Information Technology Reference
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life sciences. The second-generation systems focused on heterogeneity, scalability,
and adaptability of computational resources and data. They introduced a layer of
base Grid service software tools—called “middleware”—that provides users and
applications with homogenous standardized interfaces. This Grid middleware layer
has provided the means for interoperability and the integration of heterogeneous
resources, and a significantly enhanced uptake of e-research in new research areas,
including the humanities and the arts, which have started to compile large data
archives.
The emerging third-generation systems have focused on the reuse of existing
components and information resources, and the possibility of assembling these
components in a flexible manner. At this stage, the Grid has started to evolve
not only technologically, but has also been reconsidered organizationally. The
emphasis has shifted from solely powerful and integrated technological tools, to
an evolving infrastructure for transient multi-institutional “virtual organizations”
(De Roure, Jennings, & Shadbolt, 2005). Dynamic and coordinated resource shar-
ing and problem solving are the key features of the third-generation Grid. As De
Roure et al. (2005) put it, this sharing “is not primarily file exchange, but rather
direct access to computers, software, data, and other resources, as is required by
a range of collaborative problem-solving and resource brokering strategies emerg-
ing in industry, science, and engineering” (p. 669). The key characteristics of the
emerging Grid systems are service-oriented architecture and increasing attention
to the “knowledge-based layer.” This knowledge-based layer includes such aspects
as resource description using metadata and ontologies, annotation using provenance
information, and process descriptions, such as workflows. These developments have
made the Grid increasingly more relevant for scholarly inquiry and knowledge
creation in social sciences, arts, and humanities.
In the social sciences, including education, it is currently not so much the concept
of Grid computing that is getting researchers involved, but rather the development
of Web 2.0 and cloud computing (Greenhow, Robelia, & Hughes, 2009). This is cer-
tainly to a large extent due to the fact that the grid computing infrastructure has so
far only been accessible with tools that require considerable technical knowledge,
whereas the Web 2.0 and cloud computing tools, such as Google Docs, are read-
ily accessible for everybody with basic understanding of web browser use and text
processing. In addition, research in the social sciences and in humanities are highly
contextualized and experiential, and a single researcher or a small team can still
accomplish a lot of work without being involved in large collaborations. An excep-
tion is the development of infrastructures that address a research community as a
whole, for instance, electronic repositories of cultural heritage, e-journal collections,
and integrated distributed data repositories.
Increasing interest in social technologies and Web 2.0-enabled scholarship in
education signal that Web 2.0 and cloud computing have the potential to be at least
in the short run more transformative than the more radical large-scale visions behind
grid computing (Greenhow et al., 2009). It is more likely that in the short term, the
practice of individual and small team learning research will be more affected by
del.icio.us and Facebook than by large institutional data repositories or scientific
