Using ArcGIS, anyone can quickly make and share a map-but creating an effective map requires knowing a few design fundamentals. Enroll in this plan to learn techniques to appropriately symbolize and label map features, apply settings that enhance user interaction with your maps, and create impactful data visualizations that resonate with your intended audience.Goals Choose appropriate map symbols to represent your data. Create attractive labels to provide information about map features. Visualize data in 2D and 3D.

Description

This dataset contains a list of 186 Digital Humanities projects leveraging information visualisation techniques. Each project has been classified according to visualisation and interaction methods, 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.

Classification schema: categories and columns

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 information visualisation techniques employed within narrative structures. Here, the term narrative encompasses both author-driven linear data stories and more user-directed experiences where the narrative sequence is determined by 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, with regards to at least a visualisation, the following criteria are fulfilled: 1) avoid 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 simplifications to embrace and depict complexity, promoting time-consuming 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 (boolean): 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).

Interactions. A set of categories to assess affordable interactions based on the concept of user intent [8] and user-allowed perceptualisation data actions [9]. The following categories roughly match the manipulative subset of methods of the “how” an interaction is performed in the conception of [10]. Only interactions that affect the aspect of the visualisation or the visual representation of its 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): the organisation of visualisation elements (symbols, glyphs, etc.) or multi-visualisation layouts spatially through drag and drop or

This map visualisation service allows access to the set of information layers published in the Spatial Data Infrastructure of Navarra and that correspond to the public data of the SITNA. The Web Map Service (WMS) defined by the OGC (Open Geospatial Consortium) produces spatially referenced data maps, dynamically based on geographic information.

The 3D Visualisation Map (Non-textured models) are a set of digital data of 3D models featuring geometry models to represent the geometrical shape and position of different types of ground objects, including building, infrastructure and terrain. The dataset covers the whole territory of Hong Kong. You can click the link below to access the 3D Visualisation Map (https://3d.map.gov.hk).

3D Visualisation Map (2017)

This study presents data products to visualize past, current and alternate scenarios for an ecologically sensitive and development prone area in a sub-tropical coastal spit. Data products are created using a diverse range of geodesign tools that include existing and archived high resolution active and passive remote sensing datasets, existing, derived, and digitized spatial layers together with procedural modelling. The final products include 3d and interactive Cityengine Webscene files and fly-throughs in a generic movie format. While the fly-through movies can be played on standard digital devices, the Cityengine Webscenes once uploaded on ArcGIS website requires an Internet ready device for visualization and interaction.

The DC Office of Zoning (OZ) proudly announces an expansion of its online mapping services with the release of the DCOZ 3D Zoning Map. This new mapping application builds off existing DC Open Datasets and new OZ Zoning data to visualize the District in 3D, providing greater context for proposed development projects and helping enhance Board of Zoning Adjustment and Zoning Commission decisions throughout the District. The 3D Zoning Map was developed to enhance District resident’s understanding, knowledge, and participation in Zoning matters, and help increase transparency in the Zoning process.

Additional file 1. Perl script used for converting a contact map into an adjacency matrix based on the graphrepresentation in Fig. 1a.

Folium makes it easy to visualize data that’s been manipulated in Python on an interactive leaflet map. It enables both the binding of data to a map for choropleth visualizations as well as passing rich vector/raster/HTML visualizations as markers on the map. These files can be used to mark the state boundaries on the map of INDIA using folium library and the CSV also contains the state data and how to use it in our notebooks. I have used it in one of my kernels which can be viewed.

The library has a number of built-in tilesets from OpenStreetMap, Mapbox, and Stamen, and supports custom tilesets with Mapbox or Cloudmade API keys. folium supports both Image, Video, GeoJSON, and TopoJSON overlays. Due to extensible functionalities I find folium the best map plotting library in python. Do give it a try and use it in your kernels.

List of common proteins. List of the 252 proteins found in common between ACSN and ReconMap 2.0 maps (available at https://navicell.curie.fr/pages/maps_ReconMap 2.html ). (TXT 1 kb)

The 3D Visualisation Map (Tile-based models) are based on the mesh model made from the oblique aerial images. The dataset covers the whole territory of Hong Kong. You can click the link below to access the 3D Visualisation Map (https://3d.map.gov.hk/).

The dataset includes cartographic visualization data and software designed, implemented, and published for the ARCHITRAVE research project website. The research focused on the edition, executed in German and French, of six travelogues by German travelers of the Baroque period who visited Paris and Versailles. The edited texts are published in the Textgrid repository. For all further information on the content and objectives of the research, please refer to the website (https://architrave.eu/) and given literature. Three visualizations were created for the website: the travel stops of five of the travelers on their way to Paris and Versailles the sites in Europe mentioned in the six travelogues the sites in Paris described by the six travelers The visualizations were implemented with Leaflet.js. The dataset contains scripts for data crunching processed geodata scripts for leaflet.js License README

Crosstalks_network. Network of crosstalks based on shared proteins between modules of ACSN and subsystems of ReconMap 2.0 in TXT format. This file contains Source nodes, Target nodes, Interaction type and the number of intersection proteins corresponding to each edge. The file was used for visualisation of the crosstalks in Fig. 4 (available at https://navicell.curie.fr/pages/maps_ReconMap 2.html ). (TXT 9 kb)

Sensitivity maps made by the ODONAT Grand Est network in 2018-2019. The distribution of the species is based on recent occurrence data (1999-2018 or 2009-2018 by species). These are the natural regions in which at least one observation of the species has been made in the recent period as well as natural regions where the species is highly suspected (i.e. experts) or benefits from older data. In each of the natural regions with recent non-marginal observations, this presence is represented by the calculation of the proportion of meshes 1 x 1 km in which the species was observed. For an explanation of the method of calculation, refer to the explanation sheet of the Natural Regions maps. Natural regions identify territories in which abiotic conditions (relief, geology, climate...) are relatively homogeneous. In fact, the observation of a species in a natural region (even in one location) makes it possible to strongly assume the existence of other favourable habitats elsewhere in the natural region. Any comments shall be taken into account: these may be implanted populations, but also erratic individuals.

This layer represents the state of knowledge at the time of its realisation, it should not be considered exhaustive. The presence of the species outside the identified areas is possible.

Refer to the map reading instructions as well as PDF cards for more information.

Strategic noise maps are diagnostics of the noise exposure of populations in a territory. They make it possible to assess the exposure to noise of populations in the vicinity of major transport infrastructure and in large agglomerations. Departmental and national roads 4 index level: 50 to 75 decibels-55 to 75 decibels-65 to 75 decibels-70 to 75 decibels

The mapping of the hazard removal swelling of the clays in the municipality of Miélan in the department of Gers is extracted from the departmental cartography resulting from the BRGM. This mapping is a zoning of the probability of occurrence of the phenomenon of withdrawal-swelling of clay fields. A susceptibility map was first drawn up on the basis of purely physical criteria by BRGM from the geological maps of the department, which were interpreted taking into account the following factors for each geological formation: — the proportion of clay material within the formation (Lithological analysis); — the proportion of inflating minerals in the clay phase (mineralogical composition); — the geotechnical behaviour of the material. For each of the clay formations identified, the hazard level is ultimately the result of the level of susceptibility thus obtained with the density of shrinkage swelling, reported to 100 km² of outcropping area actually urbanised.

ReconMap2 GMT. Gene sets composing ReconMap 2.0 subsystems (available at https://navicell.curie.fr/pages/maps_ReconMap 2.html ). (GMT 21 kb)

The mapping of the hazard removal swelling of the clays in the municipality of Estramiac in the department of Gers is extracted from the departmental cartography resulting from the BRGM. This mapping is a zoning of the probability of occurrence of the phenomenon of withdrawal-swelling of clay fields. A susceptibility map was first drawn up on the basis of purely physical criteria by BRGM from the geological maps of the department, which were interpreted taking into account the following factors for each geological formation: — the proportion of clay material within the formation (Lithological analysis); — the proportion of inflating minerals in the clay phase (mineralogical composition); — the geotechnical behaviour of the material. For each of the clay formations identified, the hazard level is ultimately the result of the level of susceptibility thus obtained with the density of shrinkage swelling, reported to 100 km² of outcropping area actually urbanised.

In this project, we aimed to map the visualisation design space of visualisation embedded in right-to-left (RTL) scripts. We aimed to expand our knowledge of visualisation design beyond the dominance of research based on left-to-right (LTR) scripts. Through this project, we identify common design practices regarding the chart structure, the text, and the source. We also identify ambiguity, particularly regarding the axis position and direction, suggesting that the community may benefit from unified standards similar to those found on web design for RTL scripts. To achieve this goal, we curated a dataset that covered 128 visualisations found in Arabic news media and coded these visualisations based on the chart composition (e.g., chart type, x-axis direction, y-axis position, legend position, interaction, embellishment type), text (e.g., availability of text, availability of caption, annotation type), and source (source position, attribution to designer, ownership of the visualisation design). Links are also provided to the articles and the visualisations. This dataset is limited for stand-alone visualisations, whether they were single-panelled or included small multiples. We also did not consider infographics in this project, nor any visualisation that did not have an identifiable chart type (e.g., bar chart, line chart). The attached documents also include some graphs from our analysis of the dataset provided, where we illustrate common design patterns and their popularity within our sample.

The financially constrained element of Visualize 2045 identifies all the regionally significant capital improvements to the region’s highway and transit systems that transportation agencies expect to make and to be able to afford through 2045.For more information on Visualize 2045, visit https://www.mwcog.org/visualize2045/.To view the web map, visit https://www.mwcog.org/maps/map-listing/visualize-2045-project-map/.Download the ZIP file that contains a File Geodatabase