Atefeh Maleki Aigerim Zhalgasbekova

1. Programmatic and Institutional Opportunities to Enhance Computer Science Research for Sustainability Atefeh Maleki Aigerim Zhalgasbekova

2. Contents • Introduction • How computer science can address sustainability ? • Researches toward sustainability Vs. universality • How can a multidisciplinary approach influence on education in computer science? • How to evaluate the impact? • Conclusion

3. Introduction • Potential impediments to make significant progress to sustainability • Bridging the gap between the traditional research quest for universality and imperative to have a specific impact on sustainability challenges • The challenge of universality • Need in bottom-up approach • Connection between the universality, bottom-up approach and sustainability • Methodological opportunities for optimizing research outcomes and impacts

4. How computer science can address sustainability ? CS and IT can make a great contribution to sustainability issues. Examples of contribution of CS fundamentals to sustainability: • Abstraction design • Algorithms • Operating systems • Real-time systems • Machine learning • Human computer interaction (HCI) • Databases >> queryable structured data & strides to cope with the unstructured data

5. An example: system’s Architecture The system’s architecture provide design decisions and can significantly affect all aspects of the uses and behavior of the system over its life cycle. Therefore, the architecture of a system in a larger scale or broader as global scale can help to address sustainability issues.

6. Researches toward sustainability Vs. universality The most powerful and important computer science innovations to date share the characteristic of universality. Much of theoretical computer science, of course, begins by representing the target problem in abstract, symbolic language. Research with universality we can name : • programming languages such as Fortran and ALGOL, • human-factors research that created new modes of human computer interaction

7. Bottom-up approach CS research on sustainability is best approached from the bottom up: that is, by developing well-structured solutions to particular, critical problems in sustainability and later seeking to generalize these solutions. World Wide Web : originally conceived as a means to share research papers and scientific information object-oriented programming : early object-oriented languages were developed to address specific problems such as discrete event simulation or graphical interaction.

8. Why does bottom-up approach suit addressing sustainability issues ? Many sustainability challenges need to be addressed sooner rather than later, even if imperfectly. The fact that the problems associated with sustainability are complex, multifaceted, and in some cases poorly defined means that close attention to experimental robustness and underlying mathematical rigor will be essential. Example; smart grid, language translation, Internet protocols, machine learning, object-oriented languages, and databases.

9. Developing software is not done through implementing a perfect software system at the start. Software technology is developed, deployed, used, and modified in continuous iterative cycles and it is designed to be updated on a frequent basis over its entire life cycle.

10. CS researchers and practitioners should experiment with, apply, and pilot solutions to specific problems; look for the successes and reapply and adapt them to other applications; and develop universality while seeking to increase applicability and impact.

11. How can a multidisciplinary approach influence on education in computer science? • The change in education should include educating to achieve impact with: • Computing • Computational methods • Systems approaches • Requirements to successfully shift: • Culture experimentation • Innovation in the application of computer science • Research infrastructure: • Available standard data sets, models, and challenge problems to the community • The building of shared infrastructure through open architectures and testbeds

12. Principle of multidisciplinary approach Undergraduate and graduate education in computer science should provide experience in working across disciplinary boundaries. Graduate training grants and postdoctoral fellowships should support training in multiple disciplines. Undergraduate and graduate programs should include tracks that offer introductory and intermediate course work in such sustainability areas as life- cycle analysis, agriculture, ecology, natural resource management, economics, and urban planning.

13. Examples of opportunities to enhance multidisciplinary approaches • The creation of certicate programs, extension programs, and online programs for professionals • Scholarships and fellowships • The development of cross-agency initiatives • Support for the development of new, cross-discipline structures • Institutional structures that support multidisciplinary and interdisciplinary teams • Internships and career paths and placement programs • Coordination between academic research in computer science and non-traditional industrial partners • Regular, high-level summits involving computer science and sustainability experts

14. Principle of funding and programs Refine funding and programmatic options to reinforce and provide incentives for the necessary boundary crossing and integration in CS research to address sustainability challenges. In particular, funding, promotion, and review and assessment (peer review) models should emphasize in-depth integration with data and deployments from the constituent domains.

15. Effects of bottom-up approach • Researchers - how researchers select and approach their problems and how they approach the training of their students; • University systems - how universities incentivize and create the infrastructure for faculty to pursue sustained multidisciplinary efforts; • Funding agencies - how agencies structure multidisciplinary programs.

16. Principle of strong incentives There should be strong incentives at all stages of research for focusing on solving real problems whose solution can make a substantial contribution to sustainability challenges, along with in-depth metrics and evaluative criteria to assess progress.

17. How to evaluate the impact? • Specific metrics: • Metrics for analysis of environmental impact; • Metrics for analysis of economic impact; • Metrics for equity and engagement across different stakeholder groups. • Scale analysis: • Spatial scaling; • Temporal scaling; • Location scaling; • Computational scaling.

18. Conclusion • Computer science research in sustainability as interdisciplinary effort • A bottom-up approach leading to more universally useful contributions • Introduction of multidisciplinary approach to education institutes • Validation metrics for assessment the impact on sustainability