Электрондық ғылым: деректерге негізделген жаңа парадигма

E Science or eScience is computationally intensive science that is carried out in highly distributed network environments, or science that uses immense data sets that require grid computing; the term sometimes includes technologies that enable distributed collaboration, such as the Access Grid. The term was created by John Taylor, the Director General of the United Kingdom's Office of Science and Technology in 1999 and was used to describe a large funding initiative starting in November 2000. E science has been more broadly interpreted since then, as "the application of computer technology to the undertaking of modern scientific investigation, including the preparation, experimentation, data collection, results dissemination, and long term storage and accessibility of all materials generated through the scientific process. These may include data modeling and analysis, electronic/digitized laboratory notebooks, raw and fitted data sets, manuscript production and draft versions, pre prints, and print and/or electronic publications." In 2014, IEEE eScience Conference Series condensed the definition to "eScience promotes innovation in collaborative, computationally or data intensive research across all disciplines, throughout the research lifecycle" in one of the working definitions used by the organizers. E science encompasses "what is often referred to as big data [which] has revolutionized science [such as] the Large Hadron Collider (LHC) at CERN [that] generates around 780 terabytes per year highly data intensive modern fields of science that generate large amounts of E science data include: computational biology, bioinformatics, genomics"

Turing Award winner Jim Gray imagined "data intensive science" or "e science" as a "fourth paradigm" of science (empirical, theoretical, computational and now data driven) and asserted that "everything about science is changing because of the impact of information technology" and the data deluge. E Science revolutionizes both fundamental legs of the scientific method: empirical research, especially through digital big data; and scientific theory, especially through computer simulation model building. These ideas were reflected by The White House's Office and Science Technology Policy in February 2013, which slated many of the aforementioned e Science output products for preservation and access requirements under the memorandum's directive. E sciences include particle physics, earth sciences and social simulations.

Most of the research activities into e Science have focused on the development of new computational tools and infrastructures to support scientific discovery. Due to the complexity of the software and the backend infrastructural requirements, e Science projects usually involve large teams managed and developed by research laboratories, large universities or governments. Currently there is a large focus in e Science in the United Kingdom, where the UK e Science programme provides significant funding. In Europe the development of computing capabilities to support the CERN Large Hadron Collider has led to the development of e Science and Grid infrastructures which are also used by other disciplines.

United States based initiatives, where the term cyberinfrastructure is typically used to define e Science projects, are primarily funded by the National Science Foundation office of cyberinfrastructure (NSF OCI) and Department of Energy (in particular the Office of Science). After the conclusion of TeraGrid in 2011, the ACCESS program was established and funded by the National Science Foundation to help researchers and educators, with or without supporting grants, to utilize the nation’s advanced computing systems and services.

Dutch eScience research is coordinated by the Netherlands eScience Center in Amsterdam, an initiative founded by NWO and SURF.

Plan Europe is a Platform of National e Science/Data Research Centers in Europe, as established during the constituting meeting 29–30 October 2014 in Amsterdam, the Netherlands, and which is based on agreed Terms of Reference. PLAN E has a kernel group of active members and convenes twice annually. More can be found on PLAN E.

Traditional science is representative of two distinct philosophical traditions within the history of science, but e Science, it is being argued, requires a paradigm shift, and the addition of a third branch of the sciences. "The idea of open data is not a new one; indeed, when studying the history and philosophy of science, Robert Boyle is credited with stressing the concepts of skepticism, transparency, and reproducibility for independent verification in scholarly publishing in the 1660s. The scientific method later was divided into two major branches, deductive and empirical approaches. Today, a theoretical revision in the scientific method should include a new branch, Victoria Stodden advocate[s], that of the computational approach, where like the other two methods, all of the computational steps by which scientists draw conclusions are revealed. This is because within the last 20 years, people have been grappling with how to handle changes in high performance computing and simulation." argues that since a modern discovery process instance serves a similar purpose to a mathematical proof it should have similar properties, namely it allows results to be deterministically reproduced when re executed and that intermediate results can be viewed to aid examination and comprehension. In this case, simply modelling the provenance of data is not sufficient. One has to model the provenance of the hypotheses and results generated from analyzing the data as well so as to provide evidence that support new discoveries. Scientific workflows have thus been proposed and developed to assist scientists to track the evolution of their data, intermediate results and final results as a means to document and track the evolution of discoveries within a piece of scientific research.

Other views include Science 2.0 where e Science is considered to be a shift from the publication of final results by well defined collaborative groups towards a more open approach, which includes the public sharing of raw data, preliminary experimental results, and related information. To facilitate this shift, the Science 2.0 view is on providing tools that simplify communication, cooperation and collaboration between interested parties. Such an approach has the potential to: speed up the process of scientific discovery; overcome problems associated with academic publishing and peer review; and remove time and cost barriers, limiting the process of generating new knowledge.