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2018 Statistics Canada – Canadian Housing Statistics Program 46-10-0050-01: Total family income and owner characteristics at the residential property level by income quintiles
— 2018 <p>This dataset includes Statistics Canada table 46-10-0050-01, titled "Total family income and owner characteristics at the residential property level by income quintiles". </p> <p>The dataset has been split up into three tables: <br /> Table A includes the number of properties and average assessment value of properties by the owner's income quintile, the property type (eg. detached house, condominium), and by family type (lone-parent family, couple family, and other census family).<br /> Table B includes includes the number of properties and average assessment value of properties by the owner's income quintile, the property type (eg. detached house, condominium), and by pension income categories (eg. whether or not the owner of the property is receiving a pension).<br /> Table C includes includes includes the number of properties and average assessment value of properties by the owner's income quintile, the property type (eg. detached house, condominium), and by residency participation types (eg. whether the property is owned by resident owners only or a mix of resident and non-resident owners).</p> <p>The tables have been edited to include only geographies from British Columbia and to have the unique ID numbers added to the Census Subdivisions and Census Metropolitan Areas. The tables are available in CSV and Excel Workbook format. Definitions and notes are included at the bottom of the spreadsheet.</p> <p>This data set was collected as part of the Canadian Housing Statistics Program by Statistics Canada.</p> <p>Geographies: <br /> Abbotsford-Mission, census metropolitan area, Abbotsford, Mission, Kelowna, census metropolitan area, Central Okanagan, Central Okanagan J, Kelowna, Lake Country, Peachland, West Kelowna, Vancouver, census metropolitan area, Anmore, Belcarra, Bowen Island, Burnaby, Coquitlam, Delta, Langley, city, Langley, municipal district, Lions Bay, Maple Ridge, Metro Vancouver A, New Westminster, North Vancouver, city, North Vancouver, municipal district, Pitt Meadows, Port Coquitlam, Port Moody, Richmond, Surrey, Vancouver, West Vancouver, White Rock, Victoria, census metropolitan area, Central Saanich, Colwood, Esquimalt, Highlands, Juan de Fuca (Part 1), Langford, Metchosin, North Saanich, Oak Bay, Saanich, Sidney, Sooke, Victoria, View Royal, British Columbia, outside of census metropolitan areas, Alberni-Clayoquot A, Alberni-Clayoquot B, Alberni-Clayoquot C, Alberni-Clayoquot D, Alberni-Clayoquot E, Alberni-Clayoquot F, Alert Bay, Armstrong, Ashcroft, Barriere, Bulkley-Nechako A, Bulkley-Nechako B, Bulkley-Nechako C, Bulkley-Nechako D, Bulkley-Nechako E, Bulkley-Nechako F, Bulkley-Nechako G, Burns Lake, Cache Creek, Campbell River, Canal Flats, Cariboo A, Cariboo B, Cariboo C, Cariboo D, Cariboo E, Cariboo F, Cariboo G, Cariboo H, Cariboo I, Cariboo J, Cariboo K, Cariboo L, Castlegar, Central Coast A, Central Coast C, Central Coast D, Central Coast E, Central Kootenay A, Central Kootenay B, Central Kootenay C, Central Kootenay D, Central Kootenay E, Central Kootenay F, Central Kootenay G, Central Kootenay H, Central Kootenay I, Central Kootenay J, Central Kootenay K, Chase, Chetwynd, Chilliwack, Clearwater, Clinton, Coldstream, Columbia-Shuswap A, Columbia-Shuswap B, Columbia-Shuswap C, Columbia-Shuswap D, Columbia-Shuswap E, Columbia-Shuswap F, Comox, Comox Valley A, Comox Valley B (Lazo North), Comox Valley C (Puntledge - Black Creek), Courtenay, Cowichan Valley A, Cowichan Valley B, Cowichan Valley C, Cowichan Valley D, Cowichan Valley E, Cowichan Valley F, Cowichan Valley G, Cowichan Valley H, Cowichan Valley I, Cranbrook, Creston, Cumberland, Dawson Creek, Duncan, East Kootenay A, East Kootenay B, East Kootenay C, East Kootenay E, East Kootenay F, East Kootenay G, Elkford, Enderby, Fernie, Fort St. James, Fort St. John, Fraser Lake, Fraser Valley A, Fraser Valley B, Fraser Valley C, Fraser Valley D, Fraser Valley E, Fraser Valley F, Fraser Valley G, Fraser Valley H, Fraser-Fort George A, Fraser-Fort George C, Fraser-Fort George D, Fraser-Fort George E, Fraser-Fort George F, Fraser-Fort George G, Fraser-Fort George H, Fruitvale, Gibsons, Gold River, Golden, Grand Forks, Granisle, Greenwood, Harrison Hot Springs, Hazelton, Hope, Houston, Hudson's Hope, Invermere, Juan de Fuca (Part 2), Kamloops, Kaslo, Kent, Keremeos, Kimberley, Kitimat, Kitimat-Stikine A, Kitimat-Stikine B, Kitimat-Stikine C (Part 1), Kitimat-Stikine C (Part 2), Kitimat-Stikine D, Kitimat-Stikine E, Kitimat-Stikine F, Kootenay Boundary A, Kootenay Boundary B / Lower Columbia-Old-Glory, Kootenay Boundary C / Christina Lake, Kootenay Boundary D / Rural Grand Forks, Kootenay Boundary E / West Boundary, Ladysmith, Lake Cowichan, Lantzville, Lillooet, Logan Lake, Lumby, Lytton, Mackenzie, Masset, McBride, Merritt, Midway, Montrose, Mount Waddington A, Mount Waddington B, Mount Waddington C, Mount Waddington D, Nakusp, Nanaimo, Nanaimo A, Nanaimo B, Nanaimo C, Nanaimo E, Nanaimo F, Nanaimo G, Nanaimo H, Nelson, New Denver, New Hazelton, North Coast A, North Coast C, North Coast D, North Coast E, North Cowichan, North Okanagan B, North Okanagan C, North Okanagan D, North Okanagan E, North Okanagan F, Northern Rockies, Okanagan-Similkameen A, Okanagan-Similkameen B, Okanagan-Similkameen C, Okanagan-Similkameen D, Okanagan-Similkameen E, Okanagan-Similkameen F, Okanagan-Similkameen G, Okanagan-Similkameen H, Oliver, One Hundred Mile House, Osoyoos, Parksville, Peace River B, Peace River C, Peace River D, Peace River E, Pemberton, Penticton, Port Alberni, Port Alice, Port Clements, Port Edward, Port Hardy, Port McNeill, Pouce Coupe, Powell River, Powell River A, Powell River B, Powell River C, Powell River D, Powell River E, Prince George, Prince Rupert, Princeton, Qualicum Beach, Queen Charlotte, Quesnel, Radium Hot Springs, Revelstoke, Rossland, Salmo, Salmon Arm, Saltspring Island, Sayward, Sechelt, Sicamous, Silverton, Slocan, Smithers, Southern Gulf Islands, Spallumcheen, Sparwood, Squamish, Squamish-Lillooet A, Squamish-Lillooet B, Squamish-Lillooet C, Squamish-Lillooet D, Stewart, Stikine Region, Strathcona A, Strathcona B, Strathcona C, Strathcona D (Oyster Bay - Buttle Lake), Summerland, Sun Peaks Mountain, Sunshine Coast A, Sunshine Coast B, Sunshine Coast D, Sunshine Coast E, Sunshine Coast F, Tahsis, Taylor, Telkwa, Terrace, Thompson-Nicola A (Wells Gray Country), Thompson-Nicola B (Thompson Headwaters), Thompson-Nicola E (Bonaparte Plateau), Thompson-Nicola I (Blue Sky Country), Thompson-Nicola J (Copper Desert Country), Thompson-Nicola L (Grasslands), Thompson-Nicola M (Beautiful Nicola Valley - North), Thompson-Nicola N (Beautiful Nicola Valley - South), Thompson-Nicola O (Lower North Thompson), Thompson-Nicola P (Rivers and the Peaks), Tofino, Trail, Tumbler Ridge, Ucluelet, Valemount, Vanderhoof, Vernon, Warfield, Wells, Whistler, Williams Lake, Zeballos </p>
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Depth profiles of cadmium and silver (dissolved and particulate phases) in the Salish Sea
— 2022-06-02 This dataset contains high-resolution depth profiles of cadmium and silver in seawater and marine particles collected from the Salish Sea, with a focus on the Strait of Georgia. Dissolved and total concentrations of cadmium and silver are also reported for treated effluent from Metro Vancouver's Iona Island Wastewater Treatment Plant, and screened effluent from two outfalls located in the Capital Regional District.
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2016 Census of Canada - Selected Characteristics for Housing - Vancouver, Toronto CMAs at the Census Tract (CT) Level [custom tabulation] 003
— 2016 <p>This dataset includes two tables which were custom ordered from Statistics Canada. One table includes information on shelter cost to income ratio and total shelter cost by tenure, household type, and household income. The other table includes variables on housing characteristics (total number of bedrooms, structural type, and tenure), and households (household size, household type, and age of primary household maintainer). </p> <p>The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). <br /> For information on how to use Beyond 20/20, please see: <br /> http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf <br /> https://wiki.ubc.ca/Library:Beyond_20/20_Guide </p> <p><b>Custom Order from Statistics Canada</b></p> <p><b>TABLE 1 includes the following dimensions and variables:</b></p> <p>Geography: Toronto CMA & Vancouver CMA to the census tract level</p> <p>Tenure: Owner (with and without mortgage), renter, subsidized, not subsidized </p> <p>Shelter Cost to Income Ratio: less than 15%, 15-30%, 30-50%, 50% or more, not applicable </p> <p>Household Type: <br /> -Census-family households<br /> -One-census family households without additional persons<br /> -One couple census family without other persons in the household<br /> -With children<br /> -Without children<br /> -One lone-parent census family without other persons in the household<br /> -One-census-family households with additional persons<br /> -One couple census family household with additional persons<br /> -One lone-parent census family with additional persons in the household<br /> -With children<br /> -Without children<br /> -One lone-parent census family with other persons in the household<br /> -Multiple census-family households<br /> -Non-census family household<br /> -One person households<br /> -Two or more person non-census households</p> <p>Total Shelter Cost: under $500 to over $3000 in intervals of $250 and $500 </p> <p>Household Income: in intervals of $10,000 up to $100,000 or more</p> <p><b>TABLE 2 includes the following dimensions and variables:</b></p> <p>Geography: Toronto CMA & Vancouver CMA to the census tract level</p> <p>Total number of bedrooms: No bedrooms to 4 or more bedrooms</p> <p>Tenure: Owner, renter</p> <p>Structural type: <br /> -Single detached house<br /> -Apartment with 5 or more stories<br /> -Other attached dwelling<br /> -Semi-detached house<br /> -Row house<br /> -Apartment or flat in a duplex<br /> -Apartment, building with fewer than 5 stories<br /> -Other single attached house<br /> -Movable dwelling</p> <p>Age of Household Maintainer: Begins at 15 and continues in 9 year intervals until 75 and over.</p> <p>Condominium Status: Condominium, not a condominium</p> <p>Household Type:<br /> -Census-family households <br /> -With children<br /> -Without children<br /> -Multiple census-family households<br /> -Non-census family household</p> <p>Household Size: One person up to 5 or more persons</p> <p>Original file names:<br /> EO2969 - Table 1 (Part 1) Cost income household _Toronto and Vancouver 2016.ivt<br /> EO2969 - Table 2 Tenure and dwelling_Toronto and Vancouver 2016.ivt</p>
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UBC Farm Sales Records
— 2020-02-24 This dataset contains sales records for UBC Farm since 2019, including total revenue per product through its main sales channels: markets, community-supported agriculture (CSA) programs, and wholesale. Please note that a product does not represent a specific crop (e.g. kale), but a specific quantity and packaging of that crop. For example, 'kale, tote (10 lb)' and 'kale, bunch (0.67 lb)' are different products, but the same crop. <br><br> Please note that the UBC Farm’s data management practices have grown and evolved over time, and some forms of data have been consistently collected for more years than others. UBC Farm staff are also busy and imperfect humans and sometimes forget to log activities. On rare occasion, erroneous data may accidentally be entered, and these errors may not get corrected during quality control checks. While we do our best to ensure the data we release is complete and accurate, we provide this data to you “as is”, through the disclaimer in the CC BY-NC-SA 4.0 license.
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Data for: Water quality and greenhouse gas fluxes for stormwater detained in a constructed wetland
— 2018 http://hdl.handle.net/11272/10676 The study contains data on: i) CO2, CH4 and N2O concentrations and fluxes, and the parameters that were used for computation of GHG fluxes, and ii) DOC and NO3 concentrations from a stormwater detained in a constructed wetland. These data were collected in order to evaluate the spatial and temporal dynamics of GHG fluxes and water quality from stormwater runoff.
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JProteomics2014
— 2020-06-19 Development of a computation framework for the analysis of protein correlation profiling and spatial proteomics experiments 2014
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Replication Data for: Current Surgical Treatment of Intermediate Risk Differentiated Thyroid Cancer: A Systematic Review
— 2020-11-26 Surgical treatment of thyroid cancer has become less aggressive but for many patients, the threshold for performing total thyroidectomy (TT), as opposed to thyroid lobectomy (TL), has remained unclear. Current American Thyroid Association (ATA) guidelines encourage more individualization of treatment options, which necessitates explicit review of the pros and cons of the different options with patients. This review focuses on the extent of surgery for treatment of intermediate-risk differentiated thyroid cancer, restricted to relevant literature available after publication of the 2015 ATA guidelines. Publication Currently In Press
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Examining the University of British Columbia Vancouver campus views using LIDAR data
— 2022-05-03 This study examines the application possibilities of LIDAR data in building a digital model of the campus in three dimensions to: a) assess whether strategic observations point still exist on campus. b) mapping the built landscape across campus. c) determine planning principles for areas of interest where the new building height is considered. The study presents various methods, such as viewshed analysis and raster calculations. It mimics the observation boundaries from critical points on-campus to understand better the threatened interest points and elements that block these observation areas. The height element was a significant component in the analysis, and the maximum height of future buildings is also considered in this way. Out of interest in seeing if new buildings disturbed the balance of nature seen by one of the selected observations points. The study results showed accuracy in the input data that made it possible to build an advanced three-dimensional campus model. This model enables real-time performance to simulate and test the construction evolution of UBC's future built form.
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2018 Statistics Canada – Canadian Housing Survey 46-10-0024-01: Dwelling and neighbourhood satisfaction, by tenure including social and affordable housing and structural type of dwelling
— 2018 <p>This dataset includes Statistics Canada table 46-10-0024-01, titled “Dwelling and neighbourhood satisfaction, by tenure including social and affordable housing and structural type of dwelling”. The table includes information on satisfaction with housing by tenure, condominium status, and structural type of dwelling. One of the tenure categories is renters in social and affordable housing.</p> <p>The table has been edited to include only geographies from British Columbia. The table is available in CSV and Excel Workbook format. Definitions and notes are included at the bottom of the spreadsheet. </p> <p>This data set was collected as part of the Canadian Housing Survey by Statistics Canada.</p> <p>Geographies:<br /> British Columbia, Large urban population centres, British Columbia, Medium population centres, British Columbia, Small population centres, British Columbia, Rural areas, British Columbia, Vancouver, British Columbia, Other census metropolitan areas, British Columbia, Census agglomerations, British Columbia</p>
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Data for: UBC Farm Long-Term Biodiversity Monitoring Program
— 2020-02-24 This dataset contains data collected through the UBC Farm Long-Term Biodiversity Monitoring Program, which started in May 2019. <br><br> Project Description: The UBC Farm Long-term Biodiversity Monitoring Program assesses biodiversity across multiple scales and levels at the UBC Farm. Biodiversity is the foundation of agricultural productivity and contributes essential ecosystem functions and services to food systems. The UBC Farm provides a unique opportunity to monitor the biodiversity important for agroecosystem food production and other ecosystem services on a working, diversified, and organic farm and pilot new technologies and survey techniques to assess agrobiodiversity. The Long-Term Biodiversity Monitoring program focuses on assessing bumble bees, earthworms, forest and crop plants, birds, mammals, bats, and soil fauna each year. The program aims to improve understanding of the biodiversity at the UBC Farm, how it is changing over time, and how this affects important ecosystem services (the benefits people receive from the natural environment) that benefit people, help crops grow, and contribute to overall agroecosystem sustainability.
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Autocorrelation between Fuel Type Fragmentation and Fire Severity at the Elephant Hill wildfire in British Columbia
— 2021-04-15 Geospatial analyses focused on quantifying fuel types fragmentation and its autocorrelation with megafire severity inform decision making in contexts such as forest management and human activities regulation. Fuel type fragmentation plays a crucial role in fire severity contribution. I evaluated the landscape and class level fragmentation of fuel types in two maps: FuelSat (derived from remote sensing) and a completely randomized map. Specifically, the C-2 (Boreal Spruce), C-3 (Mature Pine), slash, and standing grass were targeted for class level metrics calculation. Fire behavior could be described in two terms – burn probability and fire intensity. Flammability (burn probability) represent the likelihood of a given location on landscape burning, while the fire intensity is the rate of heat energy released by the fire. Burn probability and fire intensity of those four target classes were extracted from landscapes (FuelSat and Random). Boxplots were created to visualize the difference between burn probability and fire intensity of four classes from FuelSat and Random, respectively. Results indicated higher fragmentated fuel types would lower the fire intensity generally, but resulted in more extreme events. It was not evident that fuel type fragmentation has significant impacts on burn probability. Moran’s I was computed and did indicate there was autocorrelation between fuel fragmentation and fire intensity. It helps fill the gap in forest fire prediction by considering effects of fuel fragmentation.
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Distribution of suitable habitat in winter and summer for plains bison (Bison bison bison) in the Pink Mountain Region of British Columbia
— 2021-04-12 The plains bison (Bison bison bison) is threatened in Canada, with the biggest threat to their recovery being a lack of habitat in which they are considered compatible. Although the Pink Mountain, British Columbia, bison herd currently has about 1,000 individuals, there has never been a formal study of the suitability of the area to sustain the herd. Therefore, this study was performed to determine if the Pink Mountain region contains plains bison suitable habitat based on guiding principles for developing a Habitat Suitability Index. Data used for analysis was aggregated from Landsat8, Canadian Digital Elevation Model, Daymet, and the Freshwater Data Atlas of British Columbia. The final habitat suitability index combined a value for slope, distance to water, landcover, aspect, and snow depth. Separate calculations were performed for summer and winter. Based on the habitat suitability model conducted, there appears to be significant habitat of sufficient quality to support a population of plains bison year-round in the Halfway River drainage. Areas with acceptable habitat were predominately in the river bottoms or valleys and the far eastern section of the study area. In the summer, approximately 60% of the area was categorized as a habitat suitability index of at least six. In winters with maximum snow coverage, only 17% was similarly categorized. Despite this, it is my impression that the area acceptable as habitat is sufficient for a considerable population of bison. Extending the area under study and creating estimates of forage production could lead to a more detailed assessment of carrying capacity for bison in the region, leading to improved management of this iconic species.
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Burning In The Muskwa-Kechika Management Area – Halfway Region: Quantifying Landscape Structure Using Historical Aerial Photographs
— 2021-04-19 Landscape configuration and composition change are common in rangeland management areas where burning is used to maintain grasslands on slopes. However, little is known about the spatial character of patches within landscapes. The spatial character of landscape patches can be used to link landcover patterns to fire occurrences. We conducted a study to examine the composition and configuration of landscape as a link between landcover types and fires in the Halfway Region – Muskwa Kechika Management Area (M-KMA) in British Columbia. We used historical aerial photos to characterize historical landcover changes and patterns. Historical aerial images from two time periods (1963 and1999) were segmented into homogenous landcover patches and classified into six landcover classes (water, bare land, grassland, shrubs, deciduous, coniferous) using the support vector machine algorithm. Class level landscape metrics as the number of patches (NP), percentage landscape (PLAND), mean patch size (AERA_MN) were computed to quantify landscape configuration and composition. Coniferous land cover increased from ~8% to ~30% from 1963 to 1999, replacing deciduous as the dominant land. Deciduous had a 27% negative change in the land cover area, with ~85% attributed to burning. Homogenous patches were observed for shrublands with an increase in PLAND while its number of patches decreased. Grasslands and bare land PLAND decreased in size over time, whereas their mean patch size increased. Despite the challenges in geoprocessing historical aerial photos due to differences in tone and texture properties, aerial photos contain information dating many years back, making them valuable in quantifying landscape landcover patterns. aerial photographs, landscape configuration, land cover, burning, muskwa kechika management area, remote sensing
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BC Transit Routes for Victoria, Whistler, Pemberton, Squamish and Kelowna, 10 February 2012
— 2012 BC Transit routes for Victoria, Whistler, Pemberton Local and Commuter, Squamish Commuter and Kelowna. The routes were created from the Google transit feed (GTFS) and ArcGIS Network Analyst. As no route shape information was available from the feed, the shape of the route was extrapolated from the road network and layout of transit stops. The transit routes were not verified as no maps are available. Although routes were calculated as carefully as possible, this data set carries no guarantee of accuracy beyond the information included in the Google transit feed. http://hdl.handle.net/11272/2OYCX <p> Info:Misc:<br> GTFS feed coordinate system: WGS 84<br> Projection: NAD_1983_BC_Environment_Albers<br> Route and arrival data used in this product or service is provided by permission of BC Transit. BC Transit assumes no responsibility for the accuracy or currency of the Data used in this product or service.<br> <p> Info:Migration:<br> UBC Library Data Services repository software migration from DSPACE to DATAVERSE. Dataset 10573/42707 was migrated on 2013/10/03.<br> The former URI for this resource (<a href="http://hdl.handle.net/10573/42707">http://hdl.handle.net/10573/42707</a>) is deprecated. <p> Resource access is PUBLIC.
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<6m Observation - Clinical 1 (dataset) ~ Smart Discharges
— 2021-04-20 <br /><strong>NOTE for restricted files:</strong> If you are not yet a CoLab member, please complete our <a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79">membership application survey</a> to gain access to restricted files within 2 business days. <br />Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator on <a href = "https://www.bcchr.ca/pediatric-sepsis-data-colab">this page</a> under "collaborate with the pediatric sepsis colab." Clinical outcome dataset #1 from Smart Discharges <6m observational study. May 2017 to March, 2020 (Thrasher - <6m - Phase 1).
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Replication Data for: Behavioral analysis of habit formation in modern slot machine gambling
— 2022-06-16 Study Abstract: Habit formation is a key process in contemporary models of addictive behaviours, but has received limited attention in the context of gambling and problem gambling. Methods for examining habit formation and expression in relation to gambling are also lacking. In this study, 60 participants with no prior slot machine experience attended three sessions spaced 6 to 8 days apart, during which they played a short 200-spin session on a realistic simulation of a modern multi-line slot machine. Behavioral data were analyzed to characterize habit formation within and between sessions. Fixed-effects regressions, integrating trial- and session-level effects, assessed predictors of gambling speed (spin initiation latencies) and betting rigidity (the likelihood of switching the bet amount), as two putative markers of habit formation. Participants gambled faster and showed less variability in betting strategy as they accumulated experience in the number of trials and sessions gambled. Simultaneously, as the number of sessions gambled increased, participants showed a more pronounced tendency to slow their betting after larger wins (i.e., the post-reinforcement pause increased from session 1 to session 3). Our methods provide a basis for future research to examine habits in the context of slot machine gambling.
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Post-Discharge Care Counselling Videos - Luganda ~ Smart Discharges
— 2022-06-02 <br /><strong>NOTE for restricted files:</strong> If you are not yet a CoLab member, please complete our <a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79">membership application survey</a> to gain access to restricted files within 2 business days. <br />Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator on <a href = "https://www.bcchr.ca/pediatric-sepsis-data-colab">this page</a> under "collaborate with the pediatric sepsis colab." <strong>Objective(s):</strong> Smart Discharges is a digital health program that uses individual-level risk prediction and intervention to increase effective health seeking behavior, improve health outcomes, and reduce mortality during the post-discharge period. Health workers aim to mitigate risk by educating caregivers on post-discharge care and by scheduling follow-up visits for at-risk children in their communities. <br /><strong>Data Description:</strong> This dataset includes an introductory video and caregiver discharge counselling videos on: 1) Hygiene; 2) Nutrition; 3) Breastfeeding; 4) Care Seeking; 5) Mosquito Net Use; 6) Medications; 7) Immunizations. Videos are available in English and local Ugandan languages of Acholi, Luganda, Lusoga, and Runyankole. This dataset contains the <strong> Luganda</strong> version. <br /><strong>Limitations:</strong> Videos were designed for the Ugandan context and may not be generalizable to other settings. <br /><strong>Abbreviations:</strong> Village Health Teams (VHT) (i.e. local term for Community Health Worker (CHW)) <br /><strong>Ethics Declaration:</strong> NA <br /><strong>Funding Source(s):</strong> BC Children's Hospital Foundation; Grand Challenges Canada; Mining4Life; Thrasher Research Fund;
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Assessing identity, redundancy and confounds in Gene Ontology annotations over time
— 2013 http://hdl.handle.net/11272/10571 <p>MOTIVATION:<p> <p>The Gene Ontology (GO) is heavily used in systems biology, but the potential for redundancy, confounds with other data sources and problems with stability over time have been little explored.<p> <p>RESULTS:<p> <p>We report that GO annotations are stable over short periods, with 3% of genes not being most semantically similar to themselves between monthly GO editions. However, we find that genes can alter their 'functional identity' over time, with 20% of genes not matching to themselves (by semantic similarity) after 2 years. We further find that annotation bias in GO, in which some genes are more characterized than others, has declined in yeast, but generally increased in humans. Finally, we discovered that many entries in protein interaction databases are owing to the same published reports that are used for GO annotations, with 66% of assessed GO groups exhibiting this confound. We provide a case study to illustrate how this information can be used in analyses of gene sets and networks. <p> <p>AVAILABILITY:<p> <p>Data available at http://chibi.ubc.ca/assessGO.<p>

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