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Who

Neil E. Klepeis and Wayne R. Ott launched the ExposureAnalysis.Org website in 2007 as a clearinghouse of freely-available curricular materials for instructors who teach Exposure Science. We welcome you to join ExposureAnalysis.Org as a student, instructor, or contributing author. If you are new to this field, you can learn about it by reading this website.

• Neil E. Klepeis, Ph.D., Consulting Assistant Professor of Civil & Environmental Engineering at Stanford University, has been studying exposure to inhaled pollutants for over 13 years. He has contributed considerable work in monitoring and modeling exposure to secondhand smoke.
• Wayne R. Ott, Ph.D., Consulting Associate Professor of Civil & Environmental Engineering at Stanford University, is a former USEPA scientist with over 40 years of experience in studying exposure to airborne pollutants. Dr. Ott was an original pioneer of the field of exposure analysis. He is the lead editor of the new textbook entitled "Exposure Analysis" (2007, CRC Press).

Why

The founders and contributors of ExposureAnalysis.Org have a strong interest in promoting the field of Exposure Science by attracting and training talented students. The field of Exposure Science is vital to identifying and understanding human health hazards, and in exploring approaches to reducing or eliminating health risks. While the field is growing rapidly, there remain few University courses devoted to Exposure Science, and few textbooks and other curricular materials are currently available. To encourage the development of new courses in Exposure Science and to assists instructors in designing and teaching these courses, we conceived the ExposureAnalysis.Org website as a clearinghouse and community forum for curricular materials in the field of Exposure Science. We have, as one of our main interests, providing free materials for those in developing areas around the world. Many students may not otherwise have the resources to access high-quality educational tools and information.

How

In conceptualizing the need for Exposure Science courseware, we realized that a collaborative effort would result in the most rich and diverse set of materials. We have envisioned ExposureAnalysis.Org as a place where scientists and instructors may contribute, using their own unique knowledge and expertise. In return, they can take whatever they need to develop a comprehensive curriculum for their own students. We hope to foster a large and eclectic community of instructors and scientists who can meet at ExposureAnalysis.Org to contribute, construct, and organize curricular materials for the benefit of present and future students.

Our adherence to Open Access and our use of an Open Source license are designed to fulfill our goals of benefiting human knowledge as a whole, regardless of geography or socioeconomic status, and of making sure our work continues to be distributed and improved, now and for as long as it is needed.

What

Most successful scientists in the field of Exposure Science possess advanced quantitative ability due to their training in traditional fields such as engineering, physical science, or biology. Hence, prospective scientists in this field need to develop good problem solving skills that make use of mathematics and computers. Most quantitative problem sets require a student to construct a basic MODEL OF REALITY. Although some models can be quite simple and based on idealistic assumptions, other models may try to mimic, or SIMULATE reality much more closely. Our main goal at ExposureAnalysis.Org is to facilitate prospective exposure scientists in gaining valuable EXPOSURE MODELING EXPERIENCE so they can explore and understand mechanisms of exposure.

The focus of this website is in developing problem sets that teach skills in data analysis and modeling, which are essential for a successful career as an exposure scientist. To support this central goal, we will be developing sophisticated software, with accompanying datasets, that can be executed online, or downloaded onto a user's own computer. Much of the software and data management will make use of the Open-Source R programming language, which is becoming the premier tool for statistics and data analysis in universities around the world.