Find research datasets worth reusing

opencc-by-4.0Apr 2022View details →

Data for: From pattern to process? Dual travelling waves, with contrasting propagation speeds, best describe a self-organised spatio-temporal pattern in population growth of a cyclic rodent

Centroid data used for the analysis in Roos et al. Eco Lett. Transects, up to 99 m in length (dependent on the field's length), were surveyed in linear stable landscape features (field, track or ditch margins) to estimate vole abundance from November 2011 until September 2017. Each transect was divided into 3 m sections (33 in total) and the presence or absence of one or more signs of vole activity (i.e., latrines by burrows, fresh vegetation clippings, and recent burrow excavations) in each section was noted. The proportion of sections with signs of vole presence per transect was then used as the abundance index. The number of surveys carried out at any time varied adaptively with the perceived risk of an outbreak (according to changes in estimated abundance in previous monitoring surveys). The response variable typically used in all models is proportional growth rate (r_{t,i}, where  is the abundance index for site  at time  (Royama 1992; Berryman 2002). A benefit of using r_{t,i}, rather than ln(N_{t,i}), is that any multiplicative effects of site quality are cancelled out, provided they are constant over time. To calculate r_{t,i}, vole abundance indices are required at the same location in successive time periods (i.e., N_{t,i} and N_{t+1,i}). Given that exact transect locations were rarely reused in successive months, and all transect measurements took place throughout the year rather than discrete seasons, the data had to be aggregated to consistent locations and times to allow growth rate to be calculated.  As such, transects were temporally aggregated into a respective yearly quarter (e.g., January to March 2014). Transects were spatially aggregated by sequentially selecting an unassigned transect as a reference point for the ith centroid and assigning all unassigned transects within a 5 km radius to the ith  centroid, and repeating until all transects had been allocated (see Figure 2 for a summary of the number of transects assigned to each centroid, centroid locations, and time series of growth rate of each centroid). Once complete, the mean Julian day, X and Y UTM (Universal Transverse Mercator) and the mean index was calculated for all transects assigned to each centroid  for each time period. Where a centroid had successive values of N_{t,i} and N_{t+1,i} available, the corresponding proportional growth rate was calculated. A constant of 3.03 was added to N_{t,i} to avoid zero entries (3.03 was the lowest non-zero value of N observed). The final dataset consisted of 3,751 observations.

opencc-by-4.0Jun 2024View details →

Community science approach reveals temporal and eutrophication-related spatial patterns in bladderwrack-associated invertebrate fauna

Data related to the "Community science approach reveals temporal and eutrophication-related spatial patterns in bladderwrack-associated invertebrate fauna" paper by Salo, Nieminen, Salovius-Laurén and Rinne published in Estuarine, Coastal and Shelf Science in 2024. <a href="https://doi.org/10.1016/j.ecss.2024.108822">https://doi.org/10.1016/j.ecss.2024.108822</a> The data describes the community data collected with the community science method described in the paper.

opencc-by-4.0Jul 2024View details →

Supplemental data for "Inequitable spatial and temporal patterns in the distribution of multiple environmental risks and benefits in Metro Vancouver"

DemoEnPoC2016.csv/DemoEnPoC2006.csv: This is a table including environmental and demographic (Census variables) data at postal code level for Metro Vancouver in the year 2006 and 2016. The environmental data (SO2 metrics, PM2.5 metrics, Calculated ozone metrics, NO2 data, NDVI metrics, and Canadian Active Living Environments Index (Can-ALE) indexed to DMTI Spatial Inc. postal codes) were extracted from CANUE (Canadian Urban Environmental Health Research Consortium). The demographic data is extracted from Canadian Census analyzer (https://datacentre.chass.utoronto.ca/), the deprivation index is downloaded from from the Institut national de santé publique du Québec (INSPQ).  DGRwithLable: This is the Dissemination Geographies Relationship File for the 2021 census year (Statistics Canada, 2021) with the lable of urban or rural, indicating which dissemination area (DA) is identified as urban and included in this study. The urban area is named as population certer.  Aggregation and SS Determination: This script contains code for: <ul> <li>Aggregating postal code level data to the Dissemination Area (DA) level.</li> <li>Eliminating rural DAs.</li> <li>Converting environmental data into ordinal categories using quartile and even break methods.</li> <li>Identifying sweet and sour spots for each DA based on these methods.</li> </ul> SSEJ Analysis: This script includes code for: <ul> <li>Creating violin and box plots to illustrate descriptive statistics of demographic groups across different environmental categories (sweet, sour, risky, and medium).</li> <li>Performing linear regression analyses between environmental categories and demographic variables.</li> </ul> SS Heatmap: This script comprises code for: <ul> <li>Summarizing the results of the linear regression analyses.</li> <li>Assessing changes in inequities among demographic groups between 2006 and 2016.</li> <li>Visualizing regression coefficients through heatmaps.</li> </ul>

opencc-by-4.0Jul 2024View details →

Two-time correlation function based on speckle patterns from x-ray photon correlation spectroscopy associated with "Intermittent cluster dynamics and temporal fractional diffusion in a bulk metallic glass" (scientific article published in Nature Communications, 2024)

This dataset consists of contrast data, i.e., the two-time correlation function, based on speckle patterns measured at the at the 8ID-E beamline of the Advanced Photon Source at Argonne National Laboratory. Experimental details are stated in the paper specified under "related work" and in the accompanying supplementary information. You are welcome to use this dataset in compliance with the CC BY 4.0 licence assigned to this dataset. Any questions regarding the data can be addressed to birte.riechers@bam.de who would also appreciate a note if you find the data useful. ____________________________________________________________________ The data consists of 32 text files in total, which correspond to the main and lower panel Figure 2 of the main publication.  30 of these text files are contrast data, which are named "contrast_DT250s_nn.text" wiith "nn" as the identifier of consecutive data sets going from 1 to 30. Each data set consists of p rows and q columns, DT250s denotes the time resolution of data points, which is 250 s along both row and column values. The data set called "Time_Contrast_1to30s.txt" states the start time in seconds of the first data point of each of the thirty contrast data set. The data set called "ScatteredIntensity.txt" states the scattered intensity at full time resolution, i.e. 2.5 s. The files are plain text files with the data points separated by "space" along rows and "new line" along columns.

opencc-by-4.0Nov 2020View details →

Database for "A new perspective for charactering the spatio-temporal patterns of the error in GPM IMERG over mainland China"

This file contains the dataset accompanying the manuscript '2020EA001232-TR' submitted to the ESS journal (https://earthandspacescience-submit.agu.org). Title: "A new perspective for charactering the spatio-temporal patterns of the error in GPM IMERG over mainland China" China Merged Precipitation Analysis data (CMPA, hourly, with the resolution of , as validation data) for China Mainland is available at website http://data.cma.cn. Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrieval data (IMERG, half-hourly, with the resolution of , as the observed data) is available at https://pmm.nasa.gov/data-access/downloads/gpm. The Shuttle Radar Topography Mission data (SRTM, with a 90-m spatial resolution) could be accessed at http://srtm.csi.cgiar.org.

opencc-by-4.0Feb 2017View details →

Synthetic Smart Card Data for the Analysis of Temporal and Spatial Patterns

This is a synthetic smart card data set that can be used to test pattern detection methods for the extraction of temporal and spatial data. The data set is tab seperated and based on a stylized travel pattern description for city of Utrecht in The Netherlands and is developed and used in Chapter 6 of the PhD Thesis of Paul Bouman. This dataset contains the following files: <ul> <li>journeys.tsv : the actual data set of synthetic smart card data</li> <li>utrecht.xml : the activity pattern definition that was used to randomly generate the synthethic smart card data</li> <li>validate.ref : a file derived from the activity pattern definition that can be used for validation purposes. It specifies which activity types occur at each location in the smart card data set.</li> </ul>

opencc-by-4.0Dec 2023View details →

Temporal Patterns and Trends in Corporate Donations Using PageRank and Node Similarity Graph Algorithm

Corporate donations wield considerable influence within political arenas, shaping policies and influencing decision-making processes. This study uses Neo4j, an advanced graph database tool, to explore a comprehensive company dataset, focusing on unraveling temporal patterns and evolving trends in corporate contributions. Visual representations, such as bar charts, reveal significant fluctuations in donations, indicating potential cyclic patterns occurring every six years. The study explores intricate relationships between donor entities and recipients, highlighting diverse donation patterns—both focused and widespread. The study's derived PageRank scores offer a comprehensive portrayal of the varying degrees of influence among diverse entities receiving donations within the network. Notably, the Conservative and Unionist Party emerges as the most prominent entity, boasting a striking score of 1.86, indicating a substantial influx of financial support likely to significantly shape its political endeavors. Despite a lower score of 0.62, the Labor Party still signifies a noteworthy level of financial backing, albeit less extensive than its counterpart. In contrast, the Liberal Democrats, The In Campaign Ltd, and Network for Animals Ltd exhibit comparatively restrained financial backing, warranting deeper investigation into the factors affecting their funding. Moreover, undisclosed findings regarding 170 similarity scores using Node Similarity algorithm disclose a prevalent similarity trend among entities, notably observed between Company 1 and Company 2, implying potential synergistic partnerships in donation-related endeavors. This high similarity often indicates shared values, highlighting prospects for collaborative initiatives or partnerships to augment positive impacts. Utilizing these insights supports the formulation of targeted donation strategies, circumventing donation redundancies, and ensuring optimal resource allocation for maximal societal benefit within specified sectors. Keywords—Company Dataset, Corporate Donations, Neo4j, Node Similarity, PageRank, Political Influence

opencc-by-4.0Mar 2022View details →

Time changes everything: A multispecies analyses of temporal patterns in evaporative water loss - data

The dataset was analysed in the manuscript “Žagar A., Carretero, M.A., de Groot M. (accepted) Time changes everything: A multispecies analyses of temporal patterns in evaporative water loss. Oecologia” The dataset consisted out of water loss by 23 populations of lizards from 16 different species and three families which was compiled from several different studies. All studies used the same standardized protocols. During the experiment every hour for 12 hours, the body weight of the lizard was measured (in total 13 measurements per lizard). The species name (SP), the snout-vent length of the animal (SVL, in millimetres), altitude (m a.s.l.), sampling location (site name, latitude and longitude), weight (in grams), sex (M=male, F=female), code of the individual lizard (CODE), date of experiment (DATE_H) and the reference of the study were noted down (full references are available in the manuscript). Per column the instantaneous water loss values (EWLi) were recorded per hour measured. First hour was EWLi8, second hour was EWLi9, etc. The EWLi was calculated by the weight minus the weight in the next hour divided by the weight multiplied by 100 ((Wn – Wn+1 / Wn) × 100).

opencc-by-4.0Nov 2003View details →

Fig. 4 in Temporal And Spatial Pattern Of Genetic Differentiation In Isophya Kraussi (Orthoptera: Tettigonoidea) In Ne Hungary

Fig. 4. Results of the PCA analysis for the two samples collected in the Mogyoróskuti meadows in 1999 and in 2001; i.e. temporalvariation within a population. The points represent the genotypic

opencc-by-4.0Nov 2003View details →

Fig. 3 in Temporal And Spatial Pattern Of Genetic Differentiation In Isophya Kraussi (Orthoptera: Tettigonoidea) In Ne Hungary

Fig. 3. Results of the PCA analysis for the three distinct populations; i.e. spatial variation (Karst region: Mogyoróskuti meadows, Haragistya; Zemplén Mts.: Gyertyánkúti meadows). The points represent

opencc-by-4.0Nov 2003View details →

Fig. 1 in Temporal And Spatial Pattern Of Genetic Differentiation In Isophya Kraussi (Orthoptera: Tettigonoidea) In Ne Hungary

Fig. 1. Sample sites. Aggtelek Karst region: Haragistya near Aggtelek (1), Mogyoróskuti meadows near Jósvafő (2); Zemplén Mts.: Gyertyánkúti meadows near Telkibánya (3)

Fig. 5. a in Local ecological knowledge of fishers about the life cycle and temporal patterns in the migration of mullet (Mugil liza) in Southern Brazil

Fig. 5. a) Whole muscular stomach (gizzard) and b) Opened gizzard, with sand and mud (in March), both of mullet (Mugil liza).

Fig. 3 in Local ecological knowledge of fishers about the life cycle and temporal patterns in the migration of mullet (Mugil liza) in Southern Brazil

Fig. 3. Percentage of the interviewed fishers (n=45) that cited the month when mullet exiting lagoons/estuaries ('criadouros') for migration, spawning and return. Some fishermen cited more than one month for each event, five did not knew about when spawning occurred and seven when mullets returned to the lagoons/estuaries.

Fig. 4 in Local ecological knowledge of fishers about the life cycle and temporal patterns in the migration of mullet (Mugil liza) in Southern Brazil

Fig. 4. Abdominal checking of mullet (Mugil liza) sex. a) Female: yellow eggs (n=27) through the urogenital orifice, and b) Male: white eggs/sperm (n=36) through the urogenital orifice.

Fig. 2 in Local ecological knowledge of fishers about the life cycle and temporal patterns in the migration of mullet (Mugil liza) in Southern Brazil

Fig. 2. The life cycle of the mullet Mugil liza following local ecological knowledge of fishers from Santa Catarina State: a) Exit of mullets from 'criadouros' or breeding sites (lagoons and estuaries) to the sea (n= 45); b) Migration of mullets known as 'corrida' (run) and recurrent gathering with smaller schools (schooling or thickening process). The outlined map represents the Santa Catarina State coastline and main stopping/fishing sites for mullets. Arrows corresponds to our data-collection sites, which were indicated as main fishing locations; c) Outline of Santa Catarina State island (Florianópolis city) and Bombinhas as most external (to the East) coastal areas and where larger captures of mullets occurs during the fishing season; d) Male and female spawning with respective milky ('ova leiteira') and yellowish ('ova amarela') gonads. According to most of our informants, after fecundation female mullets may hold their eggs under their scales until they become juvenile; e) Northward migration to São Paulo and Rio de Janeiro states, following by their (adults plus juveniles) southward return to lagoons and estuaries; f) Entrance of adult mullets and recruitment of juveniles in lagoons and estuaries; g) Growth and feeding of adults and juveniles in lagoons and estuaries.