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1,069 results for “Data managment”
Humboldt-Universität zu Berlin Research Data Management Survey Results
<p>This spreadsheet represents anonymized summary results of the research data management survey at Humboldt-Universität zu Berlin.</p>
The Role of Research University Libraries in Research Data Management: The Case of Türkiye
Open the record for dataset details and reuse information.
OpenET model data for assessing the accuracy of OpenET satellite-based evapotranspiration data to support water resource and land management applications
<h2>Overview</h2> <p>This dataset includes daily and monthly evapotranspiration (ET) data from the remote sensing models that comprise the [OpenET](https://openetdata.org/) ensemble as described in Melton et al., 2022 (https://doi.org/10.1111/1752-1688.12956); these data were extracted at specific locations within the contiguous United States that coincide with *in situ* measurement stations, including eddy covaraiance, Bowen-ratio, and lysimeter stations. Model ET data where extracted at each site in this dataset using flux footprints as described in Volk et al., (2023) (https://doi.org/10.1016/j.agrformet.2023.109307). These model data alongside the corresponding *in situ* ET data (https://doi.org/10.1016/j.dib.2023.109274) were subsequently used in the manuscript for the OpenET Phase II Intercomparison and Accuracy Assessment (https://doi.org/10.1038/s44221-023-00181-7). </p> <h3><br>Description of the data and file structure</h3> <p>The dataset is in a compressed (zipped) archive titled "OpenET_PhaseII_model_ET_dataset", so first it needs to be downloaded and extracted. The dataset is comprised of just three files. The first file is a Microsoft Excel file "Station_metadata.xlsx" that contains information about the *in situ* ET measurement stations where the OpenET model data was extracted. This file contains information such as site ID's, coordinates, land cover information, and site principal investigator (PI) contact information. Again, the corresponding *in situ* ET data are not included in this dataset. The other two files are tab-delimited text files containing timeseries the OpenET model data themselves, namely the daily ET [mm/day] and monthly ET [mm/month] as extracted for each model and the ensemble value as used in the OpenET Phase II Intercomparison and Accuracy Assessment. </p> <h3><br>Access information and code/software</h3> <p>OpenET data that was used here was produced using operational methods that are implemented on the Google Earth Engine platform. Monthly OpenET model data can be retrieved through Google Earth Data Catalog (e.g., https://developers.google.com/earth-engine/datasets/catalog/OpenET_ENSEMBLE_CONUS_GRIDMET_MONTHLY_v2_0) or through the [online data explorer](https://openetdata.org/) or using the [OpenET API](https://openetdata.org/api-info/).</p>
Data for: Climatic and management-related drivers of endemic European spruce bark beetle populations in boreal forests
<p>Climate change is already reducing carbon sequestration in Central European forests dramatically through extensive droughts and bark beetle outbreaks. Further warming may threaten the enormous carbon reservoirs in the boreal forests in northern Europe, unless disturbance risks can be reduced by adaptive forest management. The European spruce bark beetle (<em>Ips typographus</em>) is a major natural disturbance agent in spruce-dominated forests and can overwhelm the defences of healthy trees through pheromone-coordinated mass-attacks.</p> <p>We used an extensive dataset of bark beetle trap counts to quantify how climatic and management-related factors influence bark beetle population sizes in boreal forests. Trap data was collected during a period without outbreaks and can thus identify mechanisms that drive populations towards outbreak thresholds.</p> <p>The most significant predictors of bark beetle population size were volume of mature spruce, extent of newly exposed clearcut edges, temperature, and soil moisture. For clearcut edge, temperature, and soil moisture, a three-year time lag produced the best model fit. We demonstrate how a model incorporating the most significant predictors, with a time lag, can be a useful management tool by allowing spatial prediction of future beetle population sizes.</p> <p><em>Synthesis and Applications</em>: Some of the population drivers identified here, i.e., spruce volume and clearcut edges, can be targeted by adaptive management measures to reduce the risk of future bark beetle outbreaks. Implementing such measures may help preserve future carbon sequestration of European boreal forests.</p>
Figures for Developing an online data-driven approach for prognostics and health management of lithium-ion batteries
Open the record for dataset details and reuse information.
Data from: Arthropod abundance is most strongly driven by crop and semi-natural habitat type rather than management in an intensive agricultural landscape in the Netherlands
<p>The dataset supporting the publication "Arthropod abundance is most strongly driven by crop and semi-natural habitat type rather than management in an intensive agricultural landscape in the Netherlands" is provided. Methods of data collection can be found in the respective publication.</p>
Data from: Dysphagia Management in COPD: A National Survey
<p><span>Chronic obstructive pulmonary disease (COPD) is a progressive lung disease affecting approximately 300 million people globally. Ireland has the highest hospitalisation for COPD exacerbations in Europe. Dysphagia occurs in 17-85% of people with COPD (PwCOPD) and is a contributory factor to COPD exacerbations. Effective dysphagia management can reduce hospitalisation for PwCOPD. Determining Speech and Language Therapists’ (SLTs) clinical practices and confidence levels when working with PwCOPD and dysphagia is warranted. Following a pilot study, a survey exploring SLTs (<em>n </em>=131) clinical practices and confidence levels prior to and during COVID-19 was issued to SLTs working with PwCOPD and dysphagia in the Republic of Ireland. 88 survey responses were analysed. Survey respondents had up to twenty years plus experience working with PwCOPD across primarily acute and outpatient settings. Self-reported confidence ratings when assessing and treating dysphagia in PwCOPD were mixed, with some statistically significant changes noted during COVID-19. Clinical Bedside Swallow Examinations were routinely used but some components were modified because of<span> </span>COVID-19 infection control guidelines. Routine use of instrumental assessment was conducted by 30% of respondents pre COVID-19 and 39% of respondents during COVID-19. Dysphagia management primarily focused on education and compensatory strategies. Less than 1/3 of respondents used policies, procedures, protocols and guidelines (PPPGs) when managing dysphagia in PwCOPD. Development and dissemination of national PPPGs and education regarding evidence-based management of dysphagia in PwCOPD may support consistent care by SLTs. Further research investigating evidence-based dysphagia management and the impact of PPPGs and education on clinical practice is recommended. </span></p>
Data from: A burning issue: Savanna fire management can generate enough carbon revenue to help restore Africa's rangelands and fill protected area funding gaps
<p>Many savanna-dependent species in Africa including large herbivores and apex predators are at increasing risk of extinction. Achieving effective management of protected areas (PAs) in Africa where lions live will cost an estimated USD >$1-2 B/year in new funding. We explored the potential for fire management-based carbon-financing programs to fill this funding gap and benefit degrading savanna ecosystems. We demonstrated how introducing early dry season fire management programs could produce potential carbon revenues (PCR) from either a single carbon-financing method (avoided emissions) or from multiple sequestration methods ranging from USD $59.6-$655.9 M/year (at USD $5/ton) or USD $155.0 M–$1.7 B/year (at USD $13/ton). We highlighted variable but significant PCR for savanna PAs from USD $1.5–$44.4 M/year per PA. We suggest investing in fire management programs to jump-start the United Nations Decade of Ecological Restoration to help restore degraded African savannas and conserve imperiled keystone herbivores and apex predators. </p>
Data from: The active mouse rests within: Energy management among and within individuals
<p>1. The relationship between daily energy expenditure (DEE) and resting metabolic rate (RMR) provides insight into how organisms allocate energy to maintenance <i>versus</i> energetically expensive activities such as locomotor activity.</p> <p>2. Three models have been devised to describe energy management: the allocation, independent, and performance models, which respectively predict a DEE-RMR slope of <i>b</i><1, <i>b</i>=1, and <i>b</i>>1.</p> <p>3. Here, we took paired repeated metabolic and behavioural measurements in 51 female white-footed mice to 1) evaluate which energy management models apply at the among- and within-individual levels, and to 2) quantify the relationship between metabolic traits and two energetically expensive behaviours.</p> <p>4. The DEE-RMR slope was different at the among- <i>versus</i> within-individual levels, with values supporting the performance and allocation models at the among- and within-individual levels, respectively. Accordingly, the relationship between voluntary wheel running and RMR was positive at the among-individual level (<i>r</i><sub> </sub>= 0.40±0.21), but negative at the within-individual level (<i>r </i>= -0.23±0.10).</p> <p>5. To our knowledge, this is the first study to simultaneously partition the relationship between RMR and behaviour at the among- <i>versus</i> within-individuals levels while determining which energy management models apply at each of these levels. In doing so, we have identified a mechanism through which compensation occurs at the within-individual level.</p>
Data related to a study on adaptive management of Nile infrastructure
<p>Economy-related data of Ethiopia, Sudan, and Egypt.</p>
Raw data for "Assessing Cover Crop and Intercrop Performance Along a Farm Management Gradient" (2022)
<p>This dataset accompanies the publication "Assessing Cover Crop and Intercrop Performance Along a Farm Management Gradient" by Stratton et al. in the journal Agriculture, Ecosystems, and Environment (2022). <a href="https://doi.org/10.1016/j.agee.2022.107925">https://doi.org/10.1016/j.agee.2022.107925</a></p> <p>METHODS:</p> <p>We conducted our experiment between May 2018 and December 2019 on 14 farms in the eastern coastal highlands region of Santa Catarina, Brazil. The mean altitude of sites was 467 m (+/- 161 m). Eastern Santa Catarina has a subtropical climatic pattern, with mean annual rainfall ranging from 1,500-1,700 mm (Wrege et al., 2012). While 2018 had typical weather patterns for the region, 2019 was a dry year, particularly during the spring months (Appendix B, Table B.1). All farms were located in the Colonial Serrana Catarinense soil microregion, one of 16 designated microregions in the state of Santa Catarina (EMBRAPA, 2004). Primary soil types in our study site are associations of dystric Cambisols and haplic Acrisols (typic Dystrocryepts and typic Paleudults in the USDA Soil Taxonomy), which tend to be moderately to highly acidic, with limited soil nutrient availability and moisture retention (EMBRAPA, 2004; IUSS Working Group WRB, 2015; USDA, 2010). To support crop production, farmers in the region typically apply lime (calcium and magnesium carbonate) to agricultural fields to increase soil pH from <5.5 to 6 (Comissão de Química e Fertilidade do Solo - RS/SC, 2016). Exact farm locations within the region are not given and farmer identities have been anonymized.</p> <p><em>Experimental design</em></p> <p>The fully factorial experiment had six treatments (Figure 2): (1) cover crop + pea-cucumber intercrop, (2) cover crop + pea monocrop, (3) cover crop + cucumber monocrop, (4) fallow + pea-cucumber intercrop, (5) fallow + pea monocrop, and (6) fallow + cucumber monocrop. Due to the timing of farm recruitment, only conventional and transitioning farms participated in the first year of cover cropping (2018); agroecological farms were added to the study during the vegetable intercropping period of 2018 and had their first round of cover cropping in 2019. The cover crop mixture treatment was designed to emulate traditional practices in the region, as well as to include functionally complementary legume and grass species: common vetch (<em>Vicia sativa </em>L.) and black oat (<em>Avena strigosa </em>Schreb). We also selected vegetables with distinct ecological functional traits, such that intercropping represented an increase in functional diversity relative to mono-cropped vegetables. Snow peas are N-fixing legumes with a vining, upright structure and a deep root system, whereas cucumbers are low-lying, non-legume cucurbits that provide groundcover and have a relatively shallow, extensive root system.</p> <p> </p> <p>Cover crop treatments consisted of two adjacent 50 m2 plots in each field, one of which was planted with the cover crop mixture; the other served as a weedy fallow control. In 2018, the cover crop mixture seeding rate was 72 kg/ha black oat and 36 kg/ha common vetch. Due to poor vetch performance in mixtures at this rate, we increased the vetch seeding rate to 60 kg/ha in 2019, maintaining the black oat rate from 2018. Cover crop seeds were inoculated with the Brazilian strain <em>Rhizobium etli </em>(SEMIA 384; source: FEPAGRO) at 4 g/kg vetch seed prior to planting. Cover crops were grown until peak flowering, and then cover crops (and weeds in the fallow) were incorporated into the soil by rototiller (<em>n</em> = 7 farms) or by hand hoeing (<em>n</em> = 7 farms), based on farms’ available machinery, between September 5-10 in 2018 and September 10-18 in 2019 (approximately one week following cover crop sampling on each farm).</p> <p> </p> <p>Vegetables were planted two weeks following cover crop and weed biomass incorporation within a period of 7-10 days across sites. Harvest dates were spaced such that crops were growing for approximately the same period across farms. The 50 m2 plots were each divided into three intercrop treatments with a ~1 m2 pathway between each treatment, for a total of 6 treatments randomly assigned to plots per 100 m2. We planted a climbing variety of snow peas (<em>Pisum sativum</em> subsp. <em>sativum</em> var. <em>macrocarpum</em>,<strong> </strong>“<em>Torta de flor roxa”</em>) and pickling cucumber (<em>Cucumis sativa </em>L. var. <em>Pepino HT </em>05) in intercrops and in their respective monocrops, using a replacement design (i.e., equivalent crop densities in all treatments). Snow pea seeds were inoculated with <em>Rhizobium leguminosarum</em> var. <em>viceae</em> (SEMIA 3007/BR 619, source: UFSC ENR/CCA) at a rate of 4 g/kg directly prior to planting. There were five rows of crops per treatment, with only the three middle rows harvested to limit edge effects. In-row spacing was 60 cm for cucumber and 20 cm for peas, with 60 cm between rows in both intercrops and monocrops. Cucumbers were grown as starts for 2.5 weeks before planting, and peas were planted from seed on the same planting date as cucumber starts.</p> <p> </p> <p>In the summer between January and May 2019 all fields were planted to a sunflower (<em>Helianthus annuus</em> L.) crop, which was incorporated into the soil during flowering approximately two weeks prior to cover crop planting in 2019. Because we sought to understand the effects of crop diversification given existing water and nutrient limitations on working farms, the experiment was entirely rainfed and legume N fixation was the sole external N source.</p> <p><em>Soil sampling and analysis</em></p> <p>Prior to the first cover cropping period, we collected a composite sample of 15-20 soil cores (2.5 cm diameter, 20 cm depth) on both the cover crop and fallow sides of each experimental field (<em>n</em> = 28) for analysis of baseline conditions (see Appendix B for full details). Briefly, soil was analyzed for pH, macro- and micronutrients, and soil organic matter (SOM) by the Santa Catarina State Agricultural Agency (EPAGRI) in Ituporanga, Santa Catarina, Brazil, using standard protocols (Comissão de Química e Fertilidade do Solo - RS/SC, 2016). pH was measured with a glass electrode both with and without Sikora’s buffer, and buffered pH is used throughout this paper (Tecnal TEC-11 MP). Soil organic C and total soil N to 20 cm were determined by dry combustion on a Leco TruMac CN Analyzer (Leco Corporation, St. Joseph, Michigan, USA). We measured soil texture (% clay, sand, and silt) using a total dispersion method with sodium hexametaphosphate (Empresa Brasileira de Pesquisa Agropecuaria (EMBRAPA), 1997). Bulk density was estimated from the mass of 10 fresh soil cores per treatment, with subsequent accounting for soil moisture.</p> <p> </p> <p>We measured C mineralization as a baseline indicator of soil microbial activity and biological soil fertility at the start of the experiment, and N mineralization as a response variable following the second year of cover crop treatments. Specifically, using the baseline soil sample, we conducted a short-term (24-hour) C mineralization assay to determine potentially mineralizable C (PMC), which measures the flux of CO2 following re-wetting of previously air-dried, sieved soil using a Li-Cor (Franzluebbers et al., 2000; Hurisso et al., 2016). To measure potentially mineralizable N (PMN), we conducted a two-week aerobic incubation using fresh soil collected at vegetable crop planting in the second year of the experiment (spring 2019), two weeks after cover crop and weed biomass incorporation (Drinkwater et al., 1996; Appendix B.2). PMN was calculated as the difference between extractable soil inorganic N (NH4+ and NO3-) at the start and end of the incubation. We used pre-incubation extractable inorganic N concentration (mg/kg) as a measure of soil inorganic N availability at vegetable crop planting.</p> <p> <em>Cover crop sampling and analysis</em></p> <p>Cover crop biomass sampling took place from August 28-September 2 in 2018 and September 4-10 in 2019. During peak flowering of both common vetch and black oat, we destructively harvested the aboveground biomass of cover crop mixtures and weedy fallows from two 0.5 x 0.5 m quadrats of each treatment per field. We took care to avoid treatment edges, cut plant material to the soil surface, and separated harvested plant material by species, grouping all weeds together. Aboveground biomass was dried in a forced-air oven at 60 °C for 48 hours. Following grinding in a Wiley mill to 2 mm, % N and C content was determined by dry combustion on an elemental analyzer (Leco, as above). Community-weighted means were calculated for total aboveground biomass C and N in cover crop species and weeds, to determine the overall C and N inputs to soil following incorporation of biomass on each farm. We measured biological N2 fixation in inoculated common vetch from the cover crop phase of the experiment in 2018 and 2019. Vetch N fixation was estimated using the 15N natural abundance method (Shearer and Kohl, 1986), which compares stable N isotope ratios in the legume and reference species (oat monocultures) (Appendix C).</p> <p> <em>Vegetable crop sampling and analysis</em></p> <p>To capture the full production period of both cucumber and pea crops, yield was measured in two harvests, which were approximately 14 days apart on each farm. Harvest dates ran from November 16-December 6 in 2018 and November 20-December 4 in 2019. We measured yield by weighing all harvestable fruit from three designated, representative row sections (6 plants on average per row) per crop type per treatment. Rows were sampled from the center of each treatment to reduce edge effects. We calculated yield as total crop production (g) per plant harvested in each row. Mean yield for each crop type was calculated as the average of the three harvested rows per treatment on a per-plant basis and was then aggregated to the plot and hectare level based on experimental planting densities. Total N harvested, or “N yield”, was calculated for all treatments by multiplying the % N in each vegetable crop by its yield (kg/ha) after accounting for crop water content. Using plot-level yield data, we subsequently calculated the relative yield total (Land Equivalent Ratio, LER) for intercrop treatments by farm using the standard equation (Vandermeer, 1989) (Table 1). As a relative measure of total crop production per area, when mean LER > 1, intercrops were considered to have “overyielded” compared to their component monocrops. We calculated the LER for N yield (LERN in kg N/ha) using the same formula.</p> <p> </p> <p>At the second vegetable harvest, we destructively sampled whole aboveground crop biomass, including residues and remaining fruits, from the designated experimental rows. Following the harvest, a minimum of six representative cucumbers per treatment (from different plants) per farm were washed in deionized water, air-dried, sliced, and the middle sections were combined into a homogenized, composite sample of ~100 g and then dried for one week at 60 ºC. All peas from each treatment’s subplot were washed in deionized water, air-dried, de-stemmed, chopped, and each homogenized sample (35-60 g fresh material) was subsequently dried at 60 ºC in a forced-air oven for 48 h to one week, until fully desiccated. Dried vegetable biomass residues were ground using a Wiley mill; vegetable crop samples were ground in a coffee grinder; and all vegetable samples were analyzed for % C and N on a LECO elemental analyzer.</p> <p><strong>See</strong><strong> supplemental material from Stratton et al. 2022 for further detailed information on methods.</strong></p>
Data from: Clinical presentation and management of SMART syndrome
<div class="WordSection1"> <p><span>Stroke-like migraine attacks after radiation therapy (SMART) syndrome represents a rare but serious condition manifesting years after cranial radiation therapy (RT). Characterized by migraine-type headaches, stroke-like deficits and/or seizures and MR imaging abnormalities, including cortical gyriform enhancement in irradiated brain regions, SMART remains diagnostically and therapeutically challenging. Distinction from tumor progression is difficult and treatment options are limited. Although frequently reversible, SMART episodes can recur and effectuate persistent neurologic and/or imaging sequelae.</span></p> </div>
Data from: Genotyping-in-Thousands by sequencing panel development and application to inform kokanee salmon (Oncorhynchus nerka) fisheries management at multiple scales
<p>The ability to differentiate life history variants is vital for estimating fisheries management parameters, yet traditional survey methods can be inaccurate in mixed-stock fisheries. Such is the case for kokanee, the resident freshwater form of sockeye salmon (<i>Oncorhynchus nerka</i>), which exhibits various reproductive ecotypes (stream-, shore-, deep-spawning) that co-occur with each other and/or anadromous <i>O. nerka</i> in some systems across their pan-Pacific distribution. Here, we developed a multi-purpose Genotyping-in-Thousands by sequencing (GT-seq) panel of 288 targeted single nucleotide polymorphisms (SNPs) to enable accurate kokanee stock identification by geographic basin, migratory form, and reproductive ecotype across British Columbia, Canada. The GT-seq panel exhibited high self-assignment accuracy (93.3%) and perfect assignment of individuals not included in the baseline to their geographic basin, migratory form, and reproductive ecotype of origin. The GT-seq panel was subsequently applied to Wood Lake, a valuable mixed-stock fishery, revealing high concordance (>98%) with previous assignments to ecotype using microsatellites and TaqMan<span> </span>SNP genotyping assays, while improving resolution, extending a long-term time-series, and demonstrating the scalability of this approach for this system and others.</p>
Radiomics metrics combined with clinical data in the surgical management of early-stage (cT1-T2 N0) of tongue squamous cell carcinomas: a preliminary study
<p>We uploaded the clinical and the hematological parameters of enrolled patients in the study "Radiomics metrics combined with clinical data in the surgical management of early-stage (cT1-T2 N0) of tongue squamous cell carcinomas: a preliminary study" accepted on Biology journal.</p> <p>Clinical and hematological parameters include: age; gender; DOI, NLR; PLR; LMR; SIRI; SII; T stage; grading; metastatic lymph nodes; perineural infiltration; vascular infiltration.</p> <p> </p>
Data from: Population genomics of Sitka black-tailed deer supports invasive species management and ecological restoration on islands
<p>Invasive mammals represent a critical threat to island biodiversity; eradications can result in ecological restoration yet may fail in the absence of key population parameters. Over-browsing by invasive Sitka black-tailed deer (<em>Odocoileus hemionus sitkensis</em>) is causing severe ecological and cultural impacts across the Haida Gwaii archipelago (Canada). Previous eradication attempts demonstrate forest regeneration upon deer removal, but reinvasion reverses conservation gains. Here we use restriction-site associated DNA sequencing (12,947 SNPs) to investigate connectivity and gene flow of invasive deer (n=181) across 15 islands, revealing little structure throughout Haida Gwaii and identifying the large, central island of Moresby (>2,600 km2) as the greatest source of migrants. As a result, the archipelago itself should be considered the primary eradication unit, with the exception of geographically isolated islands like SGang Gwaay. Thus, limiting eradications to isolated islands combined with controlled culling and enhanced biosecurity may be the most effective strategies for achieving ecological restoration goals.</p>
Data from: Irregular forest structures originating after fire: an opportunity to promote alternatives to even-aged management in boreal forests
<p><span>1. Even-aged silviculture based on short-rotation clearcuts had severely altered boreal forests. Silvicultural alternatives (e.g., continuous cover or retention forestry) has the potential to restore and protect the habitats and functions of boreal forests. These alternatives are however often restricted to structurally complex old-growth forest, which are particularly threatened by anthropogenic disturbances. Increasing the use of alternatives to even-aged silviculture in early-successional stands could help recruit more structurally complex forests, with characteristics closer to the old-growth. In this article, we therefore evaluate the potential for silvicultural alternatives to even-aged management in boreal forests that burned less than a century ago.</span></p> <p><span>2. We analyzed 1085 field plots in a 243000 km<sup>2</sup> area situated in the boreal forest of eastern Canada. These plots burned 30 to 100 years before the survey and had not been subjected to previous or subsequent anthropogenic disturbance; they hence represent young primary forests. The main patterns of tree diameter distribution variation within the plots were identified using k-means clustering. Stand structure, tree species composition, and environmental variables that most explained the differences among the clusters were identified with a random forest model, and then compared using Kruskal-Wallis and Fisher's exact tests.</span></p> <p><span>3.</span> <span>The majority (>75 %) of the plots presented an irregular structure of stem diameters (i.e., non-normally distributed, with many small diameter trees). The understorey was generally dominated by black spruce (<em>Picea mariana</em> [Mill.] BSP), a shade-tolerant species. Irregular structures were observed in both forests of high and low productivity, implying that different processes (e.g., early regeneration, variable tree growth) can lead to observed early irregular structure. Regular structures were generally characterized by a higher productivity and abundance in hardwood species compared to the irregular structures. </span></p> <p><span>4. <em>Synthesis and application</em>: Many boreal forests of eastern Canada progress towards an irregular structure in the decades following the last stand-replacing fire. A substantial part of these early-successional forests may be suitable for alternatives to even-aged silviculture that better maintains habitats and functions of preindustrial boreal forests. </span></p>
Would you manage a vibrant data mine?
<p>The cryptocurrencies have revolutionized financial data management. Due to this situation, now we have to think: How will we manage all these interactions? How will we preserve digital information? and How will we reduce the environmental footprint of these systems?<br> This new decentralized informational architecture is putting many banking entities in check. It allows, without intermediaries, data transfers at a global level. Which is why this intercontinental database is gaining more and more followers. For this reason, professionals are required capable of managing the frenzied number of algorithms and in turn ensuring the security of the entire informational chain.</p>
Web scraping and API projects from "Online Data Collection and Management" (Spring 2022)
<p>As part of "Online Data Collection and Management" (taught at Tilburg University, Spring 2022), students collected publicly available datasets for use in academic research projects. With this repository, I am sharing (a) the documentation of these data sets, and (b) the associated source code that led to the collection of the data. The repository also contains the collected datasets.</p> <p>The data consists of the following projects:</p> <ul> <li>Autoscout (electric cars vs gasoline cars in the Dutch market)</li> <li>Mediamarkt (e-commerce)</li> <li>Steam API</li> <li>Twitch (chat capture)</li> <li>Zalando (e-commerce)</li> </ul> <p>Course website: https://odcm.hannesdatta.com. Archived at https://doi.org/10.5281/zenodo.6641811 (check for more recent versions if available).</p>
Data from: Human judgment vs. quantitative models for the management of ecological resources
Despite major advances in quantitative approaches to natural resource management, there has been resistance to using these tools in the actual practice of managing ecological populations. Given a managed system and a set of assumptions, translated into a model, optimization methods can be used to solve for the most cost-effective management actions. However, when the underlying assumptions are not met, such methods can potentially lead to decisions that harm the environment and economy. Managers who develop decisions based on past experience and judgment, without the aid of mathematical models, can potentially learn about the system and develop flexible management strategies. However, these strategies are often based on subjective criteria and equally invalid and often unstated assumptions. Given the drawbacks of both methods, it is unclear whether simple quantitative models improve environmental decision making over expert opinion. In this study, we explore how well students, using their experience and judgment, manage simulated fishery populations in an online computer game and compare their management outcomes to the performance of model-based decisions. We consider harvest decisions generated using four different quantitative models: (1) the model used to produce the simulated population dynamics observed in the game, with the values of all parameters known (as a control), (2) the same model, but with unknown parameter values that must be estimated during the game from observed data, (3) models that are structurally different from those used to simulate the population dynamics, and (4) a model that ignores age structure. Humans on average performed much worse than the models in cases 1–3, but in a small minority of scenarios, models produced worse outcomes than those resulting from students making decisions based on experience and judgment. When the models ignored age structure, they generated poorly performing management decisions, but still outperformed students using experience and judgment 66% of the time.
Quantitative assessment of research data management practice - 2021
<p>This survey aims to investigate research data management practices at EPFL and integrate their results into specific academic services. The previous two editions, in collaboration with TU Delft, Cambridge University and Illinois University, were carried out in 2017 and 2019.</p> <p>The objective of these surveys is to collect information on researchers' habits in terms of management of their research data, as well as to identify their needs for data curation services/support. For this edition of the survey, a particular focus has been given to the ways in which they disseminate data and code.</p> <p>You can find here a file corresponding to the report, in PDF, highlighting the findings of the survey, plus the file of the underlying data, in CSV, and a file with the graphical representation of such data, in PDF.<br> <br> For more information about this survey, a description on how the survey might be re-used by other institutions, and RDM services offered by the EPFL Library, please contact <a href="mailto:researchdata@epfl.ch?subject=Concerning%20the%20EPFL%20survey%20on%20RDM%20practices">researchdata@epfl.ch</a>.</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.