Ecology graduate programs are the source of the next generation of scientists who must anticipate the most pressing challenges accompanying environmental change, including biodiversity loss, depletion of natural resources, disease emergence and spread, and compromised ecosystem services. Ecologists who can meet this challenge require quantitative and data-science training to apply ecological data sets not only to hypothesis testing but also to forecasting future outcomes. This entails training ecologists to take full advantage of the enormous and heterogeneous ecological data sets that are being generated, to integrate them effectively, and to develop new analytical methods for predictive modeling. The University Program in Ecology is leveraging many of Duke’s initiatives in Data Science to produce ecologists with expertise in data science who can navigate both the domain science that generates the data and the computational arena of data science that analyzes, visualizes, and applies those data. Some of these initiatives are described below.
Use this tool to find collaborators in the Statistical Sciences Department and Data-Science programs to work with you to analyze and visualize your data. Post a description of your project by the deadline, review responses, and assemble an interdisciplinary team from Statistics and Data-Science to develop innovative analytical approaches to your Ecology data. You can also view projects posted by others, and make contact if you want to be involved! We use the MUSER interface. Use the project category “Data-Science Biology” to post your project and to browse other projects.
Data Expeditions supports graduate students to prepare data sets for undergraduate courses and for public dissemination. By doing so, students and faculty can integrate their own research into the undergraduate teaching curriculum, making teaching and research complementary and reinforcing activities. Here is an example of a UPE team’s project.
Data+ is a summer program that engages undergraduates interested in Data Science through vertically integrated teams with graduate students (one graduate student per 5-6 undergraduates for each team) to solve a problem using data-science tools, with a dataset provided by a Duke faculty â€œclientâ€ or external non-academic client. UPE students and faculty can apply to participate by proposing their own data challenge for the summer team to solve. Here is one example of UPE team’s project.
The Master in Interdisciplinary Data Science program (MIDS) hosts teams of MIDS student to collaborate on data challenges with Duke faculty. Teams of students work with faculty, graduate students, and/or external clients to solve a real-life data challenge using data that faculty, students, and clients are collecting. Graduate students can collaborate on these teams is they have a suitable data set and data-science challenge.
Story+ is a program hosted by the Franklin Humanities Center. It trains teams of students in the craft of storytelling. UPE students and faculty have participated in the program to find the narrative in their data and to experiment with presenting that narrative to diverse audiences. Cultivating storytelling skills is increasingly important for scientists, who need to communicate the relevance of their work, advocate for the scientific pursuit, and recruit future scientists into their disciplines. Learn more here.
Bass Connections offers support for interdisciplinary teams to conduct research that requires synthesis across disciplines and social groups, and to engage local communities, stakeholders and policy makers. Here is one example of a UPE team’s project.