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FIG. 7 in Overview of Mitaraka survey: research frame, study site and field protocols
FIG. 7. — Active collecting techniques: A, collecting butterflies with a net; B, sweeping vegetation (NS or SW) with a rugged sweep net; C, beating tray (BS), the vegetation is hit with a stick, which causes the arthropods to fall on the white nape mounted on a frame; D, searching for aquatic larvae with a rugged aquatic net; E, looking for butterfly caterpillars (Riodinidae and Lycaenidae) on liana flowers; F, visual search for reptiles, here with a Lachesis muta (Linnaeus, 1766) snake. Photos: A, B, C, E, Stéphane Brûlé; D, Nicolas Moulin; F, Xavier Desmier.
FIG. 3 in Overview of Mitaraka survey: research frame, study site and field protocols
FIG. 3. — Illustration of the landscape and main habitat types found in the Mitaraka study area: A, general landscape of the study area, with the drop zone visible in the foreground; B, inselberg "Sommet-en-Cloche" with bare rocks and transition forest; C, mosaic of forests and cambrouses; D, forest interior; E, swamp forest (bas-fond) with Euterpe oleracea Mart palm. Photos: Xavier Desmier, except B, Stéphane Brûlé.
FIG. 5 in Overview of Mitaraka survey: research frame, study site and field protocols
FIG. 5. — Passive interception traps: A, windowpane flight intercept trap (FIT) suspended over a fallen tree crown; B, 6 meter Malaise trap (MT) set up over a fallen tree near the Alama river; C, SLAM traps on an inselberg forest edge; D, a buprestid beetle (Buprestidae) trapped in artificial spider web (ASW). Photos: A, B, D, Julien Touroult; C, Stéphane Brûlé.
FIG. 4 in Overview of Mitaraka survey: research frame, study site and field protocols
FIG. 4. — Some of the collecting sites and techniques: A, drop zone forest clearing, with a high amount a freshly cut trees, and scattered SLAM traps; B, clearing, equiped with SLAM traps, automatic light trap and artificial spider web (ASW); C, active net collecting of butterflies on the "Sommet-en-Cloche" inselberg. Photos: A, B, Julien Touroult, C, Stéphane Brûlé.
FIG. 2 in Overview of Mitaraka survey: research frame, study site and field protocols
FIG. 2. — Mitaraka study area map with the four trails indicated (map by Maël Dewynter, map base by IGN and Parc amazonien de Guyane).
FIG. 6 in Overview of Mitaraka survey: research frame, study site and field protocols
FIG. 6. — Attractive traps: A, pink LED based automatic light trap (PVP) suspended at 15 m height close to a small canopy gap; B, light trap (LT) with light bulb of 125W and with white sheet, covered with moths at the end of a rainy night; C, colored pan traps (blue [BPT], white [WPT], and yellow [YPT]) at soil surface level to collect Diptera; D, fruit baited Coleoptera traps with banana nectar (BT), suspended in forest canopy; E, Nymphalidae butterfly trap (CHX), suspended in the forest canopy; F, tree equiped with ropes and baits composed of honey and tuna at different heights to attract ants; G, pitfall trap baited with dung (PFC) to collect coprophagous Scarabaeidae; H, Big Shot, a type of slingshot used to shoot ropes and suspend traps high up in the trees. Photos: A, B, G, H, Julien Touroult; C, Marc Pollet; F, Maurice Leponce; D, E, Stéphane Brûlé.
FIG. 11 in Overview of Mitaraka survey: research frame, study site and field protocols
FIG. 11. — Process flow for Diptera: A, each Diptera coordinator and taxonomic expert signs an agreement prior to receiving samples; B, sampling specimens with an array of methods (Malaise trap, pan traps, sweep net, SLAM trap); C, transporting of partly processed and unprocessed samples to the Belgian lab; D, sorting Diptera from complete samples and splitting the Diptera fraction into workable fractions (mostly on family level) for Diptera coordinators – taxonomic experts; E, processed Diptera fractions (Dolichopodidae, Empidoidea, Mycetophilidae, Phoridae); F, dissemination of workable fractions to Diptera coordinators – taxonomic specialists (10 in Europe, 5 in Canada, 8 in the USA, 10 in Brazil); G, examination and identification of specimens of workable fractions by the taxonomic expert (or further splitting of fractions by Diptera coordinator); H, commitments as part of the signed agreement (see Fig. 11A), with submission of identification file as first.
UK Research Software Survey 2014
<p>This spreadsheet contains the anonymised data collected as part of a survey of UK researchers in their use of research software.</p> <p>We asked people specifically about “research software” which we defined as:</p> <blockquote> <p>“Software that is used to generate, process or analyse results that you intend to appear in a publication (either in a journal, conference paper, monograph, book or thesis). Research software can be anything from a few lines of code written by yourself, to a professionally developed software package. Software that does not generate, process or analyse results - such as word processing software, or the use of a web search - does not count as ‘research software’ for the purposes of this survey.”</p> </blockquote> <p>We contacted 1,000 randomly selected researchers at each of 15 Russell Group universities. From the 15,000 invitations to complete the survey, we received 417 responses – a rate of 3% which is fairly normal for a blind survey. We used Google Forms to collect responses.</p> <p>The responses have good representation from across the disciplines, seniorities and genders. This is a statistically significant number of responses that can be used to represent the views of people in research-intensive universities in the UK.</p> <p>An overview of the data is available on the worksheet "Summary data". Responses to questions are ordered by unique respondent ID. Please read the "README" worksheet for additional information about the collection and processing of this data.</p> <p>This survey data is licensed under a Creative Commons by Attribution licence. Copyright resides with The University of Edinburgh on behalf of the Software Sustainability Institute.</p> <p>Please cite as:</p> <p><strong>APA</strong></p> <p>Hettrick. S. J., et al. (2014). UK Research Software Survey 2014 [Data set]. doi:10.5281/zenodo.14809</p> <p><strong>Chicago</strong></p> <p>S.J. Hettrick et al, UK Research Software Survey 2014 (accessed December 4, 2014), 10.5281/zenodo.14809.</p> <p><strong>MLA</strong></p> <p>Hettrick S.J., et al. “UK Research Software Survey 2014” ZENODO, 2014. Web. 4 December 2014. .</p>
H2M survey data on commercialisation training needs of Health Researchers
<p>Health-2-Market was a 3-year long Coordination and Support Action, funded by the European Union’s Seventh Framework Programme for research, technological development and demonstration (Grant Agreement No 305532). H2M aimed at providing training and individual support to Health / Life Sciences researchers in the process of translating their research results into successful new business ideas.</p> <p>With a view to properly adapting the training offer of the project to the needs of Health / Life Sciences researchers in terms of entrepreneurship and business skill development a Training Needs Analysis (TNA) was conducted. In this context, H2M launched an online survey targeted at Health / Life Sciences researchers who have been involved in EU health projects. In particular, the objectives of the survey were:</p> <ul> <li>To formulate a descriptive understanding of various aspects of commercialisation and training needs of the main target group of the project;</li> <li>To divide this target group into homogeneous sub-groups (clusters) along a number of key characteristics such as demographics, commercialisation attitudes and needs;</li> <li>To understand preferences and importance of different aspects and needs through the analysis of: <ul> <li>Knowledge areas that can influence commercialisation behaviour;</li> <li>Training modalities that have an effect on the intention to participate and /or on the perception of the usefulness of a commercialisation training;</li> <li>Variations identified over different sub-groups.</li> </ul> </li> </ul> <p>The survey was dispatched to a database composed of 7,991 unique contacts of participants in previous health projects, accessed through the Directorate General for Health and Food Safety of the European Commission. The initial aim of at least 50 complete responses was overwhelmingly surpassed: 637 respondents completed the survey in full.</p> <p>The “H2M survey data on commercialisation training needs of Health Researchers” dataset contains the raw, anonymised data that were collected from these respondents, along with the questionnaire items that were utilised.</p>
Research Software Engineers Supporting Science: Survey Responses
<p>Raw survey data for "Not everyone can use git: Research Software Engineers’ recommendations for scientist-centred software support (and what researchers think of them)", a talk given by Caroline Jay at RSE16, Manchester, UK.</p>
A Questionnaire to Assess the Research Practices and Services Related to the Academic and Research Staff at the Institutions of Higher Education in Palestine - Survey Data
<p>Data generated as part of a needs assessment survey conducted as part of ROMOR, a project funded by the Erasmus Plus Programme of the European Union in the period from October 2016 to October 2019. A questionnaire was prepared under the supervision of Palestinian Universities participating in the project. The results of the study will be used to create and develop institutional repositories to store the digital outputs of scientific research at the institutions of higher education in Palestine. The results will be also used to provide the vocational and academic training, and the institutional policies required to manage, organize the use, and populate the prospective repositories. This objective will contribute in promoting the access to and benefit of the results of scientific research in Palestine, and increase its impact at the local and international levels. This questionnaire was distributed to the representative of each institution, who in turn forwarded it to the suitable persons in the institution. Data was collected between January 4th and February 19th 2017. Paper and electronic versions of a questionnaire were prepared in both Arabic and English. The project coordinators at partner PS HEIs were requested to circulate the electronic questionnaire to all researchers and members of academic staff. Data was collected by ROMOR partners at:</p> ● The Islamic University of Gaza (IUG) ● Al-Quds Open University (QOU) ● Birzeit University (BZU) ● Palestine Technical University-Kadoori (KAD)
A Questionnaire to Assess the Research Practices and Services Related to the Academic and Research Staff at the Institutions of Higher Education in Palestine - Survey Data with Pie Charts
<p>Data generated as part of a needs assessment survey conducted as part of ROMOR, a project funded by the Erasmus Plus Programme of the European Union in the period from October 2016 to October 2019. A questionnaire was prepared under the supervision of Palestinian Universities participating in the project. The results of the study will be used to create and develop institutional repositories to store the digital outputs of scientific research at the institutions of higher education in Palestine. The results will be also used to provide the vocational and academic training, and the institutional policies required to manage, organize the use, and populate the prospective repositories. This objective will contribute in promoting the access to and benefit of the results of scientific research in Palestine, and increase its impact at the local and international levels. This questionnaire was distributed to the representative of each institution, who in turn forwarded it to the suitable persons in the institution. Data was collected between January 4th and February 19th 2017. Paper and electronic versions of a questionnaire were prepared in both Arabic and English. The project coordinators at partner PS HEIs were requested to circulate the electronic questionnaire to all researchers and members of academic staff. Data was collected by ROMOR partners at:</p> <p>● The Islamic University of Gaza (IUG)</p> <p>● Al-Quds Open University (QOU)</p> <p>● Birzeit University (BZU)</p> <p>● Palestine Technical University-Kadoori (KAD)</p> <p>[Data visualised as pie charts]</p> <p> </p>
Research Survey on 'Effects of the Coronavirus Pandemic on Scientific Research'
<p><strong>1. The aim of the research</strong></p><p>The survey aimed to collect opinions on how the pandemic has changed scientific research, especially in regards to the usage of different forms of digital tools. The onset of COVID-19 has had an immediate impact on how scientists were able to use their time and resources to do their work. However, there was a lack of real-time data on how they are responding to this event and how it has had differential impacts across scientific fields.</p><p><strong>2. Research instrument and subject</strong></p><p>A survey questionnaire prepared in English was developed for collecting empirical data from academics in Poland and abroad. We used the same version of the survey questionnaire both in Poland and in other countries in the world. The survey questionnaire consisted of several parts. Its first part included questions on demographic information. The second part of the survey questionnaire contained questions about how respondents' work hours were allocated for different activities during, and after the coronavirus pandemic outbreak and the predicted changes in future publication and funding related to spending on researching, writing during and after the coronavirus pandemic. The last part of the survey questionnaire included questions about scientific works, their quality, and support by ICTs during the coronavirus pandemic, as well as the implications of the pandemic for these issues in the future. At the end of the survey questionnaire, we asked respondents about their opinions with regard to the forecast situation in research and education after the coronavirus pandemic. Selecting a sample is a fundamental element of a quantitative study. Stratified sampling was used to obtain the sample, which can be taken to be true for the whole population. The strata were identified based on country, age, gender, position type, and research discipline. To gather a substantial number of respondents, snowball sampling was pursued, which involved daily and routine distribution (social media and e-mail posting) of an introductory e-letter and survey-link requesting participation in the research. To increase response rates, the following methods were used: involving academics (encouraging colleagues), pushing the survey (providing respondents with the survey URL in e-mails sent directly to them), publishing the project with a link for the basic questionnaire on the ResearchGate website and Facebook fan pages and providing frequent reminders.1</p><p><strong>3. Data collection</strong></p><p>Based on several analyses showing that surveys conducted over the internet provide results that are as valid as more "traditional" methods and due to social distancing caused by the coronavirus pandemic, we used the Computer Assisted Web Interview (CAWI) method for recruiting respondents and collecting data. The LimeSurvey tool was employed for recruiting reliable samples. The data were collected during a two-month period of work, between June 11, 2020, and August 18, 2020. This led to 982 responses. After screening the responses and excluding outliers, 476 usable, correct, and complete responses were collected. This uploded dataset is a subset of a larger dataset that the authors collected for their research project titled "The Effects of the Coronavirus Pandemic on Scientific Research and University Teaching". It includes the questionnaire responses related to research during and after the COVID-19 pandemic. The questions were designed to gather information about the impact of the pandemic on academic scientists' research.1</p><p><strong>4. Results</strong></p><p>Our results may suggest targeted policies to alleviate the disruptions experienced by specific scientific fields. The findings of the past research were documented in three articles, which can be found below: </p><p>1. Ziemba, E. W., & Eisenbardt, M. (2022). The effect of the Covid-19 pandemic on ICT usage by academics. Journal of Computer Information Systems, 62(6), 1154-1168. DOI: 10.1080/08874417.2021.1992806 </p><p>2. Wartini-Twardowska, J., Grabara, D., & Ziemba, E. W. (2021). The Influence of the COVID-19 Pandemic on the Use of Digital Technologies by Scientists: A Comparison Between Poland and Abroad. Problemy Zarządzania, 19(3/2021 (93), 12-31. DOI:10.7172/1644-9584.93.1 </p><p>3. Maruszewska, E. W., Eisenbardt, M., & Tuszkiewicz, M. (2022). COVID Pandemic as a disruptive factor enhancing ICT USE in social sciences' teaching practices. Scientific Papers of Silesian University of Technology. Organization & Management/Zeszyty Naukowe Politechniki Slaskiej. Seria Organizacji i Zarzadzanie, (160). DOI: 10.29119/1641-3466.2022.160.25 </p>
Survey on Developer and Researcher Views on the Ethics of Experiments on Open-Source Projects
<p>Results of a survey of 180 GitHub developers and 44 authors of research papers concerning the ethics of performing experiments on open source projects.</p>
FIG. 1 in The "Our Planet Reviewed" Mitaraka 2015 expedition: a full account of its research outputs after six years and recommendations for future surveys
FIG. 1. — Number of species published by semester from the end of the expedition, with first semester: July-December 2015, and last semester: January-July 2021. The expedition was accomplished in August 2015.
FIG. 4 in The "Our Planet Reviewed" Mitaraka 2015 expedition: a full account of its research outputs after six years and recommendations for future surveys
FIG. 4. —Density map of the shared data from the GBIF portal (https://www.gbif.org) for insects at the scale of the Guiana Shield. Only data with a high occurrence resolution (<1 km) are included.
FIG. 2 in The "Our Planet Reviewed" Mitaraka 2015 expedition: a full account of its research outputs after six years and recommendations for future surveys
FIG. 2. — Number of new (non-marine) animal species of French Guiana's fauna described since 2000. New species collected during the Mitaraka survey are indicated in colour.
FIG. 5 in The "Our Planet Reviewed" Mitaraka 2015 expedition: a full account of its research outputs after six years and recommendations for future surveys
FIG. 5. — Number of holotypes collected according to the different techniques used. Abbreviations: BS, beating sheet; HC, hand collecting; PVB, cross flight intercept trap with a blue LED; PVP, idem, with pink LED; PGL, idem, with GemLight; BPT, blue pan trap; SLAM, sea and land air malaise trap; SW & NS, sweeping & net sweeping; WPT, white pan trap; YPT, yellow pan trap (for a more detailed description of the techniques, see Touroult et al. 2018).
FIG. 6 in The "Our Planet Reviewed" Mitaraka 2015 expedition: a full account of its research outputs after six years and recommendations for future surveys
FIG. 6. — Level of compliance with recommendations for citation of expedition, ABS authorization and deposit of specimens according to two discriminating variables (n = 90 articles).
CaRCC Research Computing and Data (RCD) Workforce Survey Data 2021 - Part 1
<p>Datasets and analysis to accompany "Characterizing the US Research Computing and Data (RCD) Workforce"</p> <p>Paper: Christina Maimone, Scott Yockel, Timothy Middelkoop, Ashley Stauffer, and Chris Reidy. 2022. Characterizing the US Research<br> Computing and Data (RCD) Workforce. In Practice and Experience in Advanced Research Computing (PEARC ’22), July 10–14, 2022,<br> Boston, MA, USA. ACM, New York, NY, USA, 12 pages. https://doi.org/10.1145/3491418.3530289</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.