About Us
OUR WORK
In an age of abundant data, there's a widening gap between the availability of ecological and related data and the skills to utilize it. To address this, our project, Data4Ecology.org, aims to integrate computing, statistics, and data science into undergraduate ecology curricula. We are striving to foster computational and statistical reasoning skills among students and professionals in ecology and allied STEM disciplines, equipping them to tackle complex problems in ecology and data science.
Our platform is a virtual ecosystem where we curate, assemble, and embed a wide range of open educational and learning resources. This ecosystem not only serves as a training ground for undergraduate students in ecology and environmental science across various institutions but also facilitates the creation, sharing, and enhancement of these resources in a collaborative manner. We offer a diverse set of resources, from prebuilt lessons to customizable assets, each adaptable to cater to unique educational needs. In doing so, we aim to build a robust community of researchers, educators, and students, who can mutually benefit from a dedicated repository of data-centric ecology data, resources, and curriculum.
Utilizing interactive features, such as instant grading, question-specific hints, and real-time learning charts, our platform strives to make the learning process more engaging and effective. Additionally, we provide a multitude of assessment types to give educators flexibility in designing comprehensive assessments. This approach, coupled with a wide variety of practical datasets and efficient teaching tools, ultimately shapes Data4Ecology.org into a transformative hub for ecological education, driving the evolution of undergraduate curricula.
PROJECT TEAM
The Data4Ecology project team, working in conjunction with our external evaluators, aims to ensure that all project goals and objectives are met. Their expertise and responsibilities are listed below:
Benjamin Galluzzo, Ph.D., will serve as the project’s PI. Galluzzo is an Associate Professor at Clarkson University and is the Associate Director of Clarkson’s Institute for STEM Education where he researches new strategies and best practices for bringing active learning into K-16 STEM classrooms. He has designed and facilitated over 40 professional development workshops for teachers and is active in developing an applied mathematics education community. As PI of the NSF-funded Undergraduate Sustainability Experiences in Mathematics, Dr. Galluzzo has been involved in the development of over 30 sustainability-themed, technology-based modules for introductory level (Algebra through Calculus) math courses. He is a co-author of the Guidelines for Assessment and Instruction in Mathematical Modeling Education (GAIMME) Report and two other textbooks on mathematical modeling and has been honored with national teaching awards. He currently serves as Chair of the NCTM/SIAM/COMAP Joint Committee on Modeling across the Curriculum and is co-PI on the CodeR4MATH: Computing with R for Mathematical Modelling ($1,850,959, DRL-1742083) grant that seeks to integrate R-based mathematical modeling activities into high school math and statistics classes.
Naupaka Zimmerman, Ph.D., will serve as a project Co-PI. Zimmerman is a computational ecologist with training and expertise in microbial ecology and biogeochemistry. He has been an Assistant Professor in the Biology Department at the University of San Francisco, a primarily undergraduate institution, for the past four years, where he has designed and implemented inquiry-based courses in Ecology, California Ecology (for non-majors), Microbiology, Bioinformatics, and Urban Ecology. All of the courses are project-focused and have incorporated the use of R and Rmarkdown; several have directly incorporated NEON data accessed via the API. Outside of USF, he has 8 years of experience designing, implementing, and teaching workshops on computational and quantitative skills to scientists at all levels from high school through to senior researchers and faculty. He has taught these workshops both as an instructor, lesson maintainer, and instructor trainer for the Carpentries (Software and Data Carpentry), as well as independently through workshops at local institutions and at annual professional meetings (ESA, INTECOL). He is a co-author of two R packages on CRAN (forestr, described in Atkins et al. 2018 Methods in Ecology and Evolution; and pangaear, a data retrieval package for the PANGAEA environmental science data repository) and has served as a formal peer code reviewer for the ROpenSci project. Zimmerman will work with the project team on curricular development, site design, broadening participation efforts, and outreach to promote the usage of project materials in undergraduate and graduate classrooms.
Eric Simoneau will serve as a project Co-PI. Simoneau is currently serving as PI of the development subaward for the NSF-funded STATS4STEM: Code R for AP Statistics ($563,835, DRL-1418163) grant that looks to integrate R computing into high school statistics classes. During the STATS4STEM project, Mr. Simoneau has been able to continuously build the STATS4STEM.org learning and community platform from the ground up to the point where the platform supports over 1,400 registered statistics teachers nationwide. Furthermore, Eric is currently co-PI on the CodeR4MATH: Computing with R for Mathematical Modelling ($1,850,959, DRL-1742083) grant that seeks to integrate R-based mathematical modeling activities into high school math and statistics classes. Eric has taught math and statistics courses over the past 12 years at Boston Latin School in Boston, Massachusetts. Over the last 7 years, he has exclusively taught AP and non-AP statistics. In addition, he has taught introductory statistics courses at North Shore Community College. Prior to working as a teacher, Eric worked four years as a manufacturing engineer for Teradyne, Inc. Mr. Simoneau holds an undergraduate degree in Mechanical Engineering from the University of Illinois at Urbana-Champaign, an M.A. in Mathematical Finance from Boston University, and an M.S. in Statistics from the University of Massachusetts at Amherst.
Jeffrey Oliver, Ph.D., will serve as a project consultant. Dr. Oliver is the Data Science Specialist at the University of Arizona Libraries. He supports campus scholarship through workshops on data analyses and visualization. He also consults on software development with researchers from a variety of domains, including the humanities and social, life, and physical sciences. He also coordinates larger campus efforts towards data science literacy, including a graduate fellowship program and a cross-disciplinary, grassroots effort driving improvements in data science resources and training opportunities. His background is in life science research and open-source software development.
Katy Prudic, Ph.D., will serve as a project consultant. Dr. Prudic is an expert in biodiversity informatics, citizen science, and data science, and is the chair of the UA Data Instructional Group Faculty Learning Community for the College of Agriculture. She instructs both undergraduates and graduates on R programming and research computing-related to biodiversity and conservation research. She also co-created a continental citizen science project called e-butterfly.org with over 10 years of experience implementing data science projects across institutions and disciplines.