The term “e-science” is roughly – though not precisely – synonymous with “Cyberinfrastructure”; where the latter term is prevalent in the United States, e-science predominates in the United Kingdom and elsewhere in Europe. Both terms refer to the use of networked computing technologies to enhance collaboration and innovative methods in research. “E-Science,” however, has a more specific focus on scientific research, whereas Cyberinfrastructure is more inclusive of fields outside the sciences and engineering, and incorporates greater emphasis on supercomputing resources and innovation.
Recently, e-science, or the more generic term eResearch has come into vogue, following on the heels of the more well-established term eCommerce, which includes anything from supply-chain integration to CRM (Customer Relationship Management).
The definition of e-research is very much depends upon on an individual or organization’s perspective; it is also called Cyberinfrastructure (Cyberinfrastructure, 2006) in the USA. That’s why any group of researchers has differing, and often vocal opinions on what eResearch is.
Since the late of 1980s, computational science has become established as a third avenue of scientific discovery, alongside with the theoretical and experimental methodologies, which mainly based on large-scale computer simulations in areas such as physics and chemistry. E-Science subsumes this role; it also goes further by focusing not only on compute-intensive simulations, but also on the remote use of large-scale data and knowledge repositories, scientific instruments and experiments, and sensor arrays.
Furthermore, in the e-science, these distributed resources are typically used collectively to enable a new collaborative style of scientific endeavor, which is changing the research ethos and driving research agendas in many areas. This broadening of scope from computational science to e-science has led to the inclusion of fields, such as bio-informatics, environmental science, and medical applications, in addition to the physical sciences.
Because of advancements in information and communication technologies that brought in huge increases in computer power, network band width, expansion in data volume, storage and information; new order of collaborative research and scientific work have been immerging in recent years.
As indicated by many writers, trends in large scale distributed global collaborative science and research works have been evolving these days (Post Note, 2007, Hey, Tony and Jessie, Hey, 2006). These collaborative research and scientific works require access to very large data collections, very large scale computing resources, very good infrastructure supporting to distributed computing and high performance visualization backing effective interactions and collaborations among knowledge sharing agents (National e-Science Centre, Office of Science and Innovation e-Infrastructure Working Group, 2007, Joint Task Force on Library Support for E-Science, 2007 ). But, as it is stated before, these approaches need compute-intensive simulations, the remote use of large-scale data and knowledge repositories, scientific instruments and experiments, as well as sensor arrays.
E-research or e-science is facing serious, complex issues of strategy and policy regarding the creation, management and long-term care of data, which as the technologies related to the e-science put the data generated at risk. Hence e-science, as a new research methodology, stimulated by networked capabilities and vast amounts of data (Philip Lord & Alison Macdonald, 2004, Philip Lord, et al, 2004, Hey, Tony and Jessie, Hey, 2006).
As to many writer, besides setting the required digital infrastructures, e-science/e-research needs the effective accomplishments of activities that related to managing and promoting the use of data from its point of creation to ensure it fits for contemporary purpose, available for discovery and reuse, and ensuring that data is properly selected, stored in which can be accessed, its logical and physical integrity is got maintained over time, that including security and authenticity as well as archiving in which specific items of data are maintained over time, so that they can still be accessed and understood through changes in technology (Philip Lord, et al, 2004, Hey, Tony and Jessie, Hey, 2006).
Because of the aforementioned reasons of data creation and networking strategies that promote effective and efficient collaborations, knowledge sharing will be the focus area that I want to explore more.
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