GIS Day is an international celebration of geographic information systems (GIS) technology. The event provides an opportunity for users of geospatial data and tools to build knowledge, share their work, and explore the benefits of GIS in their communities. Since its establishment in 1999, GIS Day events have been organized by nonprofit organizations, universities, schools, public libraries, and government agencies at all levels.
Held annually on the third Wednesday of November, this year GIS Day is officially today. Happy GIS Day! CDVS has participated in Duke GIS Day activities on campus in past years, but with COVID-19, we had to find other ways to celebrate.
A (Virtual) Map Showcase
To mark GIS Day this year, CDVS is launching an ArcGIS StoryMaps showcase! We invite any students, faculty, and staff to submit a story map to highlight their mapping and GIS work. Send us an email at firstname.lastname@example.org if you would like to add yours to the collection. We are keen to showcase the variety of GIS projects happening across Duke, and we will add contributions to the collection as we receive them. Our first entry is a story map created by Kerry Rork as part of a project for undergraduate students that used digital mapping to study the English CivilWars.
Why Story Maps?
If you aren’t familiar with ArcGIS StoryMaps, this easy-to-use web application integrates maps with narrative text, images, and video. The platform’s compelling, interactive format can be an effective communication tool for any project with a geographic component. We have seen a surge of interest in story maps at Duke, with groups using them to present research, give tours, provide instruction. Check out the learning resources to get started, or contact us at email@example.com to schedule a consultation with one of our GIS specialists.
Felipe Álvarez de Toledo López-Herrera is a Ph.D. candidate at the Art, Art History, and Visual Studies Department at Duke University and a Digital Humanities Graduate Assistant for Humanities Unbounded, 2019-2020. Contact him at firstname.lastname@example.org.
Over the 2019-2020 academic year, I am serving as a Humanities Unbounded graduate assistant in Duke Libraries’ Center for Data and Visualization Sciences. As one of the three Humanities Unbounded graduate assistants, I will partner on Humanities Unbounded projects and focus on developing skills that are broadly applicable to support humanities projects at Duke. In this blog post, I would like to introduce myself and give readers a sense of my skills and interests. If you think my profile could address some of the needs of your group, please reach out to me through the email above!
My own dissertation project began with a data dilemma. 400 years ago, paintings were shipped across the Atlantic by the thousands. They were sent by painters and dealers in places like Antwerp or Seville, for sale in the Spanish colonies. But most of these paintings were not made to last. Cheap supports and shifting fashions guaranteed a constant renewal of demand, and thus more work for painters, in a sort of proto-industrial planned obsolescence.As a consequence, the canvas, the traditional data point of art history, was not a viable starting point for my own research, rendering powerless many of the tools that art history has developed for studying painting. I was interested in examining the market for paintings as it developed in Seville, Spain from 1500-1700; it was a major productive center which held the idiosyncratic role of controlling all trade to the Spanish colonies for more than 200 years. But what could I do when most of the work produced within it no longer exists?
This problem drives my research here at Duke, where I apply an interdisciplinary, data-driven approach. My own background is the product of two fields: I obtained a bachelor’s degree in Economics in my hometown of Barcelona, Spain in 2015 from the Universitat Pompeu Fabra, and simultaneously attended art history classes in the University of Barcelona. This combination found a natural mid-way point in the study of art markets. I came to Duke to be a part of DALMI, the Duke, Art, Law and Markets Initiative, led by Professor Hans J. Van Miegroet, where I was introduced to the methodologies of data-driven art historical research.
Documents in Seville’s archives reveal a stunning diversity of production that encompasses the religious art for which the city is known, but also includes still lives, landscapes and genre scenes whose importance has been understated and of which few examples remain [Figures 1 & 2]. But analysis of individual documents, or small groups of them, yields limited information. Aggregation, with an awareness of the biases and limitations in the existing corpus of documents, seems to me a way to open up alternative avenues for research. I am creating a database of painters in the city of Seville from 1500-1699, where I pool known archival documentation relating to painters and painting in this city and extract biographical, spatial and productive data to analyze the industry. I explore issues such as the industry’s size and productive capacity, its organization within the city, reactions to historical change and, of course, its participation in transatlantic trade.
This approach has obliged me to become familiar with a wide range of digital tools. I use OpenRefine for cleaning data, R and Stata for statistical analysis, Tableau for creating visualizations and ArcGIS for visualizing and generating spatial data (see examples of my own work below [Figures 3-4]). I have also learned the theory behind relational databases and am learning to use MySQL for my own project; similarly, for the data-gathering process I am interested in learning data-mining techniques through machine learning. I have been using a user-friendly software called RapidMiner to simplify some of my own data gathering.
Thus, I am happy to help any groups that have a data set and want to learn how to visualize it graphically, whether through graphs, charts or maps. I am also happy to help groups think about their data gathering and storage. I like to consider data in the broadest terms: almost anything can be data, if we correctly conceptualize how to gather and utilize it realistically within the limits of a project. I would like to point out that this does not necessarily need to result in visualization; this is also applicable if a group has a corpus of documents that they want to store digitally. If any groups have an interest in text mining and relational databases, we can learn simultaneously—I am very interested in developing these skills myself because they apply to my own project.
Help you consider potential data sources and the best way to extract the information they contain
Help you make them usable: teach you to structure, store and clean your data
And of course, help you analyze and visualize them
With Tableau: for graphs and infographics that can be interactive and can easily be embedded into dashboards on websites.
With ArcGIS: for maps that can also be interactive and embedded onto websites or in their Stories function.
Help you plan your project through these steps, from gathering to visualization.
Once again, if you think any of these areas are useful to you and your project, please do not hesitate to contact me. I look forward to collaborating with you!
As data driven research has grown at Duke, Data and Visualization Services receives an increasing number of requests for partnerships, instruction, and consultations. These requests have deepened our relationships with researchers across campus such that we now regularly interact with researchers in all of Duke’s schools, disciplines, and interdepartmental initiatives.
In order to expand the Libraries commitment to partnering with researchers on data driven research at Duke, Duke University Libraries is elevating the Data and Visualization Services department to the Center for Data and Visualization Sciences (CDVS). The change is designed to enable the new Center to:
Expand partnerships for research and teaching
Augment the ability of the department to partner on grant, development, and funding opportunities
Develop new opportunities for research, teaching, and collections – especially in the areas of data science, data visualization, and GIS/mapping research
Recognize the breadth and demand for the Libraries expertise in data driven research support
Enhance the role of CDVS activities within Bostock Libraries’ Edge Research Commons
We believe that the new Center for Data and Visualization Sciences will enable us to partner with an increasingly large and diverse range of data research interests at Duke and beyond through funded projects and co-curricular initiatives at Duke. We look forward to working with you on your next data driven project!
Interested in getting started in data driven research or exploring a new approach to working with research data? Data and Visualization Services’ spring workshop series features a range of courses designed to showcase the latest data tools and methods. Begin working with data in our Basic Data Cleaning/Analysis or the new Structuring Humanities Data workshop. Explore data visualization in the Making Data Visual class. Our wide range of workshops offers a variety of approaches for the meeting the challenges of 21st century data driven research. Please join us!
Data and Visualization Services is happy to announce its Fall 2015 Workshop Series. With a range of workshops covering basic data skills to data visualization, we have a wide range of courses for different interests and skill levels.. New (and redesigned) workshops include:
OpenRefine: Data Mining and Transformations, Text Normalization
Advanced Excel for Data Projects
Analysis with R
Webscraping and Gathering Data from Websites
Workshop descriptions and registration information are available at:
The lab features three distinct areas for supporting data driven research.
Data and Visualization Lab Space
Our lab space features twelve high end workstations with dual monitors with the latest software for data visualization, digital mapping, statistics, and qualitative research. All of the machines have two dedicated displays to encourage collaborative work and data consultations. Additionally, all twelve machines have a dedicated power port located conveniently under the edge of the table for powering a laptop or usb powered device.
Bloomberg Professional “Bar”
Since the launch of our Bloomberg terminals, we have seen a steady increase in both individual and team based usage of Bloomberg financial data. Our three Bloomberg Professional workstations are now located on a dedicated “bar” across from our lab machines. The new Bloomberg zone will facilitate collaborate work and provide a base for groups such as the Duke University Investment Club and Duke Financial Economics Center.
Consult and Collaborative Space
Our third lab space provides a set of four rolling tables for small groups to collaborate or for projects that don’t require a fixed computing space. An 85″ flat panel display near this zone features data visualizations and other data driven research projects at Duke.
Come See Us!
With ample natural light, almost 24/7 availability, and a welcoming staff eager to work with you on your next data driven project. We look forward to working with you in the upcoming year!
Explore network analysis, text mining, online mapping, data visualization, and statistics in our spring 2014 workshop series. Our workshops provide a chance to explore new tools or refresh your memory on effective strategies for managing digital research. Interested in keeping up to date with workshops and events in Data and GIS? Subscribe to the dgs-announce listserv or follow us on Twitter (@duke_data).
Data & GIS Services will soon be accepting submissions to its 2nd annual student data visualization contest. If you have a course project that involves visualization, start thinking about your submission now!
The purpose of the contest is to highlight outstanding student data visualization work at Duke University. Data & GIS Services wants to give you a chance to showcase the hard work that goes into your visualization projects.
Data visualization here is broadly defined, encompassing everything from charts and graphs to 3D models to maps to data art. Data visualizations may be part of a larger research project or may be developed specifically to communicate a trend or phenomenon. Some are static images, while others may be animated simulations or interactive web experiences. Browse through last year’s submissions to get an idea of the range of work that counts as visualization.
The Student Data Visualization Contest is sponsored by Data & GIS Services, Perkins Library, Scalable Computing Support Center, Office of Information Technology, and the Office of the Vice Provost for Research.
Would you like to add aerial photography or a topographic map underneath map layers for visual appeal or context? With ArcGIS 10, you can add a basemap to your map project.
A basemap is a link to an online imagery data source. You must be connected to the Internet in order to see a basemap.
Basemaps contain imagery at different levels of detail. When zooming in or out, new imagery will replace old imagery, which provides an approprate level of detail at any zoom level and improves performance by limiting the amount of information to be downloaded and displayed.
Export Map Packages
Sharing maps and shapefiles with others can be a pain when a map is composed of many shapefiles and layers. A map package bundles all shapefiles, layers, and map documents into a single file that can be opened by others with ArcGIS 10.
In ArcGIS 10, ArcToolbox tools default to background processing. This allows you to continue to work while the tool processes your data.
To disable background processing, navigate to the “Geoprocessing Options…” choice under the Geoprocessing Menu Bar, and uncheck the “Enable” box.
Search Toolbox Feature
Got a tool you want to use but can’t remember what toolbox its in? With the Search feature, you can easily locate what you need. Your search term can be the tool name or a close approximation of what you wish to do.
Easy to Use Time Data
Time series data became easier to use with ArcGIS 10. Version 10 recognizes time series data with the addition of a single time field.
For example, suppose you have annual precipitation for US cities. Your data will contain an ID field, a point field, a time field containing the year, and a field containing the precipitation amount.