Find research datasets worth reusing

openCustomDec 2014View details →

Long-term N-fertilized vegetation plots on Hog Island, Virginia Coastal Barrier Islands, 1992-2014

This dataset contains results from a long-term fertilization study on the dunes of Hog Island, Virginia.

openCustomDec 2009View details →

Beach Morphology of the Virginia Barrier Islands 1998, 2005 and 2009

Beach features (dune crest, dune toe and shoreline) extracted from LiDAR datasets and used in Dana Oster's 2012 M.S. Thesis at the University of Virginia. Also included are overwash probablities associated with a hypothetical storm similar to Hurricane Bonnie.Â

openCustomFeb 2022View details →

Shorelines and island boundaries for the Atlantic barrier islands of Virginia, 1851-2017

This dataset provides a shorelines (VBI-allshores.zip) and set of area polygons (VBI-allislands.zip) delineated from historical NOS t-sheet (1851-1962) and USGS satellite imagery (1994-2017) spanning the barrier islands of the Eastern Shore of Virginia in multiple GIS data layers. The VBI-allshores dataset provides a comprehensive set of historical NOS t-sheet (1851-1979) and satellite imagery (1980-2017) shorelines spanning the islands south of Assateague along the Virginia Eastern Shore in a single GIS data layer. This shoreline dataset compliments and overlaps other VCRLTER shoreline datasets for the Virginia barrier islands that contain historical shorelines derived from a combination of sources, including photointerpretation of aerial photos, satellite imagery, and LiDAR assessments (from USGS, NOAA, VITA-VGIN-VBMP, and others). The VBI-islands dataset provides a set of area polygons delineated from historical NOS t-sheet (1851-1962) and USGS satellite imagery (1994-2017) spanning the barrier islands of the Eastern Shore of Virginia in multiple GIS data layers.

openCustomApr 2023View details →

Simulation data of barrier system cross-landscape interactions from BarrierBMFT

BarrierBMFT (version 1.0) simulation results for change in ecosystem extent (i.e., profile width) across a range of input conditions. Simulations vary by the relative sea-level rise rate (3-15 mm/yr), external suspended sediment concentration (40-80 mg/L), mainland slope (0.001-0.01), characteristic dune growth rate (0.45-0.75 1/yr), flow infiltration and drag parameter (1-2 dam^3/yr), and the coefficient for sediment transport entering back-barrier bay (0.5-0.85). Each row in the spreadsheet represents a unique model simulation; to account for storm stochasticity in the model, each unique combination of parameter values was simulated 25 or 50 times. Simulations run for 400 model years.

openCustomOct 2020View details →

Groundwater well data on Hog Island, Virginia Coastal Barrier Islands, 1990-2007

Groundwater well data on Hog Island, 1990-2007. For updated wirelessly-networked well data after July 2007 (the same wells and locations, but different technology and sampling interval), please see follow-up dataset VCR09169. DEPTH variables are the depth of the water below the ground surface. They are negative when water levels are below the surface and positive when the surface is flooded.� ELEV variables are the elevation of the water surface above mean sea level.

opencc-by-4.0May 2020View details →

Taxonomy of barriers that hinders Local Flexibility Market proliferation

This dataset contains the results of the state of the art survey to retrieve the barriers that that hinders Local Flexibility Market proliferation. Scientific literature, interviews with different stakeholders, technical reports from the main energy agencies and the European and national legislation have been consulted to build the taxonomy. Three files are provided: <ul> <li>a spreadsheet with the list of barriers and the document were it is found and</li> <li>a diagram with the end taxonomy of barriers</li> <li>a document with an explanation of the barriers included in each category of the taxonomy</li> </ul>

opencc-by-4.0May 2020View details →

Prioritization of barriers that hinders Local Flexibility Market proliferation

This dataset contains the prioritization provided by a panel of 15 experts to a set of 28 barriers categories for 8 different roles of the future energy system. A Delphi method was followed and the scores provided in the three rounds carried out are included. The dataset also contains the scripts used to assess the results and the output of this assessment.  A list of the information contained in this file is: <ul> <li> data folder: this folders includes the scores given by the 15 experts in the 3 rounds. Every round is in an individual folder. There is a file per expert that has the scores between -5 (not relevant at all) to 5 (completely relevant) per barrier (rows) and actor (columns). There is also a file with the description of the experts in terms of their position in the company, the type of company and the country. </li> <li> fig folder: this folder includes the figures created to assess the information provided by the experts. For each round, the following figures are created (in each respective folder): <ul> <li> Boxplot with the distribution of scores per barriers and roles.  </li> <li> Heatmap with the mean scores per barriers and roles. </li> <li> Boxplots with the comparison of the different distributions provided by the experts of each group (depending on the keywords) per barrier and role. </li> <li> Heatmap with the mean score per barrier weighted depeding on the importance of the role in each use case and the final prioritization. </li> </ul> </li> </ul> Finally, bar plots with the mean scores differences between rounds and boxplot with comparisons of the scores distributions  are also provided. <ul> <li> stat folder: this folder includes the files with the results of the different statistical assessment carried out. For each round, the following figures are created (in each respective folder): <ul> <li> The statistics used to assess the scores (Intraclass correlation coefficient, Inter-rater agreement, Inter-rater agreement p-value, Homogeneity of Variances, Average interquartile range, Standard Deviation of interquartile ranges, Friedman test p-value    Average power post hoc) per barrier and per role. </li> <li> The results of the post hoc of the Friedman Test per berries and per roles. </li> <li> The average score per barrier and per role. </li> <li> The mean value of the scores provided by the experts grouped by the keywords per barrier and role. P-value of the comparison of these two values. </li> <li> The end prioritization of the barrier for the use case (averaging the scores or fuzzy merging of the critical sets) </li> </ul> </li> </ul> Finally, the differences between the mean and standard deviations of the scores between two consecutive rounds are provided.

dryad40/100

Data from: Breaking Barriers? Ethnicity and socioeconomic background impact on early career progression in the fields of ecology and evolution

The academic disciplines of Science, Technology, Engineering and Mathematics (STEM) have long suffered from a lack of diversity. While in recent years there has been some progress in addressing the underrepresentation of women in STEM subjects, other characteristics that have the potential to impact on equality of opportunity have received less attention. In this study, we surveyed 188 early career scientists (ECRs), defined as within ten years of completing their PhD, in the fields of ecology, evolutionary biology, behaviour, and related disciplines. We examined associations between ethnicity, age, sexual orientation, sex, socioeconomic background, and disability, with measures of career progression, namely publication record, number of applications made before obtaining a postdoc, type of contract, and number of grant applications made. We also queried respondents on perceived barriers to progression, and potential ways of overcoming them. Our key finding was that socioeconomic background and ethnicity were associated with measures of career progression. While there was no difference in the number of reported first-authored papers on PhD completion, ethnic minority respondents reported fewer other-authored papers. In addition, ECRs from a lower socioeconomic background were more likely to report being in teaching and research positions, rather than research only positions, the latter being perceived as more prestigious by some institutions. We discuss our findings in the context of possible inequality of opportunity. We hope that this study will stimulate wider discussion, and help to inform strategies to address the underrepresentation of minority groups in the fields of ecology and evolution, and STEM subjects more widely.

opencc-zeroMay 2021View details →

opencc-by-4.0Dec 2019View details →

Dataset to "Applied Research of the Hygrothermal Behaviour of an Internally Insulated Historic Wall without Vapour Barrier: In Situ Measurements and Dynamic Simulations"

This record contains raw data of a 3-month monitoring period of the HeLLo project. The datafiles titled MeasLog_YYYY-MM-DD.dat correspond to the raw data used for the data analysis presented in “Hygrothermal analysis at critical points of an internally insulated historic wall without vapour barrier: in situ measurements and dynamic simulation”, submitted for publication in journal  energies. Each file, format MeasLog_YYYY-MM-DD.dat, corresponds to daily registered data monitored every minute. Each file, format MeasLog_YYYY-MM-DD.dat, contains temperature (T)  and relative humidity (RH) values, monitored through T-RH sensors (Telaire T9602; Amphenol). The general architecture of the acquisition system is based on a Master Slave configuratio, as described in “Development of a Compatible, Low Cost and High Accurate Conservation Remote Sensing Technology for the Hygrothermal Assessment of Historic Walls” (doi:10.3390/electronics8060643). Each file, format MeasLog_YYYY-MM-DD.dat is a text-based DAT file and can be opened with a standard text editor.

opencc-by-4.0Dec 2020View details →

Coral abundance on the inshore Great Barrier Reef 1998-2013

Study sites: Coral assemblages were surveyed at two depths (shallow: 2-4 m; deep: 5-8 m) at each of four locations on the Great Barrier Reef off Townsville; Nelly Bay (S19.167°, E146.850°) and Geoffrey Bay (S19.155°, E146.861°) on Magnetic Island and Little Pioneer Bay (S18.594°, E146.485°) and southeast Pelorus (S18.560°, E146.500°) in the Palms Island group giving a total of eight sites. Survey method: Between six and nine surveys were conducted at each site between March 1998 and 2013. Between four to six replicate 15 m x 0.5 m belt transects were used at each site on each survey. The abundance of all hard and soft corals (i.e. Scleractinia, Alcyonacea and Hydrocorallina) with a maximum diameter greater than 5 cm within the belt transects was recorded. Coral were identified to genus following Veron (2000). We used colony abundance instead of the more commonly used metric of coral cover because it provides a better estimate of population level mortality.

opencc-by-4.0Oct 2018View details →

The organophosphate pesticide methamidophos opens the blood-testis barrier and covalently binds to ZO-2 in mice

We studied biological effects and post-translational modifications of proteins after treating mice with the pesticide methamidophos. This data set provides evidence for the modification of ZO-2, indicating that the blood-testis barrier in mouse was crossed.

opencc-by-4.0Jun 2017View details →

Data for: Drivers and Barriers for Microservice Adoption in the German Software Industry

Microservices are an architectural style for software which currently receives a lot of attention in both industry and academia. Several companies employ microservice architectures with great success, and there is a wealth of blog posts praising their advantages. Especially so-called Internet-scale systems use them to satisfy their enormous scalability requirements and to rapidly deliver new features to their users. However, microservices are not only popular with large, Internet-scale systems. Many traditional companies are also considering whether microservices are a viable option for their applications. However, these companies may have other motivations to employ microservices, and see other barriers which may prevent them from adopting microservices. Furthermore, these drivers and barriers may differ among industry sectors. This dataset contains the questions and results of a survey on drivers and barriers for microservice adoption among professionals in the German software industry. In addition to overall drivers and barriers, we particularly focused on the use of microservices to modernize existing software, with special emphasis on implications for runtime performance and transactionality.

opencc-by-4.0Aug 2017View details →

Drivers and Barriers for Open Access Publishing - WoS 2016 Dataset

Answers to a survey on gold Open Access run from July to October 2016. The dataset contains 15,235 unique responses from Web of Science published authors. This survey is part of a PhD thesis from the University of Granada in Spain. More details about the study can be found in the full text document, also available in Zenodo. Following are listed the questions related to the WoS 2016 dataset. Please note that countries with less than 40 answers are listed as "Other" in order to preserve anonymity. * 1. How many years have you been employed in research? <ul> <li>Fewer than 5 years</li> <li>5-14 years</li> <li>15-24 years</li> <li>25 years or longer</li> </ul> Many of the questions that follow concern Open Access publishing. For the purposes of this survey, an article is Open Access if its final, peer-reviewed, version is published online by a journal and is free of charge to all users without restrictions on access or use. * 2. Do any journals in your research field publish Open Access articles? <ul> <li>Yes</li> <li>No</li> <li>I do not know</li> </ul> * 3. Do you think your research field benefits, or would benefit from journals that publish Open Access articles? <ul> <li>Yes</li> <li>No</li> <li>I have no opinion</li> <li>I do not care</li> </ul> * 4. How many peer reviewed research articles (Open Access or not Open Access) have you published in the last five years? <ul> <li>1-5</li> <li>6-10</li> <li>11-20</li> <li>21-50</li> <li>More than 50</li> </ul> * 5. What factors are important to you when selecting a journal to publish in? [Each factor may be rated “Extremely important”, “Important”, “Less important” or “Irrelevant”. The factors are presented in random order.] <ul> <li>Importance of the journal for academic promotion, tenure or assessment</li> <li>Recommendation of the journal by my colleagues</li> <li>Positive experience with publisher/editor(s) of the journal</li> <li>The journal is an Open Access journal</li> <li>Relevance of the journal for my community</li> <li>The journal fits the policy of my organisation</li> <li>Prestige/perceived quality of the journal</li> <li>Likelihood of article acceptance in the journal</li> <li>Absence of journal publication fees (e.g. submission charges, page charges, colour charges)</li> <li>Copyright policy of the journal</li> <li>Journal Impact Factor</li> <li>Speed of publication of the journal</li> </ul> 6. Who usually decides which journals your articles are submitted to? (Choose more than one answer if applicable) <ul> <li>The decision is my own</li> <li>A collective decision is made with my fellow authors</li> <li>I am advised where to publish by a senior colleague</li> <li>The organisation that finances my research advises me where to publish</li> <li>Other (please specify) [Text box follows]</li> </ul> 7. Approximately how many Open Access articles have you published in the last five years? <ul> <li>0</li> <li>1-5</li> <li>6-10</li> <li>More than 10</li> <li>I do not know</li> </ul> [If the answer is “0”, the survey jumps to Q10.] * 8. What publication fee was charged for the last Open Access article you published? <ul> <li>No charge</li> <li>Up to €250 ($275)</li> <li>€251-€500 ($275-$550)</li> <li>€501-€1000 ($551-$1100)</li> <li>€1001-€3000 ($1101-$3300)</li> <li>More than €3000 ($3300)</li> <li>I do not know</li> </ul> [If the answer is “No charge or I don’t know” the survey jumps to Q20. ] * 9. How was this publication fee covered? (Choose more than one answer if applicable) <ul> <li>My research funding includes money for paying such fees</li> <li>I used part of my research funding not specifically intended for paying such fees</li> <li>My institution paid the fees</li> <li>I paid the costs myself</li> <li>Other (please specify) [Text box follows]</li> </ul> * 10. How easy is it to obtain funding if needed for Open Access publishing from your institution or the organisation mainly responsible for financing your research? <ul> <li>Easy</li> <li>Difficult</li> <li>I have not used these sources</li> </ul> * 11. Listed below are a series of statements, both positive and negative, concerning Open Access publishing. Please indicate how strongly you agree/disagree with each statement. [Each statement may be rated “Strongly agree”, “Agree”, “Neither agree nor disagree”, “Disagree” or “Strongly disagree”. The statements are presented in random order.] <ul> <li>Researchers should retain the rights to their published work and allow it to be used by others</li> <li>Open Access publishing undermines the system of peer review</li> <li>Open Access publishing leads to an increase in the publication of poor quality research</li> <li>If authors pay publication fees to make their articles Open Access, there will be less money available for research</li> <li>It is not beneficial for the general public to have access to published scientific and medical articles</li> <li>Open Access unfairly penalises research-intensive institutions with large publication output by making them pay high costs for publication</li> <li>Publicly-funded research should be made available to be read and used without access barrier</li> <li>Open Access publishing is more cost-effective than subscription-based publishing and so will benefit public investment in research</li> <li>Articles that are available by Open Access are likely to be read and cited more often than those not Open Access</li> </ul> This study and its questionnaire are based on the SOAP Project (http://project-soap.eu). An article describing the highlights of the SOAP Survey is available at: https://arxiv.org/abs/1101.5260. The dataset of the SOAP survey is available at http://bit.ly/gSmm71. A manual describing the SOAP dataset is available at http://bit.ly/gI8nc.

Fig. 1 in Evidence That Salt Water May Not Be A Barrier To The Dispersal Of Asian Freshwater Crabs (Decapoda: Brachyura: Gecarcinucidae And Potamidae)

Fig. 1. Hemolymph osmolality of three experimental groups (A–C) of Esanthelphusa dugasti (Gecarcinucidae) held for up to 9 days in deep 30 cm fresh water and in 22 and 30 ppt salt water. Line with diamonds = water osmolality. Columns = hemolymph osmolality, light = sub-adults; dark = juveniles; error bars = standard deviation. The x-axis shows the number of days that crabs were subjected to a particular salinity. A. Sub-adults in fresh water (n = 27 and 24, respectively). B. Juveniles in 22 ppt salt water (n = 25). C. Sub-adults (n = 22 and 8, respectively) and juveniles (n = 12) in 30 ppt water. Dark horizontal bar = salinity at which hemolymph is hyperosmotic to the external water.

Fig. 2 in Evidence That Salt Water May Not Be A Barrier To The Dispersal Of Asian Freshwater Crabs (Decapoda: Brachyura: Gecarcinucidae And Potamidae)

Fig. 2. Hemolymph osmolality of adult Eosamon smithianum (Potamidae) held for up to 9 days in deep 30 cm fresh water and in 22, 25, and 30 ppt salt water. Line with diamonds = water osmolality. Columns = hemolymph osmolality, light = sub-adults; dark = juveniles; error bars = standard deviation. The x-axis shows the number of days that crabs were subjected to a particular salinity. Adults (n = 5) and juveniles (n = 17, 5) in fresh water ('baseline'), and in deep sea water at 22 ppt (n = 5, 1, respectively), 25 ppt (n = 5), and 30 ppt (n = 3). Dark horizontal bar = salinity at which the hemolymph is hyperosmotic to the external water.

Fig. 4 in Evidence That Salt Water May Not Be A Barrier To The Dispersal Of Asian Freshwater Crabs (Decapoda: Brachyura: Gecarcinucidae And Potamidae)

Fig. 4. Hemolymph osmolality of three experimental groups (A–C) of Eosamon smithianum (Potamidae) held in shallow 2.5 cm water of different salinities for up to 13 days. Line with diamonds = water osmolality. Columns = hemolymph osmolality, light = subadults; dark = juveniles; error bars = standard deviation. The x-axis shows the number of days that crabs were subjected to a particular salinity. A. Adults (n = 20, 15, 15, 12, respectively) and juveniles (n = 10, 5, 3, respectively) in fresh water. B. Adults (n = 16, 12, 10, respectively), juveniles (n= 12, 6, respectively) and hatchlings (n=12) in 22 ppt salt water. C. Adults in 28 ppt. salt water (n = 22, 20, 18, respectively). Dark horizontal bar = salinity at which the hemolymph is hyperosmotic to the external water.

Fig. 3 in Evidence That Salt Water May Not Be A Barrier To The Dispersal Of Asian Freshwater Crabs (Decapoda: Brachyura: Gecarcinucidae And Potamidae)

Fig. 3. Hemolymph osmolality of Esanthelphusa dugasti (Gecarcinucidae) in shallow 2.5 cm water at salinities of 0, 7, 13, 15, 22, 30 and 33 ppt. The x-axis shows the number of days (5, 9, or 13) that 7 groups of crabs (A–G) were subjected to a particular salinity. Line with diamonds = water osmolality. Columns = hemolymph osmolality, light = sub-adults; dark = juveniles; error bars = standard deviation. Hemolymph osmolality of: A, sub-adults (n = 24, 17, and 14, respectively), and juveniles (n = 20) in fresh water; B, sub-adults (n = 26, 10, 4, respectively) in 7 ppt salt water. C, subadults (n = 19 and 14) and juveniles (n = 10) in 13 ppt salt water. D, sub-adults in 15 ppt salt water (n = 25, 17 and 6, respectively). E, sub-adults (n = 20, 9, 6, respectively) and juveniles (n = 22) in 22 ppt salt water. F, sub-adults (n = 26, 7, 7, respectively) and juveniles (n = 19) in 30 ppt salt water. G, juveniles in 33 ppt salt water (n = 4, 2, respectively). Dark horizontal bar = salinities at which the hemolymph is hyperosmotic to the external water.

opencc-by-4.0Dec 2023View details →

Figure 1 in A New Species of Metaprotella (Crustacea: Amphipoda: Caprellidae) from One Tree Island, Southern Great Barrier Reef, Queensland, Australia

Figure 1. Metaprotella lowryi sp. nov., holotype male, 7.08 mm, AM P.100147, and paratype female, 6.02 mm, AM P.100149, One Tree Island, Great Barrier Reef, Queensland, Australia, 23°29'05"S 152°04'07"E. Scale 1.0 mm.

opencc-by-4.0Dec 2023View details →

Figure 2 in A New Species of Metaprotella (Crustacea: Amphipoda: Caprellidae) from One Tree Island, Southern Great Barrier Reef, Queensland, Australia

Figure 2. Metaprotella lowryi sp. nov., holotype male, 7.08 mm, AM P.100147, One Tree Island, southern Great Barrier Reef, Queensland, Australia, 23°29'05"S 152°04'07"E. L, left; LL, lower lip; MD, mandible; MX, maxilla, MXP, maxilliped; R, right, and UL, upper lip. Scale = 0.05 mm.