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CALL FOR JOURNAL PAPERS
(apologies for cross-posting)
------------------------------

Exploring New Interaction Designs Made Possible by the Semantic Web

Special Issue Call: Journal of Web Semantics

Overview:
In this Special Issue, we seek papers that look at the challenges and
innovate possible solutions for everyday computer users to be able to
produce, publish, integrate, represent and share, on demand, information
from and to heterogeneous data sources. Challenges touch on interface
designs to support end-user programming for discovery and manipulation of
such sources, visualization and navigation approaches for capturing,
gathering and displaying and annotating data from multiple sources, and
user-oriented tools to support both data publication and data exchange. The
common thread among accepted papers will be their focus on such user
interaction designs/solutions oriented linked web of data challenges.
Papers are expected to be motivated by a user focus and methods evaluated in
terms of usability to support approaches pursued.

Motivation:
The current personal computing paradigm of single applications with their
associated data silos may finally be on its last legs as increasing numbers
move their computing off the desktop and onto the Web. In this transition,
we have a significant opportunity, and requirement, to reconsider how we
design interactions that take advantage of this highly linked data. Context
of when, where, what, and whom, for instance, is increasingly available from
mobile networked devices and is regularly if not automatically published to
social information collectors like Facebook, LinkedIn, and Twitter.

Intriguingly, little of the current rich sources of information are being
harvested and integrated. The opportunities such information affords,
however, as sources for compelling new applications would seem to be a
goldmine of possibility. Imagine applications that, by looking at one's
calendar on the net, and with awareness of whom one is with and where they
are, can either confirm that a scheduled meeting is taking place, or log the
current meeting as a new entry for reference later. Likewise, documents
shared by these participants could automatically be retrieved and available
in the background for rapid access. Furthermore, on the social side, mapping
current location and shared interests between participants may also
recommend a new nearby location for coffee or an art exhibition that may
otherwise have been missed. Larger social applications may enable not only
the movement of seasonal ills like colds or flus to be tracked, but more
serious outbreaks to be isolated.

The above examples may be considered opportunities for more proactive
personal information management applications that, by awareness of context
information, can better automatically support a person's goals. In an
increasingly data rich environment, the tasks may themselves change. We have
seen how mashups have made everything from house hunting to understanding
correlations between location and government funding more rapidly
accessible. If, rather than being dependent upon interested programmers to
create these interactive representations, we simply had access to the
semantic data from a variety of publishers, and the widgets to represent the
data, then we could create our own on-demand mashups to explore
heterogeneous data in any way we chose.

For each of these types of applications, interaction with information - be
it personal, social or public - provides richer, faster, and potentially
lighter-touch ways to build knowledge than our current interaction metaphors
allow. What is the bottleneck to achieving these enriched forms of
interaction? Fundamentally, we see the main bottleneck as a lack of tools
for easy data capture, publication, representation and manipulation.

Example:
The mashup is a summative demonstration of the problem: to combine only two
resources like a map and an apartment listing, one requires an API for a map
service, programming knowledge/skills to get the apartment data from one
source, say by having to scrape web pages, and plug that into the other. If
the person wishes to use a different map, they may need to rewrite how the
data from the apartment listing is plugged into that visualization. If they
wish to use a completely different visualization, such as a heat graph, they
will need to develop that code themselves.

The barrier to entry for non-programmers is too high for most to be
interested to attempt construction. By the time they would have the data
they need, it may no longer even be relevant for the questions they wish to
explore. Even for sufficiently skilled programmers, there are better things
we could be doing with our time than constantly re-inventing the wheel.

Challenges to be addressed in this issue include, but are not restricted
to:

	- approaches to support integrating data that is readily published,
such as RSS feeds that are only lightly structured.
	-   approaches to apply behaviors to these data sources.
	-  approaches to make it as easy for someone to create and to
publish structured data as it is to publish a blog.
	-  approaches to support easy selection of items within resources
for export into structured semantic forms like RDF.
	-  facilities to support the pulling in of multiple sources; for
instance, a person may wish to pull together data from three organizations.
Where will they gather this data? What tools will be available to explore
the various sources, align them where necessary and enable multiple
visualizations to be explored?
	-  methods to support fluidity and acceleration for each of the
above: lowering the interaction cost for gathering data sources, exploring
them and presenting them; designing lightweight and rapid techniques.
	-  novel input mechanisms: most structured data capture requires the
use of forms. The cost of form input can inhibit that data from being
captured or shared. How can we reduce the barrier to data capture?
	-  evaluation methods: how do we evaluate the degree to which these
new approaches are effective, useful or empowering for knowledge builders?
	- user analysis and design methods: how do we understand context and
goals at every stage of the design process? What is different about
designing for a highly personal, contextual, and linked environment?

This issue focusses on innovative interaction design that takes advantage of
linked, semantic data on the Web. Therefore, particularly relevant work
includes interaction designs to support rapid data selection or production,
reuse, representation, and designs that help users understand and control
their data environment. Real user evaluations that demonstrate that these
attributes are experienced as facile and fluid are expected as part of work
presented. We are also interested in evaluated models or frameworks that
will support such interaction, either by dealing with the limitations of
current data sources, or in particular, by making it easy for ordinary
computer users to produce shared data formats for these data interaction
tools. The preference is for RDF-based tools. Also of interest is what new
applications may be produced when such effortless heterogeneous data merging
becomes possible not *just* for Ajax hackers but for anyone currently using
the Web.

We welcome three types of submission for this Special Issue:
	Full papers from 10-30 pages of journal format.
	Short papers (4-6 page) demonstration papers with evaluations of new
tools
		that address any of the above challenges.
	Short (1-2 page) forward-looking more speculative papers addressing
the
		challenges outlined above.

Please upload papers to the Journal of Web Semantics
http://www.elsevier.com/wps/find/journaldescription.cws_home/671322/descript
ion#description

Key Dates:
	Papers due April 20
	Reviews to Authors by May 15
	Authors revisions by June 7
	Additional comments by Reviewers to Authors by June 23
	Final Revisions by July 15
	Publication Jan 2010

Editorial Committee for the Special Issue:
Co-editors:
	mc schraefel, University of Southampton, UK
	Lloyd Rutledge, Open University, Netherlands

Program Committee
	Abraham Bernstein, U of Zurich
	Duane Degler, Design for Context
	Steven Drucker, LiveLabs Research, Microsoft
	Jennifer Golbeck, U of Maryland
	David Karger, MIT

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