e-Science Infrastructure Interoperability Guide: The Seven Steps Toward Interoperability for e-Science
This chapter investigates challenges and provides proven solutions in the context of e-science infrastructure interoperability, because we want to guide worldwide infrastructure interoperability efforts. This chapter illustrates how an increasing number of e-scientists can take advantage of using different types of e-science infrastructures jointly for their e-research activities. The goal is to give readers who are working in computationally driven research infrastructures (e.g., as within European Strategy Forum on Research Infrastructures (ESFRIs) scientific user community projects) the opportunity to transfer processes to their particular situations. Hence, although the examples and processes of this chapter are closely aligned with specific setups in Europe, many lessons learned can be actually used in similar environments potentially arising from ESFRI projects that seek to use the computational resources within EGI and PRACE via their own research infrastructure, techniques, and tools. Furthermore, we emphasize that readers should get a sense of the concept and benefits of interoperability, especially by using sustainable standard-based approaches.
Since several decades, traditional scientific computing has been seen as a third pillar alongside theory and experiment and since 10 years the grid community has provided a solid e-science infrastructure base for these pillars to achieve e-science. e-Science is known for new kinds of collaboration in key areas of science through resource sharing using that infrastructure. But a closer look reveals that this base is realized by a wide variety of e-science infrastructures today while we observe an increasing demand by e-scientists for the use of more than one infrastructure to achieve e-science. One of the relatively new “e-science design pattern” in this context is the use of algorithms through scientific workflows that use concepts of both high-throughput computing (HTC) and high performance computing (HPC) with production applications of e-science infrastructures today.
This chapter illustrates ways and examples of realizing this infrastructure interoperability e-science design pattern and will therefore review existing reference models and architectures that are known to promote interoperability, such as the open grid forum (OGF) open grid services architecture (OGSA), the common component architecture (CCA), and the Organization for the Advancement of Structured Information Standards (OASIS) service component architecture (SCA). The review of these reference models and architectures provides insights into numerous limitations that arise due to not having suitable reference models in the community or because of following numerous proprietary approaches in case-by-case interoperability efforts without using any standards at all.
As its main contribution, this chapter therefore reveals a concrete seven-step plan to guide infrastructure interoperability processes. So far, reference models in grids have only addressed component-level interoperability aspects such as concrete functionality and semantics. In contrast, we change the whole process of production e-science infrastructure interoperability into a concrete seven step–based plan to achieve it while ensuring a concrete production grid impact. This impact is in turn another important contribution of this chapter, which we can see in the light of separating the “e-science hype” from “e-science production infrastructure reality.” Hence, this chapter not only presents how technical interoperability can be achieved with current production infrastructures, but also gives insights on operational, policy, and sustainability aspects, thus giving a complementary guidance for worldwide grids and emerging research infrastructures (i.e., ESFRIs or other virtual science communities), as well as their technology providers and e-scientists.
This chapter illustrates how the aforementioned steps can significantly support the process of establishing grid interoperability and, furthermore, gives concrete examples for each step in the context of real e-research problems and activities. The chapter also puts the processes into the context of interoperability field studies and uses cases in the field of fusion science (EUFORIA) and bioinformatics (WISDOM and Virtual Physiological Human).
KeywordsReference Model Design Pattern High Performance Computing Grid Service Grid Technology
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