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Mapping projects can be of all shapes and sizes, from the creation of a traditional figure with an explanatory legend and caption, such as might appear in an academic text, to an online interactive tool that allows for the searching or filtering of thousands of pieces of spatial data or hundreds of historical maps. They can combine different types of vector data representing real world features (e.g., points, lines, or polygons which can contain both spatial data and other qualitative or quantitative information) with raster (e.g., satellite imagery, elevation data, vegetation data, or a historical map).
Visualization, analysis, and storytelling are three of the most common goals for any mapping project, and they may be intertwined. Visualization focuses on the presentation of a collection of data, either through straightforward stylistic choices or through the ability to allow the user to filter datasets in some way. Spatial analysis is a process in which you model problems geographically, derive results by computer processing, and then explore and examine those results. Storytelling then combines the two, allowing the creator to present a cohesive narrative to their reader which is intrinsically tied to the data being presented at a particular moment.
BC Libraries' Digital Scholarship Group facilitates, supports, and consults on mapping projects, as well as designs and provides mapping related in-class instruction and workshops. BC's Research Services also provides support as well as licenses for platforms like ArcGIS.
The following questions are helpful to consider when beginning a mapping project. They are broken down into different sections based on different potential parts of a mapping project.
Note that some questions are good to consider in multiple contexts and that you do not need to be able to answer them all to get started. If you need assistance, contact BC's Digital Scholarship Group.
What are the goals for my project?
What is your research topic or subject focus?
Generally, where does my mapping project fit into the visualization - analysis - storytelling trifecta?
What is the timeline for my project?
What do I imagine the final product of my project might look like?
How can I obtain the data I need for my project?
Are you collecting your own data for your research or looking for data from a data provider (e.g. census or other governmental data)?
Are you dealing with vector data, raster data, both, or unsure?
Are you gathering spatial data from "pre-digital" sources, such as historical maps, that need to be digitized (the maps themselves and/or the spatial data inherent within the maps)?
Are you looking for spatial data for a certain time period or geographical focus?
Have you started searching for data sources? What are the most relevant ones?
How can I prepare my data to be used in a mapping tool?
What format(s) is your spatial data in (e.g. csv/spreadsheet, shapefile, kml, geojson, etc)?
Do you need to add qualitative or quantitative data to your vector data?
Do you need to clean your data (i.e. make the spatial data internally consistent, fix errors within the attributes of the data, etc)?
Do you need to merge your data (i.e. bring together or combine multiple data sources into one source that contains spatial data, possibly with different attributes or information attached)?
How do I want people to be able to see or engage with my data?
How much data do I have, and is it divided into multiple layers or types?
How do I imagine users engaging with my data (as a pre-created fixed figure, as an interactive map, etc. Also see Sharing below)?
How can my visualization emphasize the argument I am trying to make with the spatial data? What is the main idea I want to convey to my audience?
Is spatial analysis part of my mapping project goals?
What question am I trying to answer with spatial analysis (i.e. what kind of spatial analysis am I trying to do)?
Do I have the necessary data to answer the question I am exploring?
What GIS tool is most appropriate for me to use to answer that question, and do I have access to it (QGIS/GrassGIS/ArcGIS)?
Is storytelling (e.g. a StoryMap, a GeoTour, etc) a part of my project goals, where the spatial data integrated into a larger interactive narrative with different kinds of media?
Do you have any preferred StoryMapping tool to use (Knightlab, ArcGIS online, etc.) or do you need help with choosing the visualization tools?
Do you have a general outline of how viewers will move through your story?
What kinds of media do you want to integrate with your story (text, images, audio, video, etc)?
What kind of mapping output is ideal for my project (static figure online or printed, interactive online figure, etc.)?
How will my map be tied to my larger narrative (if desired)?
Where should my spatial data and map project appear/be hosted/preserved? Will it be accessible to the general public?
Will others be able to download my spatial data to work with on their own projects?
While raster data can be stored in many different formats, GeoTIFF is one of the most common. GeoTIFF is a standard .tif image that also contains spatial data (e.g., coordinates and projections) and attributes. In general, however, any standard image (e.g., jpeg), if given proper spatial data, a practice called georeferencing, can act like a raster file.
Vector data includes data in the form of points, lines, and polygons along with any connected attributes. This type of data can come in several different formats, such as GeoJSON, CSV, and KML. Below you can see an array of data formats (found in Boston Open Data), GeoJason, CSV, KML, Shapefile, ESRI Rest API, and ArcGIS Hub Dataset. All contain the same food truck information:
While most platforms allow for some interoperability (the ability to work with several file formats), it is helpful to understand the basic distinction between them.
A CSV (comma-separated value) file is one of the most well-known formats for both spatial and non-spatial data and is created by using commas to separate each value of an attribute, with each line of the file equal to a single data record. If we return to thinking about structured data sets, comma-separated value file simply puts a comma in between attribute value, returning an output that looks something like this:
CSV data is useful simply because it is easy to create and manipulate in software like Excel or GoogleSheets, and these programs often allow you to export your data as a CSV to make it more interoperable. It is also easy to transform a CSV file into other formats, like GeoJSON, making it an easy "go-to" for sharing spatial data
CSV files are especially useful if you simply have a collection of point data. A file of this kind, sometimes called "XY data" or "long/lat data" can be easily imported into software like ArcGIS or QGIS in order to visualize it. (Note that it will not have any attributes).
GeoJSON is an open standard format for spatial data based on the JSON file format, which includes spatial information (points, lines, polygons) along with other qualitative and quantitative attributes. If you are using Python, a coding language, or platforms like Leaflet to manipulating spatial data, a GeoJSON export is probably your best choice.
The example below is a selection of GeoJSON data. It is organized similarly to the well-known CSV, with each feature containing a series of attributes, including (in this case) the geometry for point data, latitude, and longitude values for where the food truck will be located.
It's worth noting that there are tools for converting CSV to GeoJSON and vice versa.
A KML file (Keyhole-Markup-Language) is an open standard spatial data format most commonly associated with displaying geographic data in an Earth browser such as Google Earth. Although not necessarily as easily compatible with other platforms such as ArcGIS or Leaflet, there are a variety of conversion tools and plugins built-in within these platforms that may help ease the process.
A Shapefile is a simple format for storing the geometric location and attribute information of geographic features represented by points, lines, or polygons (areas), and is most commonly associated with ESRI's ArcGIS program suite. From within ArcGIS/QGIS, you may then export it as other file types, though this sometimes requires purchasing the Interoperability extension.
: A traditional GIS analysis undertaken using ArcGIS Desktop (BC Library 2021 GIS Contest Winner); Main Goal: Data Analysis, Data Visualization; Platform: ArcGIS
: An interactive version of a traditional GIS visualization map, focused on an archaeological site outside of Rome, Italy; Main Goal: Data Visualization; Platform: Leaflet, ArcGIS
: The Authorial London project is compiling and mapping references to London places found in the works and biographies of writers who have lived there; Main Goal: Data Visualization (raster through historical maps, vector through location references); Platform: Leaflet/Mapbox (within a larger developed application)
: Artists in Paris is the first project to map comprehensively where artistic communities developed in the eighteenth-century city and offer rich scope for subsequent investigations into how these communities worked and the impact they had on art practice in the period; Main Goal: Data Visualization and Filtering; Platform: Openlayers (within a larger developed application).
: Mapping the Gay Guides aims to understand often ignored queer geographies using the Damron Address Books, an early but longstanding travel guide aimed at gay men since the early 1960s. Similar in function to the green books used by African Americans during the Jim Crow era to help identify businesses that catered to black clients in the South, the Damron Guides aided a generation of queer people to identity sites of community, pleasure, and politics. Main Goal: Data Visualization and Filtering; Platform: Leaflet within larger developed application.
: A clever use of an ArcGIS Online Story Map to discuss the use of spatial analysis in ArcGIS; Main Goal: Storytelling, Data Analysis; Platform: ArcGIS Online
This Interactive Atlas allows you to create and customize county-level maps of heart disease and stroke across the United States; Main Goal: Data Analysis, Data Visualization; Platform: ArcGIS Online
: This animated thematic map narrates the spatial history of the greatest slave insurrection in the eighteenth century British Empire; Main Goal: Storytelling; Platform: Leaflet
: An interactive, multimedia storymap detailing Arya's movements across the Game of Thrones books; Main Goal: Storytelling; Platform: Knightlab Storymaps
The following examples of vector and raster data demonstrate some of the many forms the data can take.
Vector data in mapping generally appears either as points, lines, or polygons. In this example of polygons as raster data, spatial information tied to the data defines the shape's boundaries while further information (such as a title and image) is included as additional attributes. Attributes can include any type of additional information that is useful for a viewer to know about a particular location appearing in your dataset.
A basemap is a georeferenced raster image. They help give a larger context to vector data sets, which would otherwise simply appear as points, lines, or polygons on a blank space. Satellite imagery and other top-down images (orthophotos) are the most common raster data of this kind, seen, for example, when using satellite imagery from GoogleMaps as seen below.
Raster thematic maps are similar to surface maps as they use attributes of a particular landscape, be they physical or cultural. Combining several types of data to create what are called thematic data sets, thematic maps group together certain specified attributes from vector or raster data into specific categories, and then mapping out the categories.
The example below shows vegetation types from a dataset that breaks land-cover types into categories. The data is multispectral, meaning it is the acquisition of reflected wavelength data in the visible, near infrared, and short-wave infrared spectrums.
Raster surface maps contain attributes that mark change over a particular landscape instead of representing the visual world as basemaps do. Common attributes indicated on surface maps include elevation (which is specifically termed a digital elevation map, or DEM), rainfall, or temperature. Once these types of surface maps are imported into a GIS platform like ArcGIS or QGIS, they can be .
Introduction to Mapping discusses fundamental concepts that inform spatial data related research, the use of GIS tools, and mapping project creation. While the focus in this section will be on spatial data based maps (i.e., GIS), it is important to note that simple maps can be created in tools like Knighlab StoryMaps, Google MyMaps, and even ArcGIS Online without sophisticated data. In this case, marks are made on maps using things like "pins" and "notes" that can either be added by searching coordinates or manually placing them on a designated image.
Integrating mapping methods into a DS project can offer a variety of helpful advantages in terms of visualization, storytelling, and analysis. Mapping can make complex information and arguments more digestible to the average reader, combining a multitude of information into a single comprehensible figure. It can also help an author tell a story with their data, guiding the viewer around a landscape as the story unfolds with tools such as Knightlab Storymaps. Finally, it opens the door to more specialized spatial analysis through the use of programs like ArcGIS or QGIS, taking advantage of modern computing to reinforce an academic argument to an audience.
The concept of data is discussed more broadly in Introduction to Data. Here we take a quick look at spatial data in particular. In short, spatial data adds a geographic dimension to a qualitative and/or quantitative data set, situating it in a particular location within a coordinate system relative to other data points. (The coordinate system can be a real-world system or a locally created one used to meet the needs of a particular project.)
For example, the project, Mapping Islamophobia, demonstrates how geospatial data can be combined with other data points (i.e., date, gender, and type of incident). Collectively, the data brings to light, from a geospatial perspective, trends in hostility and hate toward Muslim Americans.
The following represent questions that would benefit from a spatial data-oriented analysis and DS mapping methods.
How has the spatial patterning or characteristics of Hmong immigration to Minneapolis–Saint Paul changed over time?
Where in the city has the increased number of health clinics had the greatest impact on reducing diabetes-based illnesses? How does this data correlate with race and economic status?
How do characters in War and Peace move around a physical environment over the course of the book, and how does this connect with larger themes?
How are historical monuments clustered in downtown Boston in comparison to other major cities?
How can we visualize the movement of Jesuit missionaries travel over the course of the 18th century?
Spatial datasets, in general, come in two distinct forms, vector data and raster (or pixel data). Raster and vector data can come together in the creation of a wide variety of mapping projects, from a traditional figure with an explanatory legend and caption, such as might appear in an academic text, to an online interactive platform that allows for the searching or filtering of thousands of pieces of spatial data or hundreds of historical maps.
Vector data includes points, lines, or polygons (shapes made up of straight lines) containing spatial information that represent some sort of feature or event in a physical or imagined landscape and may contain other types of qualitative or quantitative information, called attributes. A point may represent a tree, a city, or a moment in time. Lines might indicate the street grid of a town, the path someone traveled across the world, or a social link between two communities. Polygons can mark the boundaries of a country or voting district, the catchment area of a river, or a single city block.
Raster consists of "cells" of data covering a specific area (its extent), with attribute values in each cell representing a particular characteristic. It may still consist of points, lines, and polygons, but these shapes are themselves composed of pixels (the way a jpeg or other image file type is).
Data of this type may take many forms, such as satellite imagery containing vegetation or elevation data, precipitation maps, or even an historical map, which has been given a spatial reference. Unlike vector data, raster data has a particular resolution, meaning each pixel represents a particular geographic region of a specific size.
Depending on your goals, there are a wide variety of pre-built platforms that are useful for visualizing, analyzing, and telling stories about spatial data. Below are some common platforms, starting with ones with the generally lowest level learning curve and moving to the highest.
StoryMapJS, a free online tool developed by Northwestern University's Knight Lab, allows creators to combine spatial information with multimedia and textual data to tell location based narratives. Its simple user interface and ability to use both standard and customized underlays make it a good platform for simple story-mapping projects. Its limitations include the fact that it cannot be hosted locally and little customization in terms of styling or functionality is possible. Spatial data points must also be inserted individually either on a map or through long/lat coordinates, making work with large datasets difficult.
Main use: Storytelling, Access: Free, requires a Google account
seen below combines text, video, and images to highlight how Chicago's dialogue with classical antiquity has shaped the city's look, reputation, and identity.
Main Use: Storytelling, Simple Visualization, Access: Free, requires a Google account
With Tableau, you can create the following common map types:
is ESRI's free online data visualization tool and can be integrated directly with ArcGIS Desktop or Pro. It is possible to create a free personal account or to join the Boston College account system by contacting .
While ArcGIS Online can be useful for making simple interactive maps, where it really shines is in its storymapping functionality. Like Knight Lab StoryMapJS, allow you to create inspiring, immersive stories and tours by combining text, interactive maps, and other multimedia content. ArcGIS Online, however, is a much more flexible platform, allowing creators to present their data in a wider variety of formats and utilize a wider variety of map types. Its learning curve is steeper than Knight Lab's StoryMaps and it requires the user to have a greater understanding of how they want to organize and share their spatial data.
Main Use: Storytelling, Data Visualization, Access: Free version available, also available to BC faculty, staff, and students
from BC student Wenwei Su won the 2020 Boston College Libraries GIS Contest (digital division) for looking at health care expenditures and mortality rates in the US through the lens of the movie "Dying to Survive." (For more examples, check out the .)
The free tool (available for use online or for download to mobile and desktop) is a common tool for creating simple maps with points, lines, and polygons to share with others. The program maps the Earth by superimposing satellite images, aerial photography, and GIS data onto a 3D globe, allowing users to see cities and landscapes from various angles.
The new allow you to create a "story map" experience by adding items such as images and videos into location descriptions. It is possible to share your creation in the cloud (through standard google sharing methods) or download your spatial data as a .kml file to open on a variety of platforms.
The uses historical photographs, artwork, Google street views, and satellite imagery to tell the story of Henry Box Brown, an enslaved person who shipped himself from Virginia to Pennsylvania to obtain his freedom.
is a data visualization and analytics platform that enables users to connect to a variety of data sources and explore the data in a simplified way. The drag and drop interface makes it very easy to visualize and create interactive dashboards without any programming skills. The mapping features of Tableau Desktop give users the ability to get the answers to spatial questions. Tableau's spatial file connector allows you to easily connect to and join Esri Shapefiles, KML, MapInfo tables, GeoJSON files, and other forms of geospatial data. You can also import geographic data from R or GIS (or whatever or you have) and make it more easily accessible, interactive, and shareable. Census-based population, income, and other standard demographic datasets are built-in.
Main Use: Data Visualization, Access: is a free version available to the general public, a free version of can be acquired by academic faculty, staff, and students (see )
The example map below from the project, , shows the foreign-born population around the Boston area community from 1870 to 2010.
ArcGIS and QGIS are the two most common platforms for organizing your data into a true database and for analyzing data using common spatial methodologies. As such, they are often the go-to for someone wanting to move beyond an Excel or Google Sheet file for recording their datasets. The two platforms are similar, though only runs on Windows computers while is a free and open source GIS platform that runs on Windows and Macs. While both platforms can be used for sharing visualizations as exports in traditional file formats such as .jpg and .tiff (commonly used in publications), sharing interactive online visualizations requires integration with a secondary platform like ArcGIS Online or Leaflet.
Boston College has an ArcGIS campus license for students, faculty, and staff, so please see the for more information on how to get a license for your computer. Both platforms are available for use in the . If you just want to start from the basics in ArcGIS or QGIS, we recommend running through a few of the beginner tutorials from the or the .
Main use: Spatial Organization, Spatial Analysis, Spatial Visualization, Access: are available to BC faculty, staff, and students; QGIS is free and open source, download from
is an open-source JavaScript library for interactive web maps. It is lightweight and flexible and is probably the most popular open-source mapping library at the moment. Of the web mapping platforms discussed here, it is certainly the most powerful, but at the same time is the least user friendly, as a knowledge of coding in javascript is required. Many types of functionalities may be performed more easily using the other platforms described above, yet Leaflet (especially with its many plugins) is by far the most customizable.
Main use: Data Visualization, Access: Free and open source, download from
The example map below is an Leaflet based map from the Institute for Advanced Jesuit Studies (IAJS) Jesuit Online Necrology Project, which the lives of more than 33000 members of the Jesuit Priesthood. The map shows the myriad of locations mentioned in the necrology, allowing the user to search by location and identify the Jesuits associated with a location.
