reuse information.
Dataset on an online collaborative learning situation in acomputer networks course
<p>Here you can find a dataset of a collaborative learning situation. Students were enrolled in two undergradute courses on computer networks where they were required to carry out a set of learning activities supported by Moodle and an online collaborative environment called CoTrackV2. The data collected includes logs of the writing process of shared documents, logs of the chat messages between the group members, and logs from Moodle with coarser-grained information about course-level interactions. This dataset has been generated with the aim of allowing researchers to study self-and socially-shared regulation in online environments.</p> <p>There will be 6 files:</p> <ul> <li>document_logs.csv</li> <li>chat_logs.csv</li> <li>moodle_logs.csv</li> <li>individual_submissions.csv</li> <li>learning_design.csv</li> <li>final_questionnaire.csv</li> </ul>
Analysing Scientific Mobility and Collaboration in the Middle East and North Africa
<p>Data set belonging to the paper 'Analysing Scientific Mobility and Collaboration in the Middle East and North Africa' (https://arxiv.org/abs/2009.07815v2)</p>
'Psyché' as a Rosetta stone? Assessing collaborative authorship in the French 17th century theatre -- supplementary material
<p>Supplementary material for the paper:</p> <p>‘Psyché’ as a Rosetta Stone? Assessing Collaborative Authorship in the French 17th Century Theatre</p> <p>presented at Computational Humanities Research 2021.</p>
MLR - Mapping Collaboration Challenges in Hybrid Working Environments of Information Technology Teams
<p> Supplementary artifact for Mapping Collaboration Challenges in Hybrid Working Environments of Information Technology Teams</p>
The Smart City as a Field of Innovation: Effects of Public-Private Data Collaboration on the Innovative Performance of Small and Medium-Sized Enterprises in China
<p>Data is increasingly considered to be a key component in stimulating innovation (Cockburn, Henderson, and Stern, 2019). Numerous promising possibilities have been opened up by rapidly emerging, data-intensive technologies, including the Internet of Things (IoT) and artificial intelligence. The analysis and interpretation of big data are critical in the growth of technology firms in terms of AI training and computing capabilities (Allam and Dhunny, 2019). Small and medium-sized enterprises (SMEs), with their limited resources internally, particularly face a serious challenge of implementing innovation that depends upon data.</p> <p>The smart city provides an important opportunity for creating data-driven innovation. Significant amounts of data are increasingly available from various sources through sophisticated devices and equipment scattered in smart cities. Many smart city projects across the globe provide rich opportunities for SMEs to explore data-driven innovation (Bresciani, Ferraris, and Del Giudice, 2018). China, in particular, has recently been active in collecting and utilizing various kinds of data in smart cities. The availability of and access to data help to improve the software development of firms in China, where massive amounts of data resources are held by the government (Beraja, Yang, and Yuchtman, 2022).</p> <p>In the process of smart city development, there are also many tasks that are complementary to each other, including connecting databases, building online platforms that connect different data coming from different data sources, operating online platforms, and providing products and services to citizens. These diverse kinds of tasks involved in smart city projects initiated by local governments have brought about new business opportunities for innovative SMEs in China. To implement the policies of encouraging the development of SMEs by the central government, municipal governments have introduced policies that give priority to SMEs in participating in smart city projects (Ministry of Industry and Information Technology, 2016). Those companies that have access to the data held by government agencies are expected to benefit from utilizing the rich data for creating innovative products and services.</p> <p>There were few empirical studies conducted, however, to examine how data are actually managed and provided in smart cities and how they affect companies’ innovative activities. It remains unclear how public agencies and private enterprises collaborate on data and how that influences the innovation performance of SMEs in China. In smart cities, different types of public-private collaboration are involved, including hardware purchase, platform building, platform operation, and data analysis. It is not yet well-understood how these different types of collaboration influence the innovative performance of SMEs.</p> <p>In this study, we intend to address how data are managed through collaboration between the government and companies in smart cities and how the mode of collaboration influences firms’ performance on innovation. By focusing on the case of SMEs in China, this research aims to shed light on what kinds of data are available and used in smart cities and how the government and enterprises collaborate on data to facilitate innovation.</p> <p>The analysis of this study utilizes data on more than eight million contracts extracted from the official procurement database of the government. Data on companies are assembled with regard to the registered capital, industry, software products, and patents in 1990-2021 from the Tianyancha website. A panel data is established with key characteristics of SMEs, software and patents outputs, and their record on obtaining different government contracts annually. The government contracts are divided into three categories, namely, data analysis, platform building, and equipment supply, based on keyword identifications. To deal with the unbalance between the treatment group (the companies that obtained government contracts) and the control group, we use propensity score matching (one-to-one nearest neighbor matching) to narrow down the sample size of the control group to that of the treatment group. Then we apply the traditional difference-in-difference (DID) and DID with multiple time periods (Callaway & Sant’Anna, 2021) methods to examine whether there are significant differences in innovative outputs of software products and patents before and after the companies receive government contracts. We also compare how the innovation performance of companies differs based on the types of contracts these companies obtain. That makes it possible to identify what kinds of data collaboration would be effective in improving the innovative performance of SMEs.</p> <p>Our preliminary analysis of average treatment effect suggests that obtaining the government contracts, especially research contracts and platform building type of contracts, can effectively help improve the innovation performance when comparing between the control and treatment group. After checking the common support graph and doing a balance test, the outcome is solid. In general, based on the average treatment effect on the treated group, innovation performance, as measured by the number of patents and software productions, has shown a significant increase for those companies that obtain a research type of contract, whereas the increase is smaller for the platform building contractor and slight for the equipment purchase contractor. Government purchase of equipment that contains data-intensive technologies promotes the use of these products in smart cities. That, however, does not involve any substantive exchange or transfer of data possessed by the government and would not significantly contribute to stimulating innovation at firms.</p> <p>This study will have useful implications for establishing public-private collaboration on data for facilitating innovation in smart cities. Specifically, government procurement should also be viewed as a policy tool for improving China's technological innovation. According to our findings, research and platform development can successfully assist firms in improving their innovation performance. As a result, the government should grant enterprises access to additional data resources and data management related tasks if they want to see more industry structural transformation, as stated in the government documents.</p> <p> </p>
Strategies for and Barriers to Collaboratively Developing Anti-racist Policies and Resources as Described by Geoscientists of Color Participating in the Unlearning Racism in Geoscience (URGE) Program
<p>The Unlearning Racism in Geosciences (URGE) program guides groups of geoscientists as they draft, implement, and assess anti-racist policies and resources for their workplace. Some participating Geoscientists of Color (GoC) shared concerns about microaggression, tokenism, and power struggles within their groups. These reports led us to collect and analyze data that describe the experiences of GoC in URGE. The data are from five discussion groups and two surveys. Our analyses revealed that participating GoC want to continue working with White colleagues on anti-racist work. GoC want White colleagues not to shy away from doing anti-racist work. Instead, GoC want White colleagues (1) to create and adhere to robust behavioral codes of conduct, (2) to focus discussions on anti-racism, (3) to act on anti-racism initiatives, (4) not to prompt GoC to educate them or reveal trauma, and (5) to refrain from microaggressions and tokenism. These desired outcomes were achieved in some groups with varying degrees of success. Correcting a history of mistrust relating to racism and anti-racism action is key to implementing and assessing effective anti-racist policies and resources. This requires leadership support, following through on anti-racism action, and deepening relationships between GoC and White colleagues. Future anti-racist programs should spend a substantial amount of time on and demonstrate the importance of training participants how to discuss racism effectively and how to create and adhere to robust behavioral codes of conduct. Future programs should also explore developing a robust program-wide code of conduct that includes a policy for reporting offenses.</p>
Intercultural Competencies & Collaboration from 2016 to 2022 Database
<p>Database used for the systematic literature review: Intercultural Competencies & Collaboration from 2016 to 2022.</p>
Collaborative Assessment of Molecular Geometries and Energies from the Open Force Field
<p>OpenFF Industry Public Dataset optimized at the (1) B3LYP-D3BJ / DZVP; (2) OpenFF-2.0.0; (3) Gaff-2.11-AM1BCC; (3) OPLS4 + default parameters; (4) OPLS4 + custom parameters.</p> <p>For (1) the corresponding tar.gz archive contains (a) sdf files of the final, optimized geometries and (b) json files with molecular properties of the final step of the optimization.</p> <p>For (2-4) the corresponding tar.gz archive contains sdf files of the final, optimized geometries.</p> <p>Note: The optimization carried out with both OPLS4 including default and custom parameters (4) was performed using the ffld_server to include virtual sites.</p>
U.S. ELTP Toolkit of Collaborative Practice
<p>A <strong>Research Inclusion Toolkit</strong> that provides information on best practices for mutually beneficial research collaborations. The RI Toolkit will provide proposers with the necessary information to build effective research inclusion plans. It will also provide reviewers with recommendations for assessing and ranking research inclusion proposals. </p>
Dataset for the Indonesian Newly Validated Collaborative Practice Assessment Tool
<p>The dataset is used for the analysis of an article titled: A psychometric evaluation of the Indonesian version of the Collaborative Practice Assessment Tool (CPAT) for assessing interprofessional collaborative practice in health practitioners and students.</p>
Publication Database on Recent Trends and Perspectives of Collaborative Robotics in Work 4.0
<p>This publication database is part of a literature review project aimed at providing a comprehensive and up-to-date (31st of January 2022) overview of recent trends and perspectives of robotics in the working world 4.0. The related journal article can be found here: DOI (https://doi.org/10.3390/robotics12030084). The database contains bibliographic information of all the publications that were included in the literature review.</p> <p> </p> <p>This publication database (including data and complementary documents) is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) by INSTITUTE OF MECHANISM THEORY, MACHINE DYNAMICS AND ROBOTICS - RWTH AACHEN UNIVERSITY.</p>
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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.