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These pie charts show the distribution of biomass quantities (in percentage terms) per municipality in the following categories, roadside clippings, reeds and heaths, stems and leaves. The size of the pie chart shows the cumulative quantity. This dataset is used in the "biomass" map as part of the research into the natural capital in Overijssel.
This Dashboard displays parcel status information by city and town, in a map, table and pie chart.Click on a city or town in the map to view information about that municipality.Click on a row in the table to zoom to that city or town.The pie chart displays the fiscal yer currency of parcel data updates.
Contained within the 3rd Edition (1957) of the Atlas of Canada is a plate that shows the distribution of population in what is now Canada circa 1851, 1871, 1901, 1921 and 1941. The five maps display the boundaries of the various colonies, provinces and territories for each date. Also shown on these five maps are the locations of principal cities and settlements. These places are shown on all of the maps for reference purposes even though they may not have been in existence in the earlier years. Each map is accompanied by a pie chart providing the percentage distribution of Canadian population by province and territory corresponding to the date the map is based on. It should be noted that the pie chart entitled Percentage Distribution of Total Population, 1851, refers to the whole of what was then British North America. The name Canada in this chart refers to the province of Canada which entered confederation in 1867 as Ontario and Quebec. The other pie charts, however, show only percentage distribution of population in what was Canada at the date indicated. Three additional graphs are included on this plate and show changes in the distribution of the population of Canada from 1867 to 1951, changes in the percentage distribution of the population of Canada by provinces and territories from 1867 to 1951 and elements in the growth of the population of Canada for each ten-year period from 1891 to 1951.
This dataset includes information for projects that appear on the City of Austin’s Capital Improvement Visualization Information and Communication (CIVIC) Map Viewer, www.austintexas.gov/GIS/civic. These projects, also known as Capital Improvements Program (CIP) projects, implement the construction, replacement, or renovation of city assets that are useful to the community. Data is currently available for most CIP projects funded in full or in part by voter-approved bond programs from 2010 and 2012. The dataset below is subject to change at any time, and does not represent a comprehensive list of capital improvement projects. For more information about the City of Austin’s Capital Improvement Program, please visit www.austintexas.gov/department/civic. The City of Austin has produced CIVIC, a web application to search Capital Improvement Projects, for informational purposes only. The data and information available at this web site is provided "As is", and "As Available" and without any warranties of any kind either express or implied. The City makes no warranty regarding the accuracy or completeness of this site and the information provided. By accessing or using CIVIC, you agree to these terms of use. The City of Austin may change the terms of use at any time at its sole discretion and without notice.”
http://standaarden.overheid.nl/owms/terms/licentieonbekendhttp://standaarden.overheid.nl/owms/terms/licentieonbekend
The business parks in Overijssel are divided into three classes based on the proportion of greenery (lowest 33%, middle 33% and highest 33%) on the site. This pie chart shows the share of less green, average green and above average green sites (as a percentage of the surface area of industrial estates per municipality). The size of the pie chart shows how many hectares of industrial estate there are per municipality. This dataset is used to map industrial estates as part of the research into natural capital in Overijssel.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Contained within the 3rd Edition (1957) of the Atlas of Canada is a plate that shows the distribution of population in what is now Canada circa 1851, 1871, 1901, 1921 and 1941. The five maps display the boundaries of the various colonies, provinces and territories for each date. Also shown on these five maps are the locations of principal cities and settlements. These places are shown on all of the maps for reference purposes even though they may not have been in existence in the earlier years. Each map is accompanied by a pie chart providing the percentage distribution of Canadian population by province and territory corresponding to the date the map is based on. It should be noted that the pie chart entitled Percentage Distribution of Total Population, 1851, refers to the whole of what was then British North America. The name Canada in this chart refers to the province of Canada which entered confederation in 1867 as Ontario and Quebec. The other pie charts, however, show only percentage distribution of population in what was Canada at the date indicated. Three additional graphs are included on this plate and show changes in the distribution of the population of Canada from 1867 to 1951, changes in the percentage distribution of the population of Canada by provinces and territories from 1867 to 1951 and elements in the growth of the population of Canada for each ten-year period from 1891 to 1951.
The layer is suitable for circle or pie chart maps.
Salmonid Enhancement Program (SEP) fish releases from 2015 to 2019 excluding spawning channel facilities. Releases are represented by pie charts on a regional level.Wild stocks of Pacific salmon have experienced significant declines in abundance over the past century. One of the management tools to compensate for these losses has been the use of hatcheries. Over time, hatcheries have also been used to mitigate for habitat losses, to support fisheries, for conservation, and for education.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Contained within the 4th Edition (1974) of the Atlas of Canada is a map that shows locations of ports in Eastern Canada handling more than 5000 tons. Pie charts are superimposed on the map and show whether the tonnage was loaded, unloaded, from foreign ports or from other Canadian ports. Two smaller maps show Newfoundland (1:5 000 000 scale) and Northern Canada (1:20 000 000 scale). The map is accompanied by a graph showing tonnage by territorial division for 1964.
The "Watershed" feature layer is a component of the "Pollinator Restoration 2022" map which is itself a component of the "USFWS Pollinator Restoration Projects Mapper" which is a dashboard showing management projects that benefit pollinators across the Western U.S. See below for a description of the "USFWS Pollinator Restoration Projects Mapper."The "USFWS Pollinator Restoration Projects Mapper" is under development by the Region 1 (Pacific Northwest) USFWS Science Applications program. Completion is anticipated by Winter 2023. Contact: Alan Yanahan (alan_yanahan@fws.gov).The purpose of the "USFWS Pollinator Restoration Projects Mapper" is to inform future pollinator conservation efforts by providing a way to identify geographic areas where additional pollinator conservation may be needed.The "USFWS Pollinator Restoration Projects Mapper" maps the locations of where on-the-ground projects that are beneficial to pollinators have taken place. Its primary focus is projects on public lands. The majority of records included in this tool come from internal databases for the USFWS, US Forest Service, and the Bureau of Land Management, which were queried for relevant projects. The tool is not intended as a database for reporting projects to. Rather, the tool synthesizes records from existing databases.The geographic scope of the tool includes the western states of Arizona, California, Idaho, Nevada, Oregon, Utah, and Washington.When possible, the tool includes projects from 2014 to the present. This timespan was chosen because it matches the timespan of the USFWS Monarch Conservation Database For consistency, the tool groups pollinator beneficial projects into the following four activity types:Restoration: Actions taken after a disturbance, such as planting native forbs after a wildfireMaintenance: Actions taken outside the growing season that maintain habitat quality through regular disturbance using manual or chemical means. Examples: mowing, spraying weeds, prescribed fireConservation: Acquiring land or creating easements that are managed for biodiversityEnhancement: Actions that increase forb diversity and nectar resources, such as planting native milkweedThe tool includes a map that aggregates project point locations within 49 square mile sized hexagon grid cells. Users can click on individual grid cells to activate a pop-up menu to cycle through the projects that occurred within that grid cell. Information for each project include, but are not limited to, acreage, type of activity (i.e., restoration, maintenance, conservation, enhancement), data source, and lead organization.The tool also includes a dashboard to view bar graphs and pie charts that display project acreages and project number based on location (i.e., state), project activity type (i.e., restoration, maintenance, conservation, enhancement), data source, and management type. Data can be filtered by data source, activity type, and year. Data filtering will update the map, bar graphs, and pie charts.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Contained within the 3rd Edition (1957) of the Atlas of Canada is a map that shows three condensed maps of the percentage of population: under 20 years of age, 20-64 years of age, and over 64 years of age illustrated by the census division, circa 1951. Each of these maps is accompanied by a pie chart showing the percentage distribution by province and territory. The two remaining maps show urban and rural sex ratios using the number of males to 100 females by census division as of 1951. The rural sex ratio map is accompanied by a chart showing the ratio of males to 100 females by province and territory. As well, a chart accompanies the urban sex ratio map and shows the ratio of males to 100 females for chief urban centers. A set of age-sex pyramids that show the 1951 percentage distribution of males and females by quinquennial age groups for Canada, each province and the territories are also included.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Scholarly figures are data visualizations like bar charts, pie charts, line graphs, maps, scatter plots or similar figures. Text extraction from scholarly figures is useful in many application scenarios, since text in scholarly figures often contains information that is not present in the surrounding text. This dataset is a corpus of 121 scholarly figures from the economics domain evaluating text extraction tools. We randomly extracted these figures from a corpus of 288,000 open access publications from EconBiz. The dataset resembles a wide variety of scholarly figures from bar charts to maps. We manually labeled the figures to create the gold standard.
We adjusted the provided gold standard to have a uniform format for all datasets. Each figure is accompanied by a TSV file (tab-separated values) where each entry corresponds to a text line which has the following structure:
X-coordinate of the center of the bounding box in pixel
Y-coordinate of the center of the bounding box in pixel
Width of the bounding box in pixel
Height of the bounding box in pixel
Rotation angle around its center in degree
Text inside the bounding box
In addition we provide the ground truth in JSON format. A schema file is included in each dataset as well. The dataset is accompanied with a ReadMe file with further information about the figures and their origin.
If you use this dataset in your own work, please cite one of the papers in the references.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Contained within the 3rd Edition (1957) of the Atlas of Canada is a plate that shows six condensed maps of the distribution of plants producing the following: leather footwear, womens and childrens factory made clothing, synthetic textiles and silks, mens factory made clothing, cotton textiles, and rubber products. All data for these maps is for 1954 with the exception of the rubber products map which is for 1955. Each map is accompanied by a bar graph and pie chart. The bar graphs show the value of production by major categories of products. The pie charts show the percentage distribution of persons employed in each manufacturing industry by province.
Lighting maps of Vanuatu. Maps of islands in Vanuatu and pie chart overview of lighting i.e. % access to grid, kerosene, torchgas, own lighting and other.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Contained within the 3rd Edition (1957) of the Atlas of Canada is a map that shows two condensed maps for the distribution of areas seeded in wheat and barley for harvesting circa 1951. Therefore, in the case of wheat, the areas include those seeded in the fall of 1950 as well as those seeded in the spring of 1951. These two maps are both accompanied by pie charts showing the percentage distribution of seeded areas by province. No areas were devoted to either wheat or barley in Newfoundland.
The "CountiesStatesInfo" feature layer is a component of the "Pollinator Restoration 2022" map which is itself a component of the "USFWS Pollinator Restoration Projects Mapper" which is a dashboard showing management projects that benefit pollinators across the Western U.S. See below for a description of the "USFWS Pollinator Restoration Projects Mapper."The "USFWS Pollinator Restoration Projects Mapper" is under development by the Region 1 (Pacific Northwest) USFWS Science Applications program. Completion is anticipated by Winter 2023. Contact: Alan Yanahan (alan_yanahan@fws.gov).The purpose of the "USFWS Pollinator Restoration Projects Mapper" is to inform future pollinator conservation efforts by providing a way to identify geographic areas where additional pollinator conservation may be needed.The "USFWS Pollinator Restoration Projects Mapper" maps the locations of where on-the-ground projects that are beneficial to pollinators have taken place. Its primary focus is projects on public lands. The majority of records included in this tool come from internal databases for the USFWS, US Forest Service, and the Bureau of Land Management, which were queried for relevant projects. The tool is not intended as a database for reporting projects to. Rather, the tool synthesizes records from existing databases.The geographic scope of the tool includes the western states of Arizona, California, Idaho, Nevada, Oregon, Utah, and Washington.When possible, the tool includes projects from 2014 to the present. This timespan was chosen because it matches the timespan of the USFWS Monarch Conservation Database For consistency, the tool groups pollinator beneficial projects into the following four activity types:Restoration: Actions taken after a disturbance, such as planting native forbs after a wildfireMaintenance: Actions taken outside the growing season that maintain habitat quality through regular disturbance using manual or chemical means. Examples: mowing, spraying weeds, prescribed fireConservation: Acquiring land or creating easements that are managed for biodiversityEnhancement: Actions that increase forb diversity and nectar resources, such as planting native milkweedThe tool includes a map that aggregates project point locations within 49 square mile sized hexagon grid cells. Users can click on individual grid cells to activate a pop-up menu to cycle through the projects that occurred within that grid cell. Information for each project include, but are not limited to, acreage, type of activity (i.e., restoration, maintenance, conservation, enhancement), data source, and lead organization.The tool also includes a dashboard to view bar graphs and pie charts that display project acreages and project number based on location (i.e., state), project activity type (i.e., restoration, maintenance, conservation, enhancement), data source, and management type. Data can be filtered by data source, activity type, and year. Data filtering will update the map, bar graphs, and pie charts.
Contained within the 3rd Edition (1957) of the Atlas of Canada is a map that shows two condensed maps of the locations where one or more art galleries, museums or libraries of 10 000 volumes and over existed circa the 1958 publication date of this atlas. Accompanying these maps is a pie chart showing the percentage distribution of volumes in public libraries by province and a bar graph showing the volumes per capita in libraries by province circa 1951.
This map shows the percent of households with no internet access. Pop-up shows counts of households by type of internet access. Map is mulit-scale, with data for state, county, and tract. Map is mulit-scale, with data for state, county, and tract. Pie-chart categories are households with no internet connection, households with internet access with no subscription, households with Broadband of any type, and households with dial-up internet. Hover over the pie chart pieces to see the count of households in each category.More detailed categories as to the type of Broadband subscription are available in the layers.This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset contains a list of 186 Digital Humanities projects leveraging information visualisation methods. Each project has been classified according to visualisation and interaction techniques, narrativity and narrative solutions, domain, methods for the representation of uncertainty and interpretation, and the employment of critical and custom approaches to visually represent humanities data.
The project_id
column contains unique internal identifiers assigned to each project. Meanwhile, the last_access
column records the most recent date (in DD/MM/YYYY format) on which each project was reviewed based on the web address specified in the url
column.
The remaining columns can be grouped into descriptive categories aimed at characterising projects according to different aspects:
Narrativity. It reports the presence of narratives employing information visualisation techniques. Here, the term narrative encompasses both author-driven linear data stories and more user-directed experiences where the narrative sequence is composed of user exploration [1]. We define 2 columns to identify projects using visualisation techniques in narrative, or non-narrative sections. Both conditions can be true for projects employing visualisations in both contexts. Columns:
non_narrative
(boolean)
narrative
(boolean)
Domain. The humanities domain to which the project is related. We rely on [2] and the chapters of the first part of [3] to abstract a set of general domains. Column:
domain
(categorical):
History and archaeology
Art and art history
Language and literature
Music and musicology
Multimedia and performing arts
Philosophy and religion
Other: both extra-list domains and cases of collections without a unique or specific thematic focus.
Visualisation of uncertainty and interpretation. Buiding upon the frameworks proposed by [4] and [5], a set of categories was identified, highlighting a distinction between precise and impressional communication of uncertainty. Precise methods explicitly represent quantifiable uncertainty such as missing, unknown, or uncertain data, precisely locating and categorising it using visual variables and positioning. Two sub-categories are interactive distinction, when uncertain data is not visually distinguishable from the rest of the data but can be dynamically isolated or included/excluded categorically through interaction techniques (usually filters); and visual distinction, when uncertainty visually “emerges” from the representation by means of dedicated glyphs and spatial or visual cues and variables. On the other hand, impressional methods communicate the constructed and situated nature of data [6], exposing the interpretative layer of the visualisation and indicating more abstract and unquantifiable uncertainty using graphical aids or interpretative metrics. Two sub-categories are: ambiguation, when the use of graphical expedients—like permeable glyph boundaries or broken lines—visually convey the ambiguity of a phenomenon; and interpretative metrics, when expressive, non-scientific, or non-punctual metrics are used to build a visualisation. Column:
uncertainty_interpretation
(categorical):
Interactive distinction
Visual distinction
Ambiguation
Interpretative metrics
Critical adaptation. We identify projects in which, for what concerns at least a visualisation, the following criteria are fulfilled: 1) avoid uncritical repurposing of prepackaged, generic-use, or ready-made solutions; 2) being tailored and unique to reflect the peculiarities of the phenomena at hand; 3) avoid extreme simplifications to embraces and depict complexity promoting time-spending visualisation-based inquiry. Column:
critical_adaptation
(boolean)
Non-temporal visualisation techniques. We adopt and partially adapt the terminology and definitions from [7]. A column is defined for each type of visualisation and accounts for its presence within a project, also including stacked layouts and more complex variations. Columns and inclusion criteria:
plot
(boolean): visual representations that map data points onto a two-dimensional coordinate system.
cluster_or_set
(bool): sets or cluster-based visualisations used to unveil possible inter-object similarities.
map
(boolean): geographical maps used to show spatial insights. While we do not specify the variants of maps (e.g., pin maps, dot density maps, flow maps, etc.), we make an exception for maps where each data point is represented by another visualisation (e.g., a map where each data point is a pie chart) by accounting for the presence of both in their respective columns.
network
(boolean): visual representations highlighting relational aspects through nodes connected by links or edges.
hierarchical_diagram
(boolean): tree-like structures such as tree diagrams, radial trees, but also dendrograms. They differ from networks for their strictly hierarchical structure and absence of closed connection loops.
treemap
(boolean): still hierarchical, but highlighting quantities expressed by means of area size. It also includes circle packing variants.
word_cloud
(boolean): clouds of words, where each instance’s size is proportional to its frequency in a related context
bars
(boolean): includes bar charts, histograms, and variants. It coincides with “bar charts” in [7] but with a more generic term to refer to all bar-based visualisations.
line_chart
(boolean): the display of information as sequential data points connected by straight-line segments.
area_chart
(boolean): similar to a line chart but with a filled area below the segments. It also includes density plots.
pie_chart
(boolean): circular graphs divided into slices which can also use multi-level solutions.
plot_3d
(boolean): plots that use a third dimension to encode an additional variable.
proportional_area
(boolean): representations used to compare values through area size. Typically, using circle- or square-like shapes.
other
(boolean): it includes all other types of non-temporal visualisations that do not fall into the aforementioned categories.
Temporal visualisations and encodings. In addition to non-temporal visualisations, a group of techniques to encode temporality is considered in order to enable comparisons with [7]. Columns:
timeline
(boolean): the display of a list of data points or spans in chronological order. They include timelines working either with a scale or simply displaying events in sequence. As in [7], we also include structured solutions resembling Gantt chart layouts.
temporal_dimension
(boolean): to report when time is mapped to any dimension of a visualisation, with the exclusion of timelines. We use the term “dimension” and not “axis” as in [7] as more appropriate for radial layouts or more complex representational choices.
animation
(boolean): temporality is perceived through an animation changing the visualisation according to time flow.
visual_variable
(boolean): another visual encoding strategy is used to represent any temporality-related variable (e.g., colour).
Interaction techniques. A set of categories to assess affordable interaction techniques based on the concept of user intent [8] and user-allowed data actions [9]. The following categories roughly match the “processing”, “mapping”, and “presentation” actions from [9] and the manipulative subset of methods of the “how” an interaction is performed in the conception of [10]. Only interactions that affect the visual representation or the aspect of data points, symbols, and glyphs are taken into consideration. Columns:
basic_selection
(boolean): the demarcation of an element either for the duration of the interaction or more permanently until the occurrence of another selection.
advanced_selection
(boolean): the demarcation involves both the selected element and connected elements within the visualisation or leads to brush and link effects across views. Basic selection is tacitly implied.
navigation
(boolean): interactions that allow moving, zooming, panning, rotating, and scrolling the view but only when applied to the visualisation and not to the web page. It also includes “drill” interactions (to navigate through different levels or portions of data detail, often generating a new view that replaces or accompanies the original) and “expand” interactions generating new perspectives on data by expanding and collapsing nodes.
arrangement
(boolean): methods to organise visualisation elements (symbols, glyphs, etc.) or
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Contained within the 3rd Edition (1957) of the Atlas of Canada is a map that shows six condensed maps illustrating the occurrence of important characteristics of farms. The two maps at the top show the distribution of part-time farms and occupied farms. Each of these two maps is accompanied by a pie chart showing percentage distribution of both classifications of farm operations for Canada by province. A third map shows the percentage of occupied farm lands that are occupied by owners. This map is accompanied by a chart showing the percentage of farmland, nationally and provincially, that is operated by an owner or manager. The fourth map shows the percentage of occupied farms reporting the availability of electricity and is accompanied by a chart showing percentages for Canada and each province. The fifth map shows the percentage of occupied farms reporting the usage of tractors. This map is also accompanied by a chart which shows the percentage of farms reporting tractors for Canada and each province. The sixth map, on the bottom right portion of this plate, shows the value of farm products sold per farm. These maps are based on data which was available as of the 1958 publication date of this atlas map.
http://standaarden.overheid.nl/owms/terms/licentieonbekendhttp://standaarden.overheid.nl/owms/terms/licentieonbekend
These pie charts show the distribution of biomass quantities (in percentage terms) per municipality in the following categories, roadside clippings, reeds and heaths, stems and leaves. The size of the pie chart shows the cumulative quantity. This dataset is used in the "biomass" map as part of the research into the natural capital in Overijssel.