=Paper=
{{Paper
|id=Vol-1310/avenues
|storemode=property
|title=Research Challenges and Avenues in Surfacing the Deep and the Social Web
|pdfUrl=https://ceur-ws.org/Vol-1310/avenues.pdf
|volume=Vol-1310
|dblpUrl=https://dblp.org/rec/conf/semweb/CunhaNBCV14
}}
==Research Challenges and Avenues in Surfacing the Deep and the Social Web==
https://ceur-ws.org/Vol-1310/avenues.pdf
SDSW’
2014
Panel
Report
Research
challenges
and
Avenues
in
Surfacing
the
Deep
and
the
Social
Web
After
the
paper
presentations
there
was
a
panel
where
the
audience,
authors,
and
workshop
organizers
discussed
research
challenges
and
avenues.
To
that
effect,
four
questions
were
used
to
guide
the
conversation.
The
consolidated
answers
are
presented
bellow.
Q1
-‐
By
many
the
Semantic
Web
(SW)
has
not
managed
to
reach
its
original
goal.
Nowadays
that
Big
Data,
Cloud
computing
and
Social
Networks
have
been
added
into
the
picture,
do
you
think
that
this
goal
became
closer
or
further?
The
SW
roadmap
has
been
established
in
1998.
With
respect
to
its
original
goal,
some
did
argue
that
the
SW
managed
to
be
closer,
in
promoting
RDF
as
a
kind
of
unified
model;
although
there
was
some
shift
according
to
two
directions:
from
documents
to
metadata,
and
from
data
to
resources.
With
respect
to
the
Big
Data
impact,
shifting
between
communities
makes
it
difficult
to
handle
big
data.
There
is
more
and
more
knowledge
embedded
in
the
data,
and
other
techniques
such
as
machine
learning
should
be
used
to
assist
the
data
analysis
process.
There
is
also
a
difference
between
engineering
and
science,
industry
and
academia:
although
(most)
enterprise
tools
are
SW-‐limited,
there
may
be
some
exceptions
such
as
the
Google
Graph
Knowledge.
Finally
there
is
also
a
multilingualism
issue:
as
an
example,
counting
for
the
same
entity
in
DBpedia
may
be
different
from
German
to
French.
Q2
-‐
Do
you
see
the
privacy
issue
playing
a
role
in
your
approach,
or
do
you
consider
it
completely
orthogonal?
It
was
not
clear
that
the
privacy
did
play
a
significant
role
according
to
the
papers
presented
at
the
workshop.
However,
the
discussion
highlighted
some
issues
and
candidate
solutions:
-‐ issues:
privacy
leaks
(notably
with
open
data),
need
for
a
semantics
of
privacy,
security
vs.
privacy.
-‐ solutions:
data
anonymization,
graph
structure
encryption,
ontology
watermarking.
Q3
-‐
The
ability
to
effectively
express
the
information
that
a
user
is
looking
for
is
of
paramount
importance.
Recently,
people
get
further
and
further
away
from
SQL
and
other
traditional
languages.
Keyword
query
seems
to
be
a
favorite
solution,
yet
with
a
lot
of
limitations.
What
is
your
opinion
about
modern
or
new
forms
of
querying
techniques?
The
real
issue
is
to
help
users
express
or
anticipate
their
needs.
Search
engines
are
building
Knowledge
Graphs
but
most
of
the
time
the
user
has
the
knowledge
and
does
not
know
how
to
express
it:
exploratory
search
solutions
are
being
proposed
to
tackle
this
issue.
Also,
there
is
a
need
for
visualization-‐based
solutions.
Q4
-‐
The
deep
web
looks
like
a
collection
of
structured
sources.
How
do
you
see
the
integration
of
these
data
with
the
social
and
the
document
web
data
into
one
unified
framework?
The
discussion
about
RDF
(as
a
unified
model)
was
brought
up
again.
Some
did
argue
that
we
could
almost
investigate
everything:
see,
for
example,
the
social
tagging.
Others
did
argue
that
we
may
need
some
complex
multi-‐layered
(graph)
model
to
handle
various
dimensions
such
as
temporality
and
spatiality:
as
an
example,
community
detection
is
temporality
dependent.
Hence,
there
is
a
need
for
a
multidimensional
analysis
on
a
multilayered
model,
and
more
investigation
is
needed
with
respect
to
a
unified
model/framework.
Furthermore,
it
is
clear
that
there
is
no
single
solution
for
the
semantic
web,
rather
than
a
collection
of
tools
and
techniques
orchestrated
together.
So,
it
is
not
about
simply
the
data
model.
Data
can
be
represented
flexibly.
However,
it
is
about
building
applications
that
can
communicate
between
them.