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Abstract

The innovative science of the future must be multi-domain and interconnected to usher in the next generation of “self-driving” laboratories enabling consequential discoveries and transformative inventions. Such a disparate and interconnected ecosystem of scientific instruments will need to evolve using a system-of-systems (SoS) approach. The key to enabling application integration with such an SoS will be the use of Software Development Kits (SDKs). Currently, SDKs facilitate scientific research breakthroughs via algorithmic automation, databases and storage, optimization and structure, pervasive environmental monitoring, among others. However, existing SDKs lack instrument-interoperability and reusability capabilities, do not effectively work in an open federated architectural environment, and are largely isolated within silos of the respective scientific disciplines. Inspired by the scalable SoS framework, this work proposes the development of INTERSECT-SDK to provide a coherent environment for multi-domain scientific applications to benefit from the open federated architecture in an interconnected ecosystem of instruments. This approach will decompose functionality into loosely coupled software services for interoperability among several solutions that do not scale beyond a single domain and/or application. Furthermore, the proposed environment will allow operational and managerial inter-dependence while providing opportunities for the researchers to reuse software components from other domains and build universal solution libraries. We demonstrate this research for microscopy use-case, where we show how INTERSECT-SDK is developing the tools necessary to enable advanced scanning methods and accelerate scientific discovery.

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Notes

  1. 1.

    HashiCorp’s Terraform: https://www.terraform.io/.

  2. 2.

    See https://github.com/GoogleCloudPlatform/terraform-folding-at-home.

References

  1. Bartlett, R., Demeshko, I., Gamblin, T., et al.: xSDK foundations: toward an extreme-scale scientific software development kit. Supercomput. Front. Innov. 4, 69–82 (2017)

    Google Scholar 

  2. Baxter, S.M., Day, S.W., Fetrow, J.S., Reisinger, S.J.: Scientific software development is not an oxymoron. PLOS Comput. Biol. 2, 1–4 (2006)

    Article  Google Scholar 

  3. De Bayser, M., Azevedo, L.G., Cerqueira, R.: ResearchOps: the case for DevOps in scientific applications. In: Proceedings of the 2015 IFIP/IEEE International Symposium on Integrated Network Management, IM 2015, pp. 1398–1404 (2015)

    Google Scholar 

  4. Brassil, J., Kopaliani, I.: Cloudjoin: experimenting at scale with hybrid cloud computing. In: 2020 IEEE 3rd 5G World Forum (5GWF), pp. 467–472 (2020)

    Google Scholar 

  5. CADES. CADES OpenStack cloud computing (2022)

    Google Scholar 

  6. Cataldo, M., Mockus, A., Roberts, J.A., Herbsleb, J.D.: Software dependencies, work dependencies, and their impact on failures. IEEE Trans. Software Eng. 35(6), 864–878 (2009)

    Article  Google Scholar 

  7. Crawford, K., Whittaker, M., Elish, M.C., Barocas, S., Plasek, A., Ferryman, K.: The AI now report. The Social and Economic Implications of Artificial Intelligence Technologies in the Near-Term (2016)

    Google Scholar 

  8. da Silva, R.F., Casanova, H., Chard, K., et al.: Workflows community summit: advancing the state-of-the-art of scientific workflows management systems research and development. arXiv preprint arXiv:2106.05177 (2021)

  9. Eick, S.G., Graves, T.L., Karr, A.F., Mockus, A., Schuster, P.: Visualizing software changes. IEEE Trans. Software Eng. 28, 396–412 (2002)

    Article  Google Scholar 

  10. Google Developers. Protocol Buffers (2022)

    Google Scholar 

  11. Harbor. Harbor Website (2022)

    Google Scholar 

  12. Hazzan, O., Dubinsky, Y.: The agile manifesto. SpringerBriefs Comput. Sci. 9, 9–14 (2014)

    Article  Google Scholar 

  13. Hines, J.: ORNL adds powerful AI appliances to computing portfolio - oak ridge leadership computing facility, August 2019. https://www.olcf.ornl.gov/2019/02/06/ornl-adds-powerful-ai-appliances-to-computing-portfolio/. Accessed 26 June 2022

  14. Li, L., Fan, Y., Tse, M., Lin, K.-Y.: A review of applications in federated learning. Comput. Ind. Eng. 149, 106854 (2020)

    Article  Google Scholar 

  15. Li, T., Sahu, A.K., Talwalkar, A., Smith, V.: Federated learning: challenges, methods, and future directions. IEEE Signal Process. Mag. 37, 50–60 (2020)

    Google Scholar 

  16. Li, W., Liewig, M.: A survey of AI accelerators for edge environment. In: Rocha, Á., Adeli, H., Reis, L.P., Costanzo, S., Orovic, I., Moreira, F. (eds.) WorldCIST 2020. AISC, vol. 1160, pp. 35–44. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-45691-7_4

    Chapter  Google Scholar 

  17. Lwakatare, L.E., Kuvaja, P., Oivo, M.: Dimensions of DevOps. In: Lassenius, C., Dingsøyr, T., Paasivaara, M. (eds.) XP 2015. LNBIP, vol. 212, pp. 212–217. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-18612-2_19

    Chapter  Google Scholar 

  18. Malviya-Thakur, A., Watson, G.: Dynamics of scientific software teams. Collegeville (2021)

    Google Scholar 

  19. Meyer, C., Dellby, N., Hachtel, J.A., Lovejoy, T., Mittelberger, A., Krivanek, O.: Nion swift: open source image processing software for instrument control, data acquisition, organization, visualization, and analysis using python. Microsc. Microanal. 25(S2), 122–123 (2019)

    Article  Google Scholar 

  20. Mockus, A., Fielding, R.T., Herbsleb, J.D.: Two case studies of open source software development: Apache and Mozilla. ACM Trans. Softw. Eng. Methodol. 11, 309–346 (2002)

    Article  Google Scholar 

  21. Mockus, A., Weiss, D.M.: Predicting risk of software changes. Bell Labs Tech. J. 5, 169–180 (2000)

    Article  Google Scholar 

  22. Naughton, T., et al.: Software framework for federated science instruments. In: Nichols, J., Verastegui, B., Maccabe, A.B., Hernandez, O., Parete-Koon, S., Ahearn, T. (eds.) SMC 2020. CCIS, vol. 1315, pp. 189–203. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-63393-6_13

    Chapter  Google Scholar 

  23. Nguyen-Hoan, L., Flint, S., Sankaranarayana, R.: A survey of scientific software development. In: Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement. Association for Computing Machinery (2010)

    Google Scholar 

  24. Nion Co., Nion Swift User’s Guide (2022)

    Google Scholar 

  25. Ophus, C., Ercius, P., Sarahan, M., Czarnik, C., Ciston, J.: Recording and using 4D-stem datasets in materials science. Microsc. Microanal. 20(S3), 62–63 (2014)

    Article  Google Scholar 

  26. Pennycook, S.J., Nellist, P.D.: Scanning Transmission Electron Microscopy: Imaging and Analysis. Springer, New York (2011). https://doi.org/10.1007/978-1-4419-7200-2

    Book  Google Scholar 

  27. Library Pyro. Github - irmen/pyro5: Pyro 5 - python remote objects for modern python versions (2022). https://github.com/irmen/Pyro5. Accessed 27 June 2022

  28. Python Code Quality Authority (PyCQA). PyCQA’s Bandit GitHub repository (2022)

    Google Scholar 

  29. RabbitMQ. RabbitMQ Website (2022)

    Google Scholar 

  30. Roccapriore, K.M., Dyck, O., Oxley, M.P., Ziatdinov, M., Kalinin, S.V.: Automated experiment in 4D-STEM: exploring emergent physics and structural behaviors. ACS Nano (2022)

    Google Scholar 

  31. Segal, J., Morris, C.: Developing scientific software. IEEE Softw. 25, 18–20 (2008)

    Article  Google Scholar 

  32. Slate. Slate: Kubernetes cluster with access to Summit (2021)

    Google Scholar 

  33. Somnath, S., et al.: Building an integrated ecosystem of computational and observational facilities to accelerate scientific discovery. In: Nichols, J., et al. (eds.) Smoky Mountains Computational Sciences and Engineering Conference, pp. 58–75. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-96498-6_4

    Chapter  Google Scholar 

  34. Nion Swift. Nion swift, March 2022. https://github.com/nion-software/nionswift. Accessed 26 June 2022

  35. Treveil, M., et al.: Introducing MLOps. O’Reilly Media, Sebastopol (2020)

    Google Scholar 

  36. Zager, R., Zager, J.: Ooda loops in cyberspace: a new cyber-defense model. Small Wars J. (2017)

    Google Scholar 

  37. Zhao, F., Niu, X., Huang, S.L., Zhang, L.: Reproducing scientific experiment with cloud DevOps. In: 2020 IEEE World Congress on Services (SERVICES), pp. 259–264 (2020)

    Google Scholar 

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Acknowledgement

This manuscript has been authored by UT-Battelle, LLC under Contract No. DEAC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access.

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Thakur, A.M. et al. (2022). Towards a Software Development Framework for Interconnected Science Ecosystems. In: Doug, K., Al, G., Pophale, S., Liu, H., Parete-Koon, S. (eds) Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation. SMC 2022. Communications in Computer and Information Science, vol 1690. Springer, Cham. https://doi.org/10.1007/978-3-031-23606-8_13

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  • DOI: https://doi.org/10.1007/978-3-031-23606-8_13

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