Semantic applications are the next frontier for information science,
but creating them is very difficult. Now, European researchers in the NeOn
project are developing tools that will make it easier to create
semantic applications, powerful programs that identify data not just by
their textual content, but also by the information’s relevance to users.
The tools they created are being tested by the Food and Agriculture
Organisation (FAO) and by Spain’s pharmaceutical industry. The FAO, a
project partner, is testing the tools as a means of creating an
over-fishing alert system as a means of improving the management of the
world’s fisheries. (See part two of this two-part article – ‘Semantic technologies help world’s fisheries’)
In Spain, pharmaceutical companies are testing the NeOn tools as a
means of allowing the industry to share data resources and exchange
information on diseases, epidemiology, treatments, and other medical
issues.
Enormous potential
Right now, searching a
computer or the internet works by using filenames or keywords, but
people still need to sort the results for relevance. This sorting
process can become a huge task when assessing large datasets of closely
related information like the information typically kept by the world’s
major corporations, governments and institutions.
Semantic software promises to revolutionise information science.
Semantic applications could be used to turn massive amounts of data
into machine-readable, easily identifiable and actionable information.
With semantic applications, searchers can find resources by what
data means, its context, relevance and connotations, because the
information is machine-readable. Computers can understand the data.
Semantic applications work by using metadata, descriptions of
information. The metadata is stored in dictionaries, called ontologies.
An ontology defines the concepts and relationships used to describe
and represent a domain of knowledge. An ontology specifies standard
conceptual vocabularies with which to exchange data among networked
systems, provide services for answering queries, publish reusable
knowledge bases, and offer services to allow interoperability across
multiple systems and databases.
Ontologies make it possible for machines to find valuable
information currently buried in databases and on Web pages, saving
time. More importantly, the applications access information that might
otherwise be missed, and can find unsuspected connections between
different pieces of information.
Such applications can also sort a vast dataset in seconds, a task that could take humans days, weeks or months to do.
A quantum leap
There is just a big
problem. Developing semantic applications is a difficult, costly and
time-consuming process. Currently, developers work as a kind of cottage
industry – at a small-scale and loosely organised.
Ontologies are difficult to develop and manage. Little support
exists for collaboration so individuals or small teams do most of the
work. There is no standard way for re-using existing semantic resources.
There are many projects that have, at the cost of great effort,
resulted in semantic applications. However, the NeOn team is creating
what is called a ‘development environment’ that will make the design of
semantic applications much simpler.
While Henry Ford created a paradigm shift in manufacturing by
implementing production lines in his factory, NeOn’s researchers intend
to create a similar shift in the development of semantic applications.
Their strategy is the difference between making just one car and
employing a production line so that lots of people can work together to
make more cars quicker.
“NeOn’s goal is to make a quantum leap in the level of support for
semantic application development,” explains Enrico Motta, the project’s
coordinator. “We want to create an industrial strength development
environment that gives software engineers all the tools they need to
create semantic applications easily.”
There are three main thrusts to the researcher’s work: a toolkit, a
methodology and case studies. All three tasks feed into each other.
As the tools are developed, the methodology becomes more defined.
The researchers then test and refine both the tools and the methodology
in case studies with the FAO and the Spanish pharmaceutical industry.
The NeOn researchers are tackling every aspect of semantic
application development. One team is working on the dynamics of
managing and updating ontologies across networks, a major innovation.
Other researchers are working on developing collaborative tools, so
distant teams can work together. A third group is studying how
ontologies can be adapted to different applications or contexts.
Finally, the researchers are looking at human-ontology interaction.
“Traditionally, semantic applications forgot about the human
beings,” says Motta. “NeOn is also looking at the way people interact
with these novel technologies, their issues and expectations.”
Novel studies
The project team conducted
novel empirical studies to determine how developers worked and the
problems they encountered in designing semantic applications. Then the
researchers developed solutions, new tools or methods to create such
applications simply and easily. The toolkit they developed can accept
plugins, the software modules used to extend the functionality of
specific software.
The project just entered the third year of its four-year term, and
already the researchers have developed working prototypes. The
researchers plan to continue the work after the lifetime of the
project, which ends in early 2010.
“The NeOn platform is open source software, which means people can
change and adapt it,” says Motta. “We are currently setting up the NeOn
Foundation to foster a community around the technology. This will
ensure it gets maintained, updated and improved over time.”
A free prototype is already available for download. But by the end
of the NeOn project, which received funding from the EU's Sixth
Framework Programme for research, the team plans to have created a
fully-functional, development environment for semantic applications.
This article is part one of a two-part feature on NeOn.
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