cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/5wyauk
title: Revision of the comose flame moths of the genus Sosxetra Walker (Noctuidae, Dyopsinae), with descriptions of a new genus and three new species

description: This dataset contains the digitized treatments in Plazi based on the original journal article Martinez, Jose I., Homziak, Nicholas T., Pierson, Taylor L., Campo, Rhys J. L., Plotkin, David M., Castillo-Argaez, Raiza J. (2026): Revision of the comose flame moths of the genus Sosxetra Walker (Noctuidae, Dyopsinae), with descriptions of a new genus and three new species. ZooKeys 1268: 227-248, DOI: 10.3897/zookeys.1268.138260AbstractAs part of our Neotropical Dyopsinae Project, a revision of the Neotropical genus Sosxetra Walker is proposed. Morphological and molecular evidence challenge its previous monotypic classification. The genus is redescribed and a neotype is designated for Sosxetra grata Walker, previously considered the only species in the genus. Two new species are described: Sosxetra mamanina Martinez, Homziak, & Castillo-Argaez, sp. nov. and Sosxetra thutakanay Martinez, Homziak, & Castillo-Argaez, sp. nov. Finally, Covellana Martinez, Homziak, Plotkin & Castillo-Argaez, gen. nov., is established based on Covellana niomalan Martinez, Homziak, Plotkin & Castillo-Argaez, sp. nov., previously misidentified as Sosxetra grata.
DOI: 10.25314/8a9a45cf-7dfb-4180-adc3-5f33e5669415
title: Priority threat management for Pacific salmon conservation on the Central Coast of British Columbia: Expert Elicitation Data

description: These data, containing the estimated benefits of each conservation strategy for each Conservation Unit group (i.e. the probability that the CUs will be thriving in the next 20 years) were collected using the costs and feasibility of each conservation strategy designed for the Central Coast of British Columbia to conserve Pacific Salmon Conservation Units. Page 1 contains expert estimates of the probability that each CU group will be thriving (i.e. in the green status) in 2038, under each strategy. Please see README.txt for further information, including a description of strategies and variables. Data was collected through structured expert elicitation during two workshops in May and June 2018. The study area was the Central Coast of British Columbia, covering the traditional territories of the Heiltsuk, Nuxalk, Kitasoo/Xai'xais and Wuikinuxv Nations. Confidentiality declaration: All personal data are removed and only the summarized data across experts are provided. This dataset was originally deposited in the Simon Fraser University institutional repository.
DOI: 10.25314/e55f116a-a0a3-4504-a274-377803ea0ea0
title: Caveolae and scaffold detection from single molecule localization microscopy data

description: Caveolae are plasma membrane invaginations whose formation requires caveolin-1 (Cav1), the adaptor protein polymerase I, and the transcript release factor (PTRF or CAVIN1). Caveolae have an important role in cell functioning, signaling, and disease. In the absence of CAVIN1/PTRF, Cav1 forms non-caveolar membrane domains called scaffolds. In this work, we train machine learning models to automatically distinguish between caveolae and scaffolds from single molecule localization microscopy (SMLM) data. We apply machine and deep learning algorithms to discriminate biological structures from SMLM data. Our work is the first that is leveraging machine and deep learning approaches to automatically identifying biological structures from SMLM data. In particular, we develop and compare three binary classification methods to identify whether or not a given 3D cluster of Cav1 proteins is a caveolae. The first uses a random forest classifier applied to 28 hand-picked features, the second uses a convolutional neural net (CNN) applied to a projection of the point clouds onto three planes, and the third uses a PointNet model, a recent development that can directly take point clouds as its input. We validate our methods on a dataset of super-resolution microscopy images of PC3 prostate cancer cells labeled for Cav1. Specifically, we have images from two cell populations: 10 PC3 and 10 CAVIN1/PTRF-transfected PC3 cells (PC3-PTRF cells) that form caveolae. We obtained a balanced set of 1714 different cellular structures. Our results show that both the random forest on hand selected features and the deep learning approach achieve high accuracy in distinguishing the intrinsic features of the caveolae and non-caveolae biological structures. More specifically, both random forest and deep CNN classifiers achieve classification accuracy reaching 94% on our test set, while the PointNet model only reached 83% accuracy. We also discuss the pros and cons of the different approaches. Additional information about individual files is in the accompanying CSV file (item_metadata.csv). This dataset was originally deposited in the Simon Fraser University institutional repository.
DOI: 10.25314/367690f3-7987-4c10-82d0-72a7419632bd
title: Wastewater Regulations Database

description: This MS Access database contains details on various Acts and Regulations for several jurisdictions in North America that pertain to wastewater produced during hydraulic fracturing and shale gas production. The database was produced as part of Chapter 3 in Goss et al. (2015) Unconventional Wastewater Management: A Comparative Review and Analysis of Hydraulic Fracturing Wastewater Management Practices Across Four North American Basins. (http://www.cwn-rce.ca/reports/report/unconventional-wastewater-management-a-comparative-review-and-analysis-of-hydraulic-fracturing-wastewater-management-practices-across-four-north-american-basins). This dataset was originally deposited in the Simon Fraser University institutional repository.
DOI: 10.25314/5089ab2f-5583-4675-8484-8446c0d9a701
title: Precarity in Libraries - Partnership Job Postings

description: A spreadsheet of data collected and coded from the Partnership Job Board (https://partnershipjobs.ca/) Data was coded according to the following categories: job id (generated by researchers); date posted; date closed; job title institution; title; level of position (librarian/assistant/technician/manager/administrator/archivist/other); physical location (city, province/territory); type of institution (academic/public/government/school/other); type of position (part time (&lt;35 hours)/full time (35+ hours)); status of position (0-10 hours/week, 11-20 hours/week, 21-34 hours/week, 35+ hours/week, variable, not specified); type of position (regular/auxiliary or on-call); status of of position (temporary/ongoing); duration of position (Rounded to the nearest full month for durations expressed in weeks or specific dates, calculated based on days.); preferred/required education (Positions that explicitly mentioned recent graduates, and positions that listed years or months of experience as 'preferred' as opposed to required were coded as 0 years since there was explicitly no lower bound); minimum of experience; other related notes: This dataset was originally deposited in the Simon Fraser University institutional repository.
DOI: 10.25314/35954791-2754-47d7-893a-39430535dfdd
title: Inertial Measurement Unit Fall Detection Dataset

description: Inertial Measurement Unit Fall Detection Dataset (IMU Dataset) is a dataset devised to benchmark fall detection and prediction algorithms based on acceleration, angular velocity and magnetic fields of body-worn APDM Opal IMU sensors recording at 128 Hz at 7 body locations (right ankle, left ankle, right thigh, left thigh, head, sternum, and waist). Detailed description of the dataset and column names are in README.txt file. Use of this dataset in publications must be acknowledged by referencing the following publication: - Omar Aziz, Magnus Musngi, Edward J. Park, Greg Mori, Stephen N. Robinovitch. "A comparison of accuracy of fall detection algorithms (threshold-based vs. machine learning) using waist-mounted tri-axial accelerometer signals from a comprehensive set of falls and non-fall trials". SpringerLink Med Biol Eng Comput (2017) 55: 45. We also appreciate if you drop us an email (stever@sfu.ca and oaziz@sfu.ca) to inform us of any publication using this dataset, so we can point to your publication on our webpage. Format of data is tabular and content type is sensor data. Software used was Excel. Confidentiality declaration: The dataset does not contain personal identifiable information. All human subjects provided written consent prior to data collection. This dataset was originally deposited in the Simon Fraser University institutional repository.
DOI: 10.20383/101.0276
title: Atlas of the Fraser Canyons. River Dynamics Laboratory, Simon Fraser University

description: This Atlas compiles data on the geomorphic characteristics, morphology and flow dynamics through the 42 bedrock canyons of the Fraser River.
DOI: 10.20383/101.0277
title: Atlas of the Fraser Canyons Data Archive

description: This archive contains all the data used to produce the Atlas of the Fraser Canyons: Venditti, J.G. K. Fairweather, E. Kwoll, M. Wong, C.-Y.M. Lin, C.D. Rennie, M. Church (2020). Atlas of the Fraser Canyons. River Dynamics Laboratory, Simon Fraser University, 89 pages. doi:10.20383/101.0276
DOI: 10.25314/d3bb4e11-f158-4be2-a0a2-c39baffc19fd
title: Selective Attention and the Positivity Offset

description: Raw data for a project examining the cognitive underpinnings of the positivity offset. Confidentiality declaration: All subjects provided informed consent before participating. This dataset was originally deposited in the Simon Fraser University institutional repository.
DOI: 10.25314/0645dee2-f6b7-4371-9f3a-60b31ffcd2aa
title: Attention Capture by Trains and Faces in Children with and without Autism Spectrum Disorder

description: This study examined involuntary capture of attention, overt attention, and stimulus valence and arousal ratings, all factors that can contribute to potential attentional biases to face and train objects in children with and without autism spectrum disorder (ASD). In the visual domain, faces are particularly captivating, and are thought to have a 'special status' in the attentional system. Recent research suggests that similar attentional biases may exist for other classes of objects (e.g. birds), providing support for the role of exposure in attention prioritization. This research aimed to determine whether other classes of objects (i.e. trains) can capture attention similarly to what has been reported for faces. Children (6-14 years old) with and without ASD performed a visual search task where they indicated whether a target butterfly appeared amongst an array of face, train, and neutral distractors while their eye-movements were tracked. Content type is behavioural data and eye-tracking data. Software used was IBM SPSS Statistics 24.0. This dataset was originally deposited in the Simon Fraser University institutional repository.
DOI: 10.25314/98aeed01-3c5c-45a3-987c-cb7f73ef4202
title: Fraser River Gravel Sand Transition

description: This data archive contains data collected through the gravel-sand transition of the Fraser River. This dataset is composed of the 2007 Fraser GST Survey (Metadata_Fraser_GST_Topography_2007.zip) and the Fraser River Gravel Sand Transition Summary Figures (Summary_Figures_from_Venditti_et_al_2015_and_2019.xlsx).This dataset was originally deposited in the Simon Fraser University institutional repository.
DOI: 10.20383/101.0297
title: 3D Multicriteria Evaluation Dataset

description: The buildingrooms and New_5 shapefiles were derived from the City’s open data building footprint shapefiles to represent the base units for 1211 hypothetical residential units spanning 10 high-rise buildings in downtown Vancouver, British Columbia, Canada. Supporting geospatial data and ancillary information were used to conduct spatial analyses in ArcGIS and CityEngine software to calculate the attribute values for each unit for eight evaluation criteria: the proximity to parks, schools, water, and Skytrain stations, and view, duration of direct sunlight, noise and air pollution level. The eight criteria were combined using the proposed 3D multicriteria evaluation method to conduct a suitability analysis in a 3D environment to determine the overall level of suitability of each unit, under five alternative weighting scenarios including three based on the preferences of different ‘resident types’. CityEngine software was used to compute the overall suitability scores and create a 3D model of the urban residential units by extruding unit shapefiles to their height (here termed ‘voxelization’). These tasks were performed by writing rule files using Computer-Generated Architecture (CGA), CityEngine’s unique programming language. The rule files used to calculate the overall suitability scores under the five alternative weighting scenarios, as well as those used to investigate the suitability of each unit based on each individual criterion, are included in the repository as text files. The data files used to support the analysis are also included. These data were derived from the following publicly available resources: • Bbbike Extracts OpenStreetMap https://extract.bbbike.org/ Contains information licensed under the Open Data Commons Open Database License and following a fair usage policy • City of Vancouver Open Data Portal https://opendata.vancouver.ca/pages/home/ Contains information licensed under the Open Government Licence – Vancouver • City of Vancouver VanMap https://maps.vancouver.ca/portal/apps/sites/#/vanmap/ Contains information licensed under the Open Government Licence – Vancouver • Metro Vancouver Open Data Catalogue http://www.metrovancouver.org/data Contains information under the provisions of the Copyright Act for Metro Vancouver Regional District • OpenStreetMap https://www.openstreetmap.org/#map=2/71.3/-96.8 Contains information licensed under the Open Data Commons Open Database License • Statistics Canada https://www150.statcan.gc.ca/n1/en/catalogue/92-169-X Contains information licensed under the Statistics Canada Open License Agreement Any reuse or redistribution of the data must acknowledge the original data sources accordingly. As some sources prohibit data redistribution and publication, some of the geospatial data files used to conduct the research are not available.
DOI: 10.20383/101.0301
title: Newfoundland and Labrador climate index

description: The Newfoundland and Labrador (NL) climate index aims to describe the environmental conditions on the NL shelf and in the Northwest Atlantic as a whole. It consists of annual normalized anomalies of 10 subindices with equal contribution: Winter North Atlantic Oscillation, air temperature, sea ice, icebergs, sea surface temperature, vertically-averaged temperature and salinity at Station~27, cold intermediate layer (CIL) core temperature at Station~27, CIL area on 3 hydrographic sections and bottom temperature on the NL shelf. This index runs from 1951 to 2019 and will be updated annually. Data associated with Cyr, F. and Galbraith, P. S.: A climate index for the Newfoundland and Labrador shelf, Earth Syst. Sci. Data, 13, 1807–1828, https://doi.org/10.5194/essd-13-1807-2021, 2021.
DOI: 10.20383/101.0150
title: Fingerprinting of Quartzitic Outcrops at Olduvai Gorge, Tanzania

description: The African Early Stone Age record, including that of Olduvai Gorge, reveals widespread evidence for hominin exploitation of quartzose lithic raw materials such as quartzite. However, few studies have sought to characterize these rock types grounded on the assumption that they are not amenable for provenance studies. Through the use of macroscopic, petrographic, and EDXRF analysis, we characterize source material from five quartzitic outcrops belonging to the Mozambique Belt adjacent to Olduvai Gorge. Our results show that certain macroscopic varieties strictly occur at some outcrops while petrographic analyses reveal that accessory minerals may be outcrop-specific pending a greater sample size. Statistical interrogation of the geochemical data through linear correlations, ANOVA tests, and PCA, show that there are inter- and intra-outcrop differences, and elemental concentrations characteristic of certain outcrops. This multi-scalar approach provides a reproducible classificatory framework for future characterization studies and archaeological testing at Olduvai Gorge to shed light on hominin palaeoenvironmental exploitation and palaeoecological behavior.
DOI: 10.20383/101.0195
title: Data used for the analysis of dominant controls on evapotranspiration from the BERMS Old Jack Pine site, Saskatchewan

description: Land surface schemes can be applied to simulate evapotranspiration. This dataset contains the driving meteorological data, and various diagnostic data, from one of the Boreal Ecosystem Research and Monitoring Sites in central Saskatchewan, known as the Old Jack Pine site. In Nazarbakhsh et al. (2019, Hydrological Processes, https://doi.org/10.1002/hyp.13674) we used these data to drive two Canadian land surface schemes (CLASS and CLASS–CTEM). We used half–hourly values of shortwave radiation, longwave radiation, precipitation, air temperature, specific humidity, wind speed, and atmospheric pressure to drive the models. Flux tower estimates of evapotranspiration, with energy balance closure applied, were used to assess the performance of the models on daily and monthly timescales for years 2000 to 2010. We also used soil moisture (measured with Campbell Scientific CS615 probes, which measure liquid water content only) and soil temperature observations for years 2000 to 2010 to assess the models’ performance during the snowmelt and soil–thaw periods in the spring.
DOI: 10.20383/101.0193
title: Unmanned aerial vehicle structure from motion and lidar data for sub-canopy snow depth mapping

description: Unmanned Aerial Vehicles (UAV) have had recent widespread application to capture high resolution information on snow processes and the data herein was collected to address the sub-canopy snow depth challenge. Previous demonstrations of snow depth mapping with UAV Structure from Motion (SfM) and airborne-lidar have focused on non-vegetated surfaces or reported large errors in the presence of vegetation. In contrast, UAV-lidar systems have high-density point clouds, measure returns from a wide range of scan angles, and so have a greater likelihood of successfully sensing the sub-canopy snow depth. The effectiveness of UAV-lidar and UAV-SfM in mapping snow depth in both open and forested terrain was tested with data collected in a 2019 field campaign in the Canadian Rockies Hydrological Observatory, Alberta and at Canadian Prairie sites near Saskatoon, Saskatchewan, Canada. The data archived here comprises the raw point clouds from the UAV-SfM and UAV-lidar platforms, generated digital surface models, and survey data used for accuracy assessment for the field campaign in question as reported in Harder et al., 2019. This dataset was generated by the work of the Smart Water Systems Laboratory within the Centre for Hydrology at the University of Saskatchewan. This contributes to the objectives of a number of Pillar 3 Global Water Futures projects including Mountain Water Futures and the Transformative Technology and Smart Watersheds.
DOI: 10.20383/101.0111
title: A Bias-Corrected 3-hourly 0.125 Gridded Meteorological Forcing Data Set (1979 – 2016) for Land Surface Modeling in North America

description: Cold regions hydrology is very sensitive to the impacts of climate warming. Future warming is expected to increase the proportion of winter precipitation falling as rainfall. Snowpacks are expected to undergo less sublimation, form later and melt earlier and possibly more slowly, leading to earlier spring peak streamflow. More physically realistic and sophisticated hydrological models driven by reliable climate forcing can provide the capability to assess hydrologic responses to climate change. However, hydrological processes in cold regions involve complex phase changes and so are very sensitive to small biases in the driving meteorology, particularly temperature and precipitation. Cold regions often have sparse surface observations, particularly at high elevations that generate the major amount of runoff. The effects of mountain topography and high latitudes are not well reflected in the observational record. The best available gridded data in these regions is from the high resolution forecasts of the Global Environmental Multiscale (GEM) atmospheric model and the Canadian Precipitation Analysis (CaPA) reanalysis but this dataset has a short historical record. The EU WATCH ERA-Interim reanalysis (WFDEI) has a longer historical record, but has often been found to be biased relative to observations over Canada. The aim of this study, therefore, is to blend the strengths of both datasets (GEM-CaPA and WFDEI) to produce a less-biased long record product (WFDEI-GEM-CaPA). First, a multivariate generalization of the quantile mapping technique was implemented to bias-correct WFDEI against GEM-CaPA at 3h x 0.125ᵒ resolution during the 2005-2016 period, followed by a hindcast of WFDEI-GEM-CaPA from 1979. **Please note: This dataset is linked to an ESSD paper at https://doi.org/10.5194/essd-12-629-2020.  The authors kindly request that you reference this paper in addition to the dataset.
DOI: 10.20383/101.0274
title: Warm-air entrainment and advection during alpine blowing snow events

description: This dataset includes 50 Hz sonic anemometry data, 3-Dimensional wind vectors and sonic temperature, used in the publication “Warm-air entrainment and advection during alpine blowing snow events.” doi.org/10.5194/tc-14-2795-2020. The observations were conducted at the Fortress Mountain Snow Laboratory as part of the PhD work of Nikolas Aksamit. Each file begins at midnight at the beginning of the recording day and runs until the end of the experiment, typically close to midnight. The two anemometers were located on the same steel mast above a constant snow cover. The data spans five days from Nov 20 2015 to Mar 3 2016. The depth of snow fluctuated between the days of observation causing the anemometer height above the snow to vary between 20 and 50 cm for the lower anemometer and 120 and 150 cm. The purpose of the study was to connect turbulent structures as identified in these time series with blowing snow transport measured immediately below the mast. No preprocessing of the data has been performed and caution should be taken to avoid measurements that were contaminated by blowing snow particles.
DOI: 10.20383/101.0152
title: Aggregated gridded bedrock depth dataset for Mackenzie and Nelson-Churchill River Basin based on bedrock data by Shangguan et al. (2017)

description: The bedrock dataset created by Shangguan et al. (2017) is aggregated to a lower resolution (larger pixels) of 0.125 degree for Mackenzie and Nelson-Churchill River Basins for its applicability with Hydrology and Land Surface Models. This dataset is in particular generated for using with MESH (Modélisation Environnementale communautaire - Surface Hydrology), a distributed coupled hydrology-land surface model developed by Environment and Climate Change Canada, as applied to Mackenzie and Nelson-Churchill River Basins. The statistics calculated for each final larger pixel (0.125 degrees) include mean, median, maximum, minimum, and standard deviation of the original higher resolution pixels within it. Also, in order to provide an idea of the reliability of this transformation, a corresponding 0.125 degrees raster dataset is created containing the number of missing values (NA) from the Shangguan et al. (2017) dataset within each larger 0.125 degree pixels.