offered at a level to attract a broad collection of students from outside the natural
sciences and engineering. A similar course which focuses on the interdisciplinary nature
of challenges posed by sustainability at a more advanced mathematical level could
provide a “capstone” experience, drawing together an array of students from science,
technology, engineering, and mathematics disciplines. Sustainability programs also
provide a natural context for mathematical scientists to collaborate with faculty from
other disciplines in developing brief modules that illustrate quantitative approaches to
practical issues potentially useful as short components in a wide variety of
undergraduate science offerings.
4.2. Data sharing
To engage a broader community of mathematical scientists in studying problems
of sustainability, an effective approach is through the sharing of data.
For many mathematical researchers as well as students, an introduction to a new
application area comes from reading about a specific problem in a paper or research
article. Taking that introduction to the next level involves the generalization or
improvement of the approach.
Having access to the data sets for relevant aspects of the human and
environmental disciplines is an excellent way to facilitate entry for mathematical
researchers not presently engaged in the area. Indeed, new ideas can be tested and
benchmarked against existing approaches, as more data becomes available to a larger
public of scientists. A broader community of researchers involved in the modeling of
sustainability sciences will have multiple benefits, from greater visibility by the public of
the issues themselves, to new and potentially better mathematical approaches for
solving existing problems, to tackling more complex and far-reaching issues in those
areas.
Making data sets available to the community can be done in both a centralized
and a decentralized manner and most likely both approaches are needed. Centralized
approaches would include the various professional societies hosting a website repository
either for the data sets themselves or for links to data sets stored elsewhere.
Decentralized approaches include individual researchers or university
departments/laboratories hosting such websites or via the various social networking
platforms.
The data sets in question should be broad and cover aspects central to
traditional areas of sustainability science as well as those presently on the fringes.
Examples of data from the traditional areas include those covered in this document:
fishery data, historical weather (climate) data, consumption levels, reported forest fires
and their characteristics over time, rainfall, sea levels, and other environmental variables
covering numerous parts of the world, over significantly long time periods.
Furthermore, studying the above factors in the context of other human-
environmental systems is particularly important for moving sustainability science forward
and for drawing in more mathematical researchers. Examples of data sets from outside
these core areas include human land-use data such as is used in economic studies,
water and energy distribution networks and their characteristics, water and energy
consumption levels and system failures, etc, transportation-related data such as network
connectivity, travel demands and costs, and health-related data such as incidence of
various diseases over time and in different locations across the country and the world.