Find research datasets worth reusing

opencc-by-4.0Feb 2019View details →

MiRoR5 - P1 - A scoping review provided a framework for new ways of doing research through mobilizing collective intelligence

Data of scoping review on methods of mobilizing collective intelligence includes list of included articles, data extraction form, spreadsheet of data extracted and R script for data analysis

opencc-by-4.0Mar 2020View details →

CCoDaMiC: A framework for Coherent Coordination of Data Migration and Computation platforms

This dataset release supports the results presented in the paper Chinmaya Kumar Dehury, Satish Narayana Srirama, Tek Raj Chhetri, CCoDaMiC: A Framework for Coherent Coordination of Data Migration and Computation Platforms. Future Generation Computer Systems URL: https://www.sciencedirect.com/science/article/pii/S0167739X19330924

opencc-by-4.0Nov 2019View details →

Supplementary Data for "Tuning the Redox Activity of Metal–Organic Frameworks for Enhanced, Selective O2 Binding: Design Rules and Ambient Temperature O2 Chemisorption in a Cobalt–Triazolate Framework"

Supplementary dataset to support "Tuning the Redox Activity of Metal–Organic Frameworks for Enhanced, Selective O2 Binding: Design Rules and Ambient Temperature O2 Chemisorption in a Cobalt–Triazolate Framework"

opencc-by-4.0May 2020View details →

BigFuzz: Efficient Fuzz Testing for Data Analytics using Framework Abstraction

BigFuzz supplementary material.

openother-openJun 2020View details →

Data and Code Accompanying the Study "Developing an annotation framework for word formation processes in comparative linguistics"

Cite the source of the dataset as: <blockquote> Schweikhard, N. E. and List, J.-M. (2020): Developing an annotation framework for word formation processes in comparative linguistics. SKASE Journal of Theoretical Linguistics. 17.1: 2-26. </blockquote>

opencc-by-4.0Dec 2019View details →

PyGNA: a unified framework for geneset network analysis

Input data and results for the manuscript "PyGNA: a unified framework for geneset network analysis".  Manifest files describe the content of each file.

Data from: A framework for the integrated analysis of the magnitude, selectivity, and biotic effects of extinction and origination

The taxonomic and ecologic composition of Earth's biota has shifted dramatically through geologic time, with some clades going extinct while others diversified. Here, we derive a metric that quantifies the change in biotic composition due to extinction or origination and show that it equals the product of extinction/origination magnitude and selectivity (variation in magnitude among groups). We also define metrics that describe the extent to which a recovery (1) reinforced or reversed the effects of extinction on biotic composition and (2) changed composition in ways uncorrelated with the extinction. To demonstrate the approach, we analyzed an updated compilation of stratigraphic ranges of marine animal genera. We show that mass extinctions were not more selective than background intervals at the phylum level; rather, they tended to drive greater taxonomic change due to their higher magnitudes. Mass extinctions did not represent a separate class of events with respect to either strength of selectivity or effect. Similar observations apply to origination during recoveries from mass extinctions, and on average, extinction and origination were similarly selective and drove similar amounts of biotic change. Elevated origination during recoveries drove bursts of compositional change that varied considerably in effect. In some cases, origination partially reversed the effects of extinction, returning the biota towards the pre-extinction composition; in others, it reinforced the effects of the extinction, magnifying biotic change. Recoveries were as important as extinction events in shaping the marine biota, and their selectivity deserves systematic study alongside that of extinction.

opencc-by-4.0Jul 2020View details →

CGRE Framework Dataset - A Dataset automatically generated to evaluate OCR Software on Webdocuments

Description The provided dataset was generated by the <a href="https://github.com/Drizzy3D/CGRE">CGRE Framework.</a> It was generated as a part of a bachelor thesis and used to evaluate the Tesseract OCR Software on webdocuments. CGRE_dataset.zip: 1. crawl.json This file contains crawling results from the alexa.com Top 50 most used webpages in the US from the 7th June 2020. The crawling was done specifically for styling information only. 2. html The generated webdocuments can be found in this directory. They are based on the crawled styling information. The levels of the directory are used to store the different  styling attributes. Every directory is named by the used value for a specific styling attribute. Every word is placed in a span html element. 3. dataset The rendered webdocuments can be found in this directory as png files. They were rendered using the Chromium Embedded Framework (CEF) and contain corresponding labels. The labels are in the same directory with the same name as the corresponding rendered webdocument, just as txt files. The labels contain "word\t(left,top,width,height)\n" lines. "(left,top,width,height)" is the bounding box of a span element containing a word. "word" is the word in the bounding box. 4. dataset_tesseract_complete This directory contains the Tesseract results on the dataset as txt files. The structure is analogue to the dataset. The txt files contain analogue to the dataset "word\t(left,top,width,height)\n" lines. 5. evaluation The results of the evaluation of Tesseract on the dataset. To evaluate the localisation of words by Tesseract, the Intersection Over Union metric was used, with different threshold values (0.5, 0.6, 0.7, 0.8, 0.9). To evaluate the determination of words by Tesseract, a normalized Levenshtein distance metric was used, with different threshold values (0.5, 0.6, 0.7, 0.8, 0.9). The times were measured by using this system: Ubuntu 20.04, AMD Ryzen 5 1600 CPU, AMD Radeon RX Vega 56 GPU, 16 GB DDR4 RAM with 2400 MHz The different threshold values are stored in the filenames. You can find the results in the csv files. Every line contains the results for a specific webdocument. The txt files contain calculated precision and recall values.

opencc-by-4.0Aug 2020View details →

Interaction Framework within Collaborative Virtual Environments for Multiple Users each interacting with Multiple Degrees-Of-Freedom Controllers

Collaboration is a process in which two or more agents work together to achieve shared goals. However, many existing platforms cannot generate a collaborative environment to engage multiple users with multiple controllers in a seamless manner. To address this need, this video and work in progress will describe LISU (Library for Interactive Settings and User-modes) an input management computing framework that enables collaboration across multiple input controllers as its default. Within the system team members cohabit any real-time simulation environments simultaneously and are then able to jointly control visualisation software across multiple controllers while being continually monitored and evaluated at a low level, allowing research questions to be answered.

opencc-zeroAug 2020View details →

An effect size statistical framework for investigating sexual dimorphism in non-avian dinosaurs and other extinct taxa

Despite reports of sexual dimorphism in extinct taxa, such claims in non-avian dinosaurs have been underrepresented recently (~the last decade) and often criticized. Since dimorphism is widespread in sexually reproducing organisms today, underrepresentation might suggest either methodological shortcomings or that this diverse group exhibited highly unusual reproductive biology. Univariate significance testing, especially for bimodality, is ineffective and prone to false negatives. Species recognition and mutual sexual selection hypotheses, therefore, may not be required to explain supposed absence of sexual dimorphism across the grade, likely a type II error. Instead, multiple lines of evidence support sexual selection and variation of structures consistent with secondary sexual characteristics, strongly suggesting sexual dimorphism in non-avian dinosaurs. We propose a framework for studying sexual dimorphism in fossils, focusing on likely secondarily sexual traits and testing against all alternate hypotheses for variation in them using multiple lines of evidence. We use effect size statistics appropriate for low sample sizes, rather than significance testing, to analyze potential divergence of growth curves in traits and constrain estimates for dimorphism magnitude. In many cases, estimates of sexual variation can be reasonably accurate, and further developments in methods to improve sex assignments and account for intrasexual variation (e.g., mixture modelling) will improve accuracy. It is better to compare estimates for the magnitude of and support for dimorphism between datasets than to dichotomously reject or fail to reject monomorphism in a single species, enabling the study of sexual selection across phylogenies and time. We defend our approach with simulated and empirical data, including dinosaur data, showing that even simple approaches can yield fairly accurate estimates of sexual variation in many cases, allowing for comparison of species with high and low support for sexual variation.

opencc-zeroAug 2020View details →

Data from: Framework for quantifying population responses to disturbance reveals that coastal birds are highly resilient to hurricanes

Changes in the frequency and severity of extreme weather may introduce new threats to species that are already under stress from gradual habitat loss and climate change. We provide a probabilistic framework that quantifies potential threats by applying concepts from ecological resilience to single populations. Our approach uses computation to compare disturbance-impacted projections to a population's normal range of variation, quantifying the full range of potential impacts. We illustrate this framework with projection models for coastal birds, which are commonly depicted as vulnerable to disturbances, especially hurricanes and oil spills. We found that populations of coastal specialists are resilient to extreme disturbances, with high resistance to the effects of short-term reductions in vital rates and recovery within 20 years. Applying the general framework presented here across disturbance-prone species and ecosystems would improve understanding of population resilience and generate specific projections of resilience that are needed for effective conservation planning.

opencc-by-4.0Apr 2000View details →

The Emergency Conceptual Framework Big Picture

The Emergency System Conceptual Framework Big Picture gives an insight to better manage and plan for different emergencies (Accidents, Incidents, Crisis, Disasters, Catastrophes).

opencc-zeroAug 2020View details →

A multi-state occupancy modeling framework for robust estimation of disease prevalence in multi-tissue disease systems

1. Given the public health, economic, and conservation implications of zoonotic diseases, their effective surveillance is of paramount importance. The traditional approach to estimating pathogen prevalence as the proportion of infected individuals in the population is biased because it fails to account for imperfect detection. A statistically robust way to reduce bias in prevalence estimates is to obtain repeated samples (or sample many tissues in multi-tissue disease systems) and to apply statistical methods that account for imperfect detection and permit the interdependence of the infection process across multiple tissues. 2. We developed a multi-state occupancy modeling framework which considers two scenarios about the infection process, one where no assumptions about the dependencies among the tissues are made (general), and another where dependence among tissues is not permitted (constrained). 3. We applied this model to pseudorabies virus (PrV) DNA detection data obtained from whole blood; and oral, nasal, and genital mucosa of 510 feral swine (Sus scrofa) during the years 2014-2016 in Florida, USA. 4. The constrained model was better supported by data. Estimated PrV prevalence varied among tissues, ranging from to 0.06 (CI: 0.02-0.14) in genital to 0.54 (CI: 0.14-0.82) in nasal tissue. Probability of PrV detection ranged from 0.11 (CI: 0.06-0.18) in nasal to 0.51 (CI: 0.21-0.81) in genital tissue. Estimates of PrV prevalence after accounting for imperfect detection were higher than the naïve estimates for all four tissues. 5. PrV prevalence was not affected by the age or sex of the animal or the year of sampling, but prevalence increased as drought severity increased. 6. The conditional probability of detecting PrV given infection in at least one tissue type within an individual was highest for nasal tissue, suggesting that nasal is the best tissue to sample for PrV surveillance if only one tissue can be sampled, at least for systems with tissue-specific prevalence and detection probabilities similar to ours. 7. We found that pathogen prevalence in multi-tissue disease systems can vary across tissues. Our results emphasize the importance of sampling multiple tissues, and the application of robust statistical models to account for imperfect detection in the surveillance of systemic diseases. The multi-state modeling framework is broadly applicable to the surveillance of pathogens that infect multiple tissues and where the infection status or detection of the pathogen in one tissue may depend on the infection status of the pathogen in other tissues). 29-Jul-2020

A minimal yet flexible likelihood framework to assess correlated evolution

An evolutionary process is reflected in the sequence of changes through time of any trait (e.g. morphological, molecular). Yet, a better understanding of evolution would be procured by characterizing correlated evolution, or when two or more evolutionary processes interact. A wide range of parametric methods have previously been proposed to detect correlated evolution but they often require significant computing time as they rely on the estimation of many parameters. Here we propose a minimal likelihood framework modelling the joint evolution of two traits on a known phylogenetic tree. The type and strength of correlated evolution is characterized by few parameters tuning mutation rates of each trait and interdependencies between these rates. The framework can be applied to study any discrete trait or character ranging from nucleotide substitution to gain or loss of a biological function. More specifically, it can be used to 1) test for independence between two evolutionary processes, 2) identify the type of interaction between them and 3) estimate parameter values of the most likely model of interaction. In its current implementation, the method takes as input a phylogenetic tree together with mapped discrete evolutionary events on it and then maximizes the likelihood for one or several chosen scenarios. The strengths and limits of the method, as well as its relative power when compared to a few other methods, are assessed using both simulations and data from 16S rRNA sequences in a sample of 54 γ-enterobacteria. We show that even with datasets of less than 100 species, the method performs well in parameter estimation and in the selection of evolutionary scenario.

Data from: Surviving drought: a framework for understanding animal responses to small rain events in the arid-zone

Large rain events drive dramatic resource pulses and the complex pulse-reserve dynamics of arid ecosystem changes between high-rain years and drought. However, arid-zone animal responses to short-term changes in climate are unknown, particularly smaller rain events that briefly interrupt longer-term drought. Using arthropods as model animals, we determined the effects of a small rain event on arthropod abundance in western NSW, Australia during a longer-term shift towards drought. Arthropod abundance decreased over two years, but captures of ten out of fifteen ordinal groups increased dramatically after the small rain event (<40mm). The magnitude of increases ranged from 10.4 million% (collembolans) to 81% (spiders). After three months, most groups returned to pre-rain abundance. However, small soil-dwelling beetles, mites, spiders, and collembolans retained high abundances despite the onset of winter temperatures and lack of subsequent rain. As predicted by pulse-reserve models, most arid-zone arthropod populations declined during drought. However, small rain events may play a role in buffering some groups from declines during longer-term drought or other xenobiotic influences. We outline the framework for a new model of animal responses to environmental conditions in the arid zone, as some species clearly benefit from rain inputs that do not dramatically influence primary productivity.

opencc-by-4.0Dec 2019View details →

Hierarchically Porous Reduced Graphene Oxide Coated with Metal-Organic Framework HKUST-1 for Enhanced Hydrogen Gas Affinity

Metal organic frameworks (MOFs) are crystalline porous materials with interconnected pores and have been actively explored for various gas storage, separation and conversion applications due to their structural tunability. While the micropores (<2 nm) in MOFs are essential for increased gas affinity, these small pores significantly decrease the mass transport kinetics. One way to address this challenge is to develop hierarchically porous MOFs with interconnected micro-, meso- and macropores. Whereas these MOFs can be formed by using soft/hard templates or by creating pores through post-modification, it can also be achieved by growing MOFs on structural templates such as porous carbons i.e., reduced graphene oxide. The latter strategy can enable the introduction of hierarchical porosity, while creating a synergistic effect to simultaneously improve both mechanical property and gas affinity by creating pores at the interface. In this direction, we demonstrated that the coating of HKUST-1 onto a porous reduced graphene oxide (HRGO) led to the formation of a hierarchically porous structure, namely, HKUST-1@HRGO with increased affinity towards H2 gas. While the isosteric heats of adsorption (Qst) values for H2 were found to be 7.7, 6.9 and 6.7 kJ mol-1 for HRGO, HKUST-1 and the physical mixture of HKUST-1 and HRGO, respectively, at zero coverage, that of HKUST-1@HRGO composite revealed a significant increase up to 9.26 kJ mol-1 , thus clearly demonstrating not only the synergetic effect between HKUST-1 and the reduced graphene oxide and also the critical role interfacial pores as high affinity binding sites.

opencc-by-4.0Jan 2020View details →

Metrics Literacies research project mapped to Knowledge two Action (K2A) framework

Schematic representation of the Metrics Literacies research project mapped onto the Knowledge to Action (K2A) framework  Based on K2A framework proposed by: Wilson, K. M., Brady, T. J., Lesesne, C., & NCCDPHP Work Group on Translation. (2011). An organizing framework for translation in public health: The Knowledge to Action Framework. Preventing Chronic Disease, 8(2), A46. PMID: 21324260

opencc-by-4.0Sep 2020View details →

Retrofitting coal-fired power plants with biomass co-firing and CCS for net zero carbon emission: A plant-by-plant assessment based on GIS-LCA framework

Dataset for "Retrofitting coal-fired power plants with biomass co-firing and CCS for net zero carbon emission: A plant-by-plant assessment based on GIS-LCA framework"

Data from: A novel longitudinal framework aimed at improving the teaching of the neurological examination

Objective: To develop an educational framework basis for improving the teaching of the neurological examination (NE) by asking German neurologists to (i) identify the basic elements of the screening NE, and (ii) nominate the steps they would deem mandatory for medical students to master. Methods: We conducted a questionnaire-based survey among neurologists working in a hospital or ambulatory setting in southwest Germany. To define the screening NE, neurologists were asked to list the NE components they normally use in clinical encounters with patients in whom neurological findings are unlikely. Furthermore, they were asked to identify additional elements of the NE which they would consider mandatory for students to master. Results: Our neurologists nominated a set of 23 elements as being essential for a screening NE. There was high consensus amongst the two groups and the results were concordant with international data. Furthermore, nearly 60 additional maneuvers of the NE were deemed obligatory for students to master. Conclusion: Our results reinforce the international consensus for screening NE components, and confirm a large set of additional examination steps that medical students should master, thereby indicating the need for an educational NE teaching concept. To solve this educational challenge, we propose a longitudinal curriculum that incorporates the "core + clusters" framework, thus combining the screening NE (core) with hypothesis-driven sets of maneuvers (clusters). Based on our data, we provide an initial proposal for the core and neurological diagnostic clusters which is applicable to both novice as well as advanced learners across the continuum of training.