Find research datasets worth reusing

opencc-by-4.0Nov 2022View details →

Campi Flegrei cGPS network – RINEX data quality control (2000 – 2019)

For each cGPS station, the file contains a summary report with information about Rinex observation data. For each day, the summary line shows the following information: <ol> <li>cGPS station name (Name),</li> <li>the start time of the window, the time format is year (Y), month (M), day (D), hour and minutes (Hour), day of year (DOY), modified Julian date (M J Date) and GPS week (Week),</li> <li>the end time of the window, the time format is year (Y), month (M), day (D), hour and minutes (Hour), day of year (DOY), modified Julian date (M J Date), and GPS week (Week),</li> <li>the start and end times of the window (time format is year month day hour min),</li> <li>window time laps (Hrs),</li> <li>observation interval (OI),</li> <li>the number of possible observations (#expt) above the elevation mask,</li> <li>the number of complete observations (#obs),</li> <li>the ratio of complete to possible observations as a percent (DCP),</li> <li>the RMS “multipath combinations” values MP1 and MP2, in meters, limited by the elevation mask (MP1, MP22) rounded to two decimal points,</li> <li>cycle slips (CS),</li> <li>the ratio of complete observations to cycle slips (obs/CS).</li> </ol> A full description of cGPS network is reported in: - De Martino P, Dolce M, Brandi G, Scarpato G, Tammaro U (2021). The Ground Deformation History of the Neapolitan Volcanic Area (Campi Flegrei Caldera, Somma–Vesuvius Volcano, and Ischia Island) from 20 Years of Continuous GPS Observations (2000–2019). Remote Sensing. 13(14):2725. doi:10.3390/rs13142725. Please cite this when using the dataset

opencc-by-4.0Nov 2022View details →

Ischia cGPS network – RINEX data quality control (2001 – 2019)

opencc-by-4.0Dec 2021View details →

Data supporting: Impacts of extreme climatic events on trophic network complexity and multidimensional stability

Data used to produce the results presented in the manuscript entitled "Impacts of extreme climatic events on trophic network complexity and multidimensional stability", published in the journal "Ecology". The data were obtained from an outdoor pond mesocosm experiment where freshwater communities were exposed to two different heatwave scenarios.

opencc-by-4.0May 2022View details →

Code and extensive data for training neural networks for radiation, used in "Implementation of a machine-learned gas optics parameterization in the ECMWF Integrated Forecasting System: RRTMGP-NN 2.0""

Data and code used in a paper submitted to JAMES titled : Implementation of a machine-learned gas optics parameterization in the ECMWF Integrated Forecasting System 1) The files ml_training_*.7z contain extensive datasets (in NetCDF format) for training neural network versions of the RRTMGP gas optics scheme as described in the paper. The datasets are read by <a href="https://github.com/peterukk/rte-rrtmgp-nn/blob/main/examples/rrtmgp-nn-training/ml_train.py">ml_train.py.</a> 2) The ML datasets were in turn generated using the input profiles (in NetCDF format) inside inputs_to_RRTMGP.zip by running the Fortran programs <code>rrtmgp_sw_gendata_rfmipstyle.F90 and rrtmgp_lw_gendata_rfmipstyle.F90 </code>in rte-rrtmgp-nn/examples/rrtmgp-nn-training, which call the RRTMGP gas optics scheme, The input profiles contain millions of columns, hundreds of perturbation experiments (including hypercube-sampled gas concentrations), are derived from several different data sources (including CAMS reanalysis, GCM, and CKDMIP-MMM), and span present-day, preindustrial, and future atmospheric conditions. They could be used to generate training data for developing emulators of the full RTE+RRTMGP radiation scheme, not just gas optics (see nn_dev on the <a href="https://github.com/peterukk/rte-rrtmgp-nn">RTE+RRTMGP-NN repository on Github</a>, used in a previous paper where different emulation methods were compared) 3) The Fortran and Python code used for data generation and NN training are found in<a href="https://github.com/peterukk/rte-rrtmgp-nn/tree/main/examples/rrtmgp-nn-training"> rte-rrtmgp-nn/examples/rrtmgp-nn-training </a>on the main branch on Github; an archived version is also included here (rte-rrtmgp-nn-2.0.zip). See the readme in the above sub-directory for further information.

opencc-by-4.0Jul 2022View details →

Data for: Reconstructing Cosmological Initial Conditions from Late-Time Structure with Convolutional Neural Networks

Trained models and evaluation data for the revised submitted paper "Reconstructing Cosmological Initial Conditions from Late-Time Structure with Convolutional Neural Networks," Christopher J. Shallue & Daniel J. Eisenstein (2022)

opencc-by-4.0Feb 2023View details →

Data and code for "Representing storylines with causal networks to support decision making: framework and example"

Data and code for the paper "Representing storylines with causal networks to support decision making: framework and example", along with the Shiny webapp code accompanying the paper. The paper has been submitted to the journal of Climate Risk Management and is currently under review.

opencc-zeroFeb 2023View details →

Data for: Prescribed fire increases plant-pollinator network robustness to losses of rare native forbs

Restoration efforts often focus on changing the composition and structure of invaded plant communities, with two implicit assumptions: 1) functional interactions with species of other trophic levels, such as pollinators, will reassemble automatically when native plant diversity is restored; and 2) restored communities will be more resilient to future stressors. However, the impact of restoration activities on pollinator richness, plant-pollinator interaction network structure, and network robustness is incompletely understood. Leveraging a restoration chronosequence in Pacific Northwest prairies, we examined the effects of restoration-focused prescribed fire and native forb replanting on floral resources, pollinator visitation, and plant-pollinator network structure. We then simulated the effects of plant species loss/removal scenarios on secondary extinction cascades in the networks. Specifically, we explored three management-relevant plant loss scenarios (removal of an abundant exotic forb, removal of an abundant forb designated a noxious weed, and loss of the rarest native forb) and compared them to control scenarios. Pyrodiversity, proportion of area recently burned, and cumulative replanting effort (plugging and seeding) over the prior 10 years increased the abundance and diversity of floral resources, with concomitant increases in pollinator visitation and diversity. Pyrodiversity also decreased network connectance and nestedness, increased modularity, and buffered networks against secondary extinction cascades. Rare forbs contributed disproportionately to network robustness in less restored prairies, while removal of typical "problem" plants like exotic and noxious species had relatively small impacts on network robustness, particularly in prairies with a long history of restoration activities. Restoration actions aimed mainly at improving the diversity and abundance of pollinator-provisioning plants may also produce plant-pollinator networks with increased resilience to plant species losses.

opencc-zeroMar 2023View details →

Data and code for: Generation and applications of simulated datasets to integrate social network and demographic analyses

Social networks are tied to population dynamics; interactions are driven by population density and demographic structure, while social relationships can be key determinants of survival and reproductive success. However, difficulties integrating models used in demography and network analysis have limited research at this interface. We introduce the R package genNetDem for simulating integrated network-demographic datasets. It can be used to create longitudinal social networks and/or capture-recapture datasets with known properties. It incorporates the ability to generate populations and their social networks, generate grouping events using these networks, simulate social network effects on individual survival, and flexibly sample these longitudinal datasets of social associations. By generating co-capture data with known statistical relationships it provides functionality for methodological research. We demonstrate its use with case studies testing how imputation and sampling design influence the success of adding network traits to conventional Cormack-Jolly-Seber (CJS) models. We show that incorporating social network effects in CJS models generates qualitatively accurate results, but with downward-biased parameter estimates when network position influences survival. Biases are greater when fewer interactions are sampled or fewer individuals are observed in each interaction. While our results indicate the potential of incorporating social effects within demographic models, they show that imputing missing network measures alone is insufficient to accurately estimate social effects on survival, pointing to the importance of incorporating network imputation approaches. genNetDem provides a flexible tool to aid these methodological advancements and help researchers test other sampling considerations in social network studies.

opencc-by-4.0Mar 2023View details →

Data for "Structure and drivers of social networks and their links with health in older adults"

Data, supplementary material and scripts for the paper "Structure and drivers of social networks and their links with health in older adults" Social network is an important factor in promoting healthy aging. However, the mechanisms linking social capital to health are complex. Moreover, most of the social network analysis studies on older adults consider only participants’ relationships and not how these relationships are themselves connected. In this study, we went further than current ego-centered network studies by determining global social network metrics and the structure of relationships among older adult participants of the RECORD Cohort using the Veritas-Social questionnaire. The aim of this study is to identify key dimensions of social networks of older adults, and to evaluate how these dimensions relate to depressive symptoms, life satisfaction, and well-being. Using Principal Component Analyses (PCA), we identified four social network dimensions with psychological meanings. Dimension 1 (homophily) was positively linked with perceived accessibility to services in one’s residential neighborhood but negatively linked with the level of study. Dimension 2 (social integration) as Dimension 3 (social support) was only linked to the number of people living with ego. Dimension 4 was linked with perceived accessibility to local services. Finally, and rather surprisingly, we found that none of the four network dimensions, even the degree, was linked to the three health status metrics.

opencc-zeroApr 2023View details →

Data for: Fishing triggers trophic cascade in terms of variation, not abundance, in an allometric trophic network model

Trophic cascade studies often rely on linear food chains instead of complex food webs and are typically measured as biomass averages, not as biomass variation. We study trophic cascades propagating across a complex food web including a measure of biomass variation in addition to biomass average. We examined whether different fishing strategies induce trophic cascades and whether the cascades differ from each other. We utilized an allometric trophic network (ATN) model to mechanistically study fishing-induced changes in food web dynamics. Different fishing strategies did not trigger traditional, reciprocal trophic cascades, as measured in biomass averages. Instead, fishing triggered a variation cascade that propagated across the food web, including fish, zooplankton and phytoplankton species. In fisheries that removed a large amount of top-predatory and cannibalistic fish, the biomass oscillations started to decrease after fishing was started. In fisheries that mainly targeted large planktivorous fish, the biomass oscillations did not dampen but slightly increased over time. Removing species with specific ecological functions might alter the food web dynamics and potentially affect the ecological resilience of aquatic ecosystems.

opencc-by-4.0Apr 2023View details →

Supplementary Data for "Prediction of solar wind speed by applying convolutional neural network to potential field source surface (PFSS) magnetograms"

These are supplementary data for the paper "Prediction of solar wind speed by applying convolutional neural network to potential field source surface (PFSS) magnetograms". They are: - Python code to construct a neural network model - Saved optimal models (for 8-fold validation) - Selected y-label data (solar wind speed) and corresponding dates, which we eliminate the data identified as ICME

opencc-zeroDec 2022View details →

Data from: Network structure of avian mixed-species flocks decays with elevation and latitude across the Andes

Birds in mixed-species flocks benefit from greater foraging efficiency and reduced predation but also face costs related to competition and activity matching. Because this cost-benefit trade-off is context-dependent (e.g., abiotic conditions, habitat quality), the structure of flocks is expected to vary along elevational, latitudinal, and disturbance gradients. Specifically, we predicted that the connectivity and cohesion of flocking networks would (1) decline towards tropical latitudes and lower elevations, where competition and activity matching costs are higher, and (2) increase with lower forest cover and greater human disturbance. We analysed the structure of 84 flock networks across the Andes and assessed the effect of elevation, latitude, forest cover and human disturbance on network characteristics. We found that Andean flocks are overall open-membership systems (unstructured), though the extent of network structure varied across gradients. Elevation was the main predictor of structure, with more connected and less modular flocks upslope. As expected, flocks in areas with higher forest cover were less cohesive, with better-defined flock subtypes. Flocks also varied across latitude and disturbance gradients as predicted, but effect sizes were small. Our findings indicate that the unstructured nature of Andean flocks might arise as a strategy to cope with harsh environmental conditions.

Data for: Patterns of species diversity in a network of artificial wetlands

Aim Artificial island habitats such as human-made wetlands are emerging novel ecosystems. Understanding the drivers of diversity in such artificial systems is essential for balancing the goals of biodiversity conservation and human socio-economic needs. Location Telangana State, India. Methods We surveyed water birds in a network of 57 artificial wetlands and assessed four macroecological biodiversity patterns: spatial beta diversity, temporal beta diversity, species-abundance distributions (SADs), and the species–area relationship (SAR). We employed a mix of phenomenological and mechanistic models to examine the four macro-ecological patterns. We hypothesised that the wetland bird communities are primarily structured by immigration–extinction dynamics and thus that spatial and temporal beta diversity would be high, the within-wetland SADs would exhibit a large number of rare species and a monotonically declining overall shape, and that the SAR across wetlands would be strongly increasing. Results Spatial and temporal beta diversity were both high and mostly attributable to turnover rather than nestedness. While the pooled SAD exhibited an interior mode, the SAD for individual wetlands was generally log-series distributed, consistent with a model in which immigration among wetlands is high. The SAR exhibited an increasing trend, with the "small-island effect", which reflects constraints on immigration and is often observed for true island archipelagos, being absent. Main Conclusions We tentatively conclude that bird diversity in this network of artificial wetlands is mainly structured by immigration–extinction dynamics, although we acknowledge that some of the patterns are also consistent with niche dynamics and future research should measure relevant biotic and abiotic variables in these wetlands. We encourage future work in which our rich data set is used to fit dynamic models that permit more detailed quantitative inferences about mechanisms structuring diversity in this novel ecosystem, which can ultimately also inform conservation management.

Data from: The fat body cortical actin network regulates Drosophila inter-organ nutrient trafficking, signaling, and adipocyte cell size

Defective nutrient storage and adipocyte enlargement (hypertrophy) are emerging features of metabolic syndrome and type 2 diabetes. How the cytoskeletal network contributes to nutrient uptake, fat storage, and adipocyte size remains poorly understood. Utilizing the Drosophila larval fat body (FB) as a model adipose tissue, we show that a specific actin isoform—Act5C—forms the cortical actin network necessary for inter-organ lipid trafficking. Act5C also promotes FB tissue expansion during larval development so larvae can store sufficient biomass for metamorphosis. We find FB-specific loss of Act5C, but not other Drosophila actins, perturbs FB triglyceride (TG) storage in lipid droplets (LDs), resulting in developmentally delayed larvae that fail to develop into flies. Act5C localizes to the FB cell surface where it intimately contacts peripheral LDs (pLDs), forming a cortical actin network together with spectrins for cell architectural support. While both the cortical actin and spectrin cytoskeletons maintain FB cell surface architecture, we find that only the actin network is required for fat storage. Mechanistically, we show that FBs lacking the Act5C cortical cytoskeleton exhibit a block in lipoprotein (Lpp) secretion from FB cells, and a subsequent disruption of gut:FB inter-organ lipid transport, resulting in mid-gut fat accumulation. Utilizing temporal RNAi-depletion approaches, we also reveal that Act5C is indispensable post-embryogenesis during larval feeding to promote FB cell expansion. Act5C-deficient FBs fail to expand cell sizes, leading to lipodystrophic larvae unable to accrue sufficient biomass for metamorphosis. Collectively, we propose that the Act5C-mediated cortical actin network of Drosophila adipose tissue plays an essential role in post-embryonic inter-organ nutrient transport and FB cell size determination for organismal energy homeostasis and development.

opencc-by-4.0May 2023View details →

Data supporting the publication "Quadrature nonreciprocity in bosonic networks without breaking time-reversal symmetry"

Data supporting the publication "Quadrature nonreciprocity in bosonic networks without breaking time-reversal symmetry"

Data from: Task-evoked metabolic demands of the posteromedial default mode network are shaped by dorsal attention and frontoparietal control networks

External tasks evoke characteristic fMRI BOLD signal deactivations in the default mode network (DMN). However, for the corresponding metabolic glucose demands both decreases and increases have been reported. To resolve this discrepancy, functional PET/MRI data from 50 healthy subjects performing Tetris® were combined with previously published data sets of working memory, visual and motor stimulation. We show that the glucose metabolism of the posteromedial DMN is dependent on the metabolic demands of the correspondingly engaged task-positive networks. Specifically, the dorsal attention and frontoparietal network shape the glucose metabolism of the posteromedial DMN in opposing directions. While tasks that mainly require an external focus of attention lead to a consistent downregulation of both metabolism and the BOLD signal in the posteromedial DMN, cognitive control during working memory requires a metabolically expensive BOLD suppression. This indicates that two types of BOLD deactivations with different oxygen-to-glucose index may occur in this region. We further speculate that consistent downregulation of the two signals is mediated by decreased glutamate signaling, while divergence may be subject to active GABAergic inhibition. The results demonstrate that the DMN relates to cognitive processing in a flexible manner and does not always act as a cohesive task-negative network in isolation.

Social network and fitness data from age-structured populations of forked fungus beetles

We investigated the relationships between age, social behavior, and fitness at three levels of organization: the individual, the local social environment, and the population. Replicate groups of forked fungus beetles (Bolitotherus cornutus) were engineered to have either young- or old- biased age structures, and both social and reproductive behaviors were recorded.

opencc-by-4.0May 2023View details →

Data of "Multilayer spintronic neural networks with radio-frequency connections"

This dataset corresponds to the open data of the publication "Multilayer spintronic neural networks with radio-frequency connections".

opencc-by-4.0May 2023View details →

Reproducibility Package (Raw Data) for Predictive Limitations of Physics-Informed Neural Networks in Vortex Shedding

Raw data results from the simulations using PINN methods and PetIBM for the paper at: https://github.com/barbagroup/jcs_paper_pinn