Due to numerous requests, the deadline for submissions to the Journal of
Web Semantics special issue on "Exploring New Interaction Designs Made
Possible by the Semantic Web" is extended from April 20th to April 30th.
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
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.
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
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
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
Challenges to be addressed in this issue include, but are not restricted
- 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
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
- 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 focuses 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
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
that address any of the above challenges.
Short (1-2 page) forward-looking more speculative papers addressing
challenges outlined above.
Please upload papers to the Journal of Web Semantics
Papers due April 30 (extended)
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:
mc schraefel, University of Southampton, UK
Lloyd Rutledge, Open Universiteit Nederland
Abraham Bernstein, U of Zurich
Duane Degler, IPGEMS
Steven Drucker, LiveLabs Research, Microsoft
Jennifer Golbeck, U of Maryland
David Karger, MIT
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