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1,146 results for “collaboration;”
Individual versus computer-supported collaborative self-explanations: how do their writing analytics differ? Coh-Metrix results and students' excerpts.
<p>Coh-Metrix results and students' excerpts of the publication: Albó, L., Beardsley, M., Amarasinghe, I. & Hernández-Leo, D. (2020). Individual versus computer-supported collaborative self-explanations: how do their writing analytics differ? In International conference on Advanced Learning Technologies and Technology-enhanced Learning (ICALT). </p>
Interaction Framework within Collaborative Virtual Environments for Multiple Users each interacting with Multiple Degrees-Of-Freedom Controllers
<p>Collaboration is a process in which two or more agents work together to achieve shared goals. However, many existing platforms cannot generate a collaborative environment to engage multiple users with multiple controllers in a seamless manner. To address this need, this video and work in progress will describe LISU (Library for Interactive Settings and User-modes) an input management computing framework that enables collaboration across multiple input controllers as its default. Within the system team members cohabit any real-time simulation environments simultaneously and are then able to jointly control visualisation software across multiple controllers while being continually monitored and evaluated at a low level, allowing research questions to be answered.</p>
InHARD - Industrial Human Action Recognition Dataset in the Context of Industrial Collaborative Robotics
<p><strong>Objectives</strong></p> <p>We introduce a RGB+S dataset named “Industrial Human Action Recognition Dataset” (InHARD) from a real-world setting for industrial human action recognition with over 2 million frames, collected from 16 distinct subjects. This dataset contains 13 different industrial action classes and over 4800 action samples. The introduction of this dataset should allow us the study and development of various learning techniques for the task of human actions analysis inside industrial environments involving human robot collaborations.<br> Read <strong>00-README.txt</strong> for detailed download instructions.</p> <p>More details on the dataset at <a href="https://github.com/vhavard/InHARD">https://github.com/vhavard/InHARD</a></p> <p>This work has been performed at the CESI LINEACT : <a href="https://recherche.cesi.fr/inhard-industrial-human-action-recognition-dataset/">https://recherche.cesi.fr/inhard-industrial-human-action-recognition-dataset/</a></p>
Making plasma science more open, collaborative, and reproducible
<p>The reproducibility crisis of modern science is the inability of scientists to reproduce roughly half of the results published in scientific journals. This crisis has affected a broad range of fields, such as psychology, chemistry, and oncology. While physicists tend to have high confidence that physics research is reproducible, no comprehensive studies have been performed to support or refute this claim. Nevertheless, the scientific, cultural, and institutional practices that contribute to the reproducibility crisis in other fields are also present in plasma science. This tutorial will describe how to implement best practices for scientific reproducibility into plasma research. The talk will begin by outlining sources of irreproducibility, such as cognitive biases, improper use of statistics, publication bias, closed access policies for data and software, and the reward system for modern academia. The talk will then describe remedies for these problems such as open access data policies; open metadata standards; open source software; training on proper use of statistics; pre-registration of research methodologies; independent methodological and statistical support; and valuing the reproducibility of research in tenure, hiring, and funding decisions.</p>
With a little help from my friends: individual and collaborative performance during trail clearing in leaf-cutting ants
<p>Social organisms express collaborative behaviours, allowing them to solve problems that exceed their individual capabilities. Group coordination and environmental context are some of the factors that may determine the performance of individual and collaborative strategies. Using the trail-clearing behaviour of leaf-cutting ants, we evaluated experimentally for both strategies whether the success probability and clearing time depend on problem characteristics and context. We placed obstacles of different sizes and shapes (problem characteristics), in trails with different foragers' fluxes and soil roughness (context) in 10 field nests of <i>Atta cephalotes, </i>and<i> </i>compared removal success (i.e. if ants could remove obstacles) and time of individual and collaborative strategies. Very large obstacles could only be removed collaboratively, confirming individual limitations for transporting large objects. For all obstacle shapes, collaborative removals were more successful but took longer, suggesting that coordination among individuals delays these actions. Individual strategies were faster, regardless of ant flux. However, as ant flux increased, removal success was higher for collaborative than for individual removals. Lastly, trail roughness had no effect. This work highlights one advantage of sociality, the option of collaboratively solving problems that exceed the individual abilities. In addition, it reveals the associated costs of joint actions, since they can be time-consuming presumably due to coordination problems.Social organisms express collaborative behaviours, allowing them to solve problems that exceed their individual capabilities. Group coordination and environmental context are some of the factors that may determine the performance of individual and collaborative strategies. Using the trail-clearing behaviour of leaf-cutting ants, we evaluated experimentally for both strategies whether the success probability and clearing time depend on problem characteristics and context. We placed obstacles of different sizes and shapes (problem characteristics), in trails with different foragers' fluxes and soil roughness (context) in 10 field nests of <i>Atta cephalotes, </i>and<i> </i>compared removal success (i.e. if ants could remove obstacles) and time of individual and collaborative strategies. Very large obstacles could only be removed collaboratively, confirming individual limitations for transporting large objects. For all obstacle shapes, collaborative removals were more successful but took longer, suggesting that coordination among individuals delays these actions. Individual strategies were faster, regardless of ant flux. However, as ant flux increased, removal success was higher for collaborative than for individual removals. Lastly, trail roughness had no effect. This work highlights one advantage of sociality, the option of collaboratively solving problems that exceed the individual abilities. In addition, it reveals the associated costs of joint actions, since they can be time-consuming presumably due to coordination problems.</p>
Data from: The changing nature of collaboration in tropical ecology and conservation
Collaboration can improve conservation initiatives through increases in article impact and by the building scientific understating required for conservation practice. We investigated temporal trends in collaboration in the tropical ecology and conservation literature by examining patterns of authorship for 2,271 articles published from 2000 to 2016 in Biotropica and the Journal of Tropical Ecology. Consistent with trends in other studies and scientific disciplines, we found that the mean number of authors per article increased from 2.6 in 2000 to 4.2 in 2015. We modeled changes in multi-national collaboration in articles using a generalized linear model, finding that the mean number of author-affiliated countries increased from 1.3 (± 0.6 SD) to 1.7 (± 0.8 SD) over time, and that increases were best explained by the number of authors per article. The proportion of authors based in tropical countries increased, but the probability of tropical-extratropical collaboration did not, and was best explained solely by the number of authors per article. Overall, our analyses suggest that only certain types of collaboration are increasing, and that these increases coincide with a general increase in the number of authors per article. Such changes in author numbers and collaboration could be the result of increased data-sharing, changes in the scope of research questions, changing authorship criteria, or scientific migration. We encourage tropical conservation scientists continue to build collaborative ties, particularly with researchers based in underrepresented tropical countries, to ensure that tropical ecology and conservation remains inclusive and effective.
Data from: An origin of citations: Darwin's collaborators and their contributions to the Origin of Species
<p>Since the first edition of the Origin of Species (1859), Charles Darwin apologizes for not correctly referencing all the works cited in his magnum opus. More than 150 years later we catalogued these citations and analysed the resultant data. Looking for a complete selection of collaborators, a flexibilization of the term "citation" was necessary, and we define it as any reference made to a third party, independently of its form or function. Following the same idea, the last edition of the Origin, originally published in 1872 and reprinted with minor additions and corrections in 1876, was chosen for the research because it represents the end of a long debate between Darwin and his peers, naturally being the edition with the most number of citations and collaborators. Through a diverse theoric approach we hope to present a new perspective for the study of the Origin of Species: a bibliographic approach gives us the tools needed to understand the history of the book as a physical and cultural object; bibliometrics provides a theory of citations as well as a quantitative analysis; lastly, the Science Studies highlight the profound social aspects of science in the making. The analysis resulted in 639 citations to 298 collaborators, although these results are only the tip of the iceberg of all the gathered data's potential.</p>
Trasncripts and Survey from Case Study of Small Collaboration
<p>To identify the particularities of the small collaboration we used an exploratory case study methodology. The case study followed an embedded case study design and we collected data via semi-structured interviews and the SDR’s logs. In the study, we explored three topics: the scientific collaboration process, the collaboration’s data-sharing practices and attitudes.</p> <p>We found that, on the topic of collaboration, the collaborations suffered the common problems of geographically distributed collaborations. In terms of data- sharing practices and attitudes, we found that collaborators were solely motivated by extrinsic incentives. They showed a very restricted awareness of potential benefits, and sharing only occurred under low risk scenarios.</p> <p>We begin this section with the description of the exploratory study. We then present the results and a discussion of this exploration and propose three empirical claims.</p> <p> </p>
Supplementary Material for: Starting Collaborations Between SMEs and Researchers in Software Engineering
<p>Supplementary Material for: Starting Collaborations Between SMEs and Researchers in Software Engineering</p>
Extra Material for the paper: Experiences from conducting rapid reviews in collaboration with practitioners --- Two industrial cases
Open the record for dataset details and reuse information.
Rapid Review on Gender and Collaboration
<p>Dataset on search and filtering process of a rapid review on A Rapid Review of Gender Parity and Collaboration in Technology: Insights from the Past Decade (DOI: 10.48340/ecscw2024_ep10), presented at ECSCW 2024.<br><br></p>
Artifacts for paper "PATCH: Empowering Large Language Model with Programmer-Intent Guidance and Collaborative-Behavior Simulation for Automatic Bug Fixing" submitted to TOSEM
<p>The project includes the data and code used in the submitted TOSEM paper titled "PATCH: Empowering Large Language Model with Programmer-Intent Guidance and Collaborative-Behavior Simulation for Automatic Bug Fixing"</p>
Data Collaborative and Clusters_Bartolomucci_Bresolin
<p> The dataset describes 171 Data Collaboratives according to organisational, technological, geographical, and impact dimensions. The dataset is derived from the one present on datacollaboratives.org and complemented with additional data obtained by secondary data sources. </p> <p>A related work using a previous version of this dataset can be found online with the following title. Fostering data collaboratives’ systematisation through models’ definition and research priorities setting." <em>DG. O 2022: The 23rd Annual International Conference on Digital Government Research</em>. 2022</p> <p> </p>
Framework and results of "Performance evaluation in the Inter-institutional collaboration context of hybrid smart cities"
<pre>Comparative study of the Lugano and Turin framework and policy and agenda elements.</pre>
Collaboration for conservation: assessing country-wide carnivore occupancy dynamics from sparse data
<p><strong>Aim:</strong> Assessing the distribution and persistence of species across their range is a crucial component of wildlife conservation. It demands data at adequate spatial scales and over extended periods of time, which may only be obtained through collaborative efforts, and the development of methods that integrate heterogeneous datasets. We aimed to combine existing data on large carnivores to evaluate population dynamics and improve knowledge on their distribution nationwide.</p> <p><strong>Location:</strong> Botswana</p> <p><strong>Methods:</strong> Between 2010 – 2016, we collated data on African wild dog, cheetah, leopard, brown and spotted hyaena, and lion gathered with different survey methods by independent researchers across Botswana. We used a multi-species, multi-method dynamic occupancy model to analyse factors influencing occupancy, persistence, and colonisation, while accounting for imperfect detection. Lastly, we used the gained knowledge to predict the probability of occurrence of each species countrywide.</p> <p><strong>Results:</strong> Wildlife areas and communal rangelands had similar occupancy probabilities for most species. Large carnivore occupancy was low in commercial farming areas and where livestock density was high, except for brown hyaena. Lion occupancy was negatively associated with human density; lion and spotted hyena occupancy was high where rainfall was high, while the opposite applied to brown hyaena. Lion and leopard occupancy remained constant countrywide over the study period. African wild dog and cheetah occupancy declined over time in the south and north, respectively, whereas both hyaena species expanded their ranges. Countrywide predictions identified the highest occupancy for leopards and lowest for the two hyaena species.</p> <p><strong>Main Conclusions:</strong> We highlight the necessity of data sharing and propose a generalisable analytical method that addresses the challenges of heterogeneous data common in ecology. Our approach, which enables a comprehensive multi-species assessment at large spatial and temporal scales, supports the development of data-driven conservation guidelines and the implementation of evidence-based management strategies nationally and internationally.</p>
Analytics of collaborations and performance of citizen science teams during the GEAR cycle 2 of the Crowd4SDG project.
<p>This data frame is part of the deliverable 4.2 of the Crowd4SDG project.</p> <p>It contains the measured analytics of citizen collaborations using new metrics/descriptors developed during the first year of the Crowd4SDG project. </p> <pre>The goal of the Crowd4SDG project is to research the extent to which Citizen Science (CS) can provide an essential source of non-traditional data for tracking progress towards the SDGs, as well as the ability of CS to generate social innovations that enable such progress. In the Crowd4SDG project, the Work Package 4 aims to develop and monitor new metrics and develop statistical models of team engagement and collaboration that contribute to the many-faceted outcomes of the citizen science projects developed within the Crowd4SDG consortium over the 3-years course of the project. Here, we share a dataframe of features collected during the GEAR cycle 2 pertaining to team composition, activity, performance and interaction dynamics. In particular, we leveraged the CoSo platform for collecting self-reported data on collaborations and task allocation structure of participating teams, as well as Slack data for measuring communication networks. The related findings are presented in the deliverable 4.4 of the Crowd4SDG project and serve as a basis for i) exhibiting the potential of using digital traces to derive measures related to team process, ii) highlighting perspectives for monitoring metrics in the next GEAR cycle.</pre>
Are Intercultural Competencies the Key for International Collaboration?: A Systematic Review
<p>Database used for the SLR: Are Intercultural Competencies the Key for International Collaboration?</p>
Collaboration modeling
<p>This repository includes data in chapter 2- Select infrastructures with collaboration relationship modeling</p>
Wolpert et al. 2022_Collaborative agroforestry_primary data
<p>The data set shows the primary data of the survey related to the publication of Wolpert et al (2022) Collaborative agroforestry to mitigate wildfires in Extremadura, Spain: land manager motivations and perceptions of outcomes, benefits, and policy needs.</p>
A flexible operation-based infrastructure for collaborative model-driven engineering (Evaluation Data)
<p>Repository containing the UML models used in the evaluation of the paper entitled: "A flexible operation-based infrastructure for collaborative model-driven engineering" submitted to ECMFA 2023.</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.