=Paper=
{{Paper
|id=Vol-447/paper-10
|storemode=property
|title=Data Republishing on the Social Semantic Web
|pdfUrl=https://ceur-ws.org/Vol-447/paper8.pdf
|volume=Vol-447
|dblpUrl=https://dblp.org/rec/conf/esws/WagnerM09
}}
==Data Republishing on the Social Semantic Web==
https://ceur-ws.org/Vol-447/paper8.pdf
Data Republishing on the Social Semantic Web
Claudia Wagner1,2 and Enrico Motta2
1
Institute for Networked Media, JOANNEUM RESEARCH,
Steyrergasse 17, 8010 Graz, Austria
claudia.wagner@joanneum.at
2
Knowledge Media Institute, The Open University,
Walton Hall, Milton Keynes, MK7 6AA, United Kingdom
e.motta@open.ac.uk
Abstract. Data Republishing is a recent Social Web phenomenon which
can be observed in different areas of the Social Web. However, current
Data Republishing tools don’t work in the emerging context of the Se-
mantic Web. In particular, these tools neither generate any semantic
metadata which provide information about the republished content (e.g.,
provenance information) nor are they able to make use of existing seman-
tic metadata annotating the original content being republished. In this
work we introduce the concept of Semantic Data Republishing and de-
scribe how to implement it.
1 Introduction
1.1 Motivation
Data Republishing is a recent Social Web phenomenon which can be observed in
different areas of the Social Web, such as the blogosphere, the microblogosphere
or the social networking sphere. Data Republishing refers to the process in which
a user, knowing that data are already published on the Web, rereleases them in
a new context. Users for example republish data by reblogging external content
on their blogs, by retweeting microblog posts from other users on their own
microblog or by posting external content to their Facebook3 wall. A new kind of
republishing oriented Social Web application, so-called tumblelogs, has recently
emerged from this trend. Tumblelogs are blogs with shorter posts and mixed
media types which are usually less structured than classical blogs [19]. Users can
quickly share their online discoveries by republishing multimedia content, found
on the Web, on their tumblelogs. Tumblelog providers, such as tumblr4 and
soup5 , gain in importance thanks to their increasing number of unique visitors6 .
3
http://facebook.com
4
http://tumblr.com
5
http://soup.io
6
http://siteanalytics.compete.com/soup.io+tumblr.com/?metric=uv
Current Data Republishing tools, such as Tumblr Share7 , ShareThis8 or
Zemanta Reblog9 , support users in republishing their online discoveries on So-
cial Web applications. These tools allow users to select data on any web page,
generate a new data item on their preferred target web application, transfer the
selected data as text or binary data and use them as content of the new data
item. However, a limitation of this approach is that no semantic metadata are
generated - e.g., to expose the provenance of the copied data. That means that
the information about the republishing process (i.e., who republished, when,
from which source application, which fragments of data on which target appli-
cation) is lost. Another drawback of current Republishing tools is that they are
not able to make use of existing semantic metadata which may annotate the
original data being republished. Consequently, these tools do not fully support
the next generation of Social Web applications, so-called Social Semantic Web
applications, which expose the semantics of their data in a machine-interpretable
way by using ontology-based metadata.
In this paper we illustrate the need of a new kind of Republishing tool for
the Social Semantic Web. We introduce the concept of Semantic Data Repub-
lishing and discuss requirements and functionalities of tools implementing this
concept in section 2. An initial implementation of an example prototype imple-
menting Semantic Data Republishing is presented in section 3. Finally, in section
4 and 5 we discuss related work stemming from the areas of data publishing and
Data Portability on the Social Semantic Web and outline new opportunities for
research and development made possible by it.
1.2 Data Republishing on the Social Semantic Web
Two different methods for Data Republishing across individual web sites can
be distinguished: (1) Data Republishing by copying data values and (2) Data
Republishing by copying data references.
(1) Data Mobility standards (e.g., RSS 1.0, RSS 2.0, Atom, OPML) facilitate
Data Republishing by copying data values [9]. Thanks to Data Mobility
initiatives structured data can be republished on individual websites without
the need to implement application-specific Programming Interfaces (APIs).
(2) Linked Data Design Principles10 provide data access by reference. Hence,
data published according to these principals can be republished and reused
by reference. Social Semantic Web applications can reference and derefer-
ence resources by using their URIs, access their machine-interpretable de-
scriptions and republish data without the need to copy data values.
Both methods, i.e. Data Republishing by reference and Data Republishing
by value, are important for different scenarios.
7
http://www.tumblr.com/goodies
8
http://sharethis.com
9
http://zemanta.com/reblog
10
http://www.w3.org/DesignIssues/LinkedData.html
If data are republished by copying their values both, the source and the target
application, store an individual instance of the same data. These instances can
then be changed individually. Therefore this technique is suited for situations in
which users want their republished data to be independent of the original data
(e.g., because users do not want the republished data to change, if the original
ones change or because the original data may not be available for long).
If data are republished by reference, the source and the target application
point to the same data instance. In this scenario, if the source or target appli-
cation modifies the data, the data being displayed change on both applications.
Therefore this approach ensures that in situations where data are likely to be
modified (e.g., in the context of a wiki page) the republished data and the orig-
inal data are kept in sync.
The advantage of exploiting Semantic Web technologies in the context of the
current republishing phenomenon of the Social Web is that the two aforemen-
tioned republishing methods can be integrated to combine the advantages of
both approaches. In particular by applying Semantic Web technologies to Data
Republishing data can be cached on the target application to increase the avail-
ability of republished data and can in addition be updated at certain intervals
by using the semantic metadata of the republished data to formulate queries.
2 The Design of a Semantic Republishing Tool
2.1 Requirements
A Semantic Republishing tool should allow users to select content from any
web site and republish it on their preferred Social Web or Social Semantic Web
application (e.g., their blog, their Facebook wall). To exploit the full potential
of the Social Semantic Web in the context of the current Republishing trend we
have identified the following main requirements for Semantic Republishing tools:
1. Semantic Republishing tools must be able to detect and republish
semantic metadata together with the data they annotate. Semantic
metadata must be republished together with the original data they annotate
to allow users to benefit from additional third party services and tools which
leverage semantic metadata of the data currently being processed. These
additional services need semantically described structured data in order to
be able to interpret the data and provide services upon them.
For example browser tools, such as Firefox Operator11 , leverage semantic
metadata found on the currently viewed web site and provide services (such
as ”Export contact to MS Outlook address book”) upon the data which are
annotated by the processed metadata.
2. Semantic Republishing tools must be able to generate new seman-
tic metadata exposing information about the provenance of the
republished data. If data are republished in a new context, new semantic
11
https://addons.mozilla.org/de/firefox/addon/4106
metadata must be created which expose information about the provenance
and the republishing process in a machine-interpretable way. Consequently,
Semantic Web search engines can use this information to answer sophisti-
cated data queries (such as select all users who republished this section of this
article or select all comments about a certain youtube12 video related with the
original video or with posts embedding the video). Furthermore, it is impor-
tant that Semantic Republishing tools expose detailed provenance metadata
to boost the transparency and information accountability on the Web (see
section 2.3). Finally, the exposure of detailed machine-interpretable prove-
nance metadata allows implementing synchronization services which keep
the republished data and the original ones in sync.
3. Semantic Republishing tools must be able to interpret semantic
metadata associated with the data to republish. Existing semantic
metadata can expose information about the content, the structure, the pri-
vacy settings and usage restrictions of the data they annotate. Hence, ex-
isting semantic metadata annotating the original data must be interpreted
by Semantic Republishing tools in order to support users during the Repub-
lishing process (e.g., suggest tags of original data to reuse or suggest how to
republish original data according to their licenses).
4. Semantic Republishing tools must be easy to use for end-user. To
minimize usage barriers the interface of the Semantic Republishing tools
must be similar to interfaces of already widely used traditional Republishing
tools.
2.2 Metadata Modelling
We use the SIOC13 ontology (namespace prefix sioc) together with the DCMI
Metadata Terms14 (namespace prefix dcterms), the Dublin Core Metadata Ele-
ment Set15 (namespace prefix dc), the FoaF16 Ontology (namespace prefix foaf)
and the RDF Site Summary 1.0 Module Content17 (namespace prefix content)
to describe republished data items in a machine-interpretable way. A repub-
lished data item is exposed as a resource of type sioc:Post and identified by a
URI (e.g., http://example.com#rebloggedItem_443af) to enable any third party
to make reference to this item in other RDF statements. The sioc:content
property is used to expose the plain text content and the content:encoded
property is used to expose the (X)HTML content of a republished item. The
dc:source property relates the republished item with the resource from which
it originates. The dcterms:created property exposes the date and time when
the republished content has been published for the last time.
12
http://youtube.com
13
http://rdfs.org/sioc/spec/
14
http://dublincore.org/documents/dcmi-terms/
15
http://dublincore.org/documents/dces/
16
http://xmlns.com/foaf/spec/
17
http://web.resource.org/rss/1.0/modules/content/
2.3 Related Privacy and Usage Rights Issues
In the context of Data Republishing privacy and usage policies related with the
data being republished must be taken into account. Privacy policies specify the
confidentiality of data during transmission and also after receipt of data [10] and
usage policies specify how and under which conditions clients are allowed to use
data. With current widely-used Republishing tools users can either republish
all data for which they have reading permissions without taking privacy and
usage policies into account or cannot republish private or usage restricted data
at all. Usage rights and privacy settings related with the selected data cannot
be taken into account by these tools, because the settings are usually neither
published in a machine-interpretable way nor are these tools able to interpret
them. Consequently, traditional Data Republishing tools cannot support users
in republishing data without compromising privacy and usage policies of data.
We believe that Semantic Data Republishing tools can help to overcome this
problem and support privacy and right data usage by taking one of the following
approaches:
(1) Interpreting privacy and usage policies related with the data being reused
to guide users through the republishing process -i.e. support users in repub-
lishing data without compromising privacy policies or usage restrictions.
(2) Preserving privacy and usage policies of the original data when they are
republished to enforce them for the republished data as well.
First, to allow Semantic Republishing tools interpreting policies of data web
applications must expose not only their data in a machine-interpretable form,
but also the related privacy and usage policies. If policy metadata are embedded
in web pages to relate data with their policy descriptions, Semantic Repub-
lishing tools will be able to extract and interpret them. Consequently, users
will be informed about policies related with the data they want to republish
and will be warned if they are going to violate policies by republishing data.
The Creative Commons Rights Expression Language (ccREL) [1], the standard
recommended by Creative Commons (CC) for machine-readable expression of
usage rights, is a successful example of publishing lightweight usage rights en-
coded in XHTML+RDFa. The proposed interpreting and guiding functionality
of Semantic Republishing tools will however not prevent users from abusing
data and compromising privacy and usage settings, but boost user’s awareness
of data privacy and ’good’ data usage. This user’s awareness combined with a
transparent republishing process can ensure privacy through fair, appropriate
and transparent use of information [20]. Semantic Republishing tools expose the
provenance and republishing history of data in a machine-interpretable form.
Consequently, users who violate usage and/or privacy policies related to data
being republished can then be held accountable.
Second, to allow source and target application to share data and their policies
Semantic Republishing tools must make the relation between the original data
and the republished data explicit. Existing policy frameworks, such as REIN
[11] or Protune [7], can be used on source and target applications to share the
policies of the original data and reason over them. Both frameworks are based
on Semantic Web technologies and can be used for representing and processing
distributed policies. However, in the context of Data Republishing the same data
can be accessed on the source and target application. Therefore the source and
target application must both be able to enforce the policies of the original data or
the target application must redirect the client request to the source application
which can consequently enforce the policies of original data for the republished
data as well.
3 Implementation of a Semantic Reblog Tool
To demonstrate our ideas we have implemented a first example of a Semantic
Data Republishing tool, namely a Semantic Reblog tool for the OpenSource
Blogging Software WordPress18 . The Semantic Reblog prototype consists of a
client side bookmarklet and a server side reblog script. This section gives some
insight into implementation issues and describes the Semantic Data Republishing
process.
3.1 Extraction of semantic metadata
The Semantic Reblog tool extracts semantic metadata which annotate the cur-
rent user selection (see step 1 and 2 in figure 1). On the client side the Semantic
Reblog bookmarklet uses jQuery RDF plug-ins19 to extract semantic metadata
which are embedded in the selected (X)HTML region of the current web site. If
no semantic metadata related with the selected (X)HTML region can be found,
the Semantic Reblog server component parses the whole (X)HTML page search-
ing for links to external RDF files which describe the page’s data. The Semantic
Reblog server component extracts triples from the external RDF files as well
and checks if the selected data values belong to any object values of the ex-
tracted triples. The Semantic Reblog server component uses ARC220 to parse
and extract semantic metadata. It must be noticed that the results of this server
side extraction process can be ambiguous and that therefore the results of the
client side extraction which takes positional information as well into account are
usually more precise.
3.2 Generation of semantic metadata
The Semantic Reblog server component pastes the selected data into the tinyMCE
editor21 which is used as visual user editor by WordPress (see step 3 in figure
18
http://wordpress.org
19
http://code.google.com/p/rdfquery
20
http://arc.semsol.com
21
http://tinymce.moxiecode.com/
1). As described in section 2.2 the republished data are automatically anno-
tated with semantic metadata exposing their provenance. All semantic meta-
data are embedded in the (X)HTML of the post’s content and are serialized in
XHTML+RDFa.
1 2 Extractor
select & reblog
user
http://www.w3.org/2002/12/cal/ical#vEvent
rd
f
:ty
pe
http://upcoming.yahoo.com/event/1850882/#event
3
n
tio
XHTML/RDFa content
ip
of new post
scr
: de
dc
Fig. 1. Semantics-aware reblog process: extract and edit data and semantic metadata
3.3 Republishing data and semantic metadata
The Semantic Reblog tool preserves existing semantic metadata embedded in the
selected content of the source site and republishes them together with the newly
created semantic metadata and the data being annotated by them. Two different
approaches have been identified for preserving semantic metadata embedded in
(X)HTML snippets during the republishing process:
(1) RDFa Serialization: The RDF graph which has been extracted from the
selected fragment of the source site can be serialized as XHTML+RDFa
snippet. The disadvantage of this approach is that the parts of the selected
(X)HTML content which are not semantically annotated get lost.
(2) Snippet Semantification: Cutting individual (X)HTML snippets from
a semantically enriched (X)HTML pages can lead to (X)HTML snippets
which contain meaningless, local and/or incomplete semantic metadata.
During the semantification process the semantic metadata embedded in
the selected (X)HTML snippet are transformed into a valid semantically
enriched (X)HTML snippet by reusing the semantic metadata extracted
from the source site. The semantified (X)HTML snippets are serialized as
XHTML+RDFa and are stored in a post’s content.
Finally, the Semantic Reblog tool makes the republished and newly generated
data and semantic metadata accessible for further web applications (see figure 2).
The semantified (X)HTML snippet together with the newly generated semantic
metadata are displayed in a user’s reblog editor and can be edited by the user
(see step 1 in figure 2). The editor can either be used in the visual edit mode
in which the (X)HTML mark-up is hidden or in the HTML mode in which the
data and their mark-up are displayed. The user can push the publish button to
publish the post (see step 2 in figure 2). A newly created post is displayed on the
user’s blog. To make the embedded, reblogged resources accessible the WordPress
SIOC Exporter22 which models the content of a blog semantically and serializes
it as RDF/XML document has been extended. The extended WordPress SIOC
Exporter23 is used to export resources embedded inside a post’s content (e.g.
reblogged data items) and relates them with the blog post via the sioc:embeds
property of the SIOC ontology (see step 3 in figure 2) . Finally, the Semantic
Web index service Sindice24 is pinged to ensure that the republished semantically
annotated data are indexed (see step 4 in figure 2).
3.4 Usage Scenario
To illustrate the benefits of our Semantic Reblog tool, an example scenario is
described:
Tim is a typical Social Web users and one of his hobbies is taking pictures
and sharing them on the Social Web application Flickr25 . He likes discussing his
pictures with other users interested in photography. Tim browses the Web and
stumbles across one of his pictures which has been republished on the tumblelog
of someone he does not know. The republished picture has been commented on
the tumblelog and Tim is happy that he found such nice comments about his pic-
ture. Tim starts being interested in who else might have republished his picture.
In particular, he would like to find all comments about his picture, no matter
on which application they have been published. That means that Tim wants to
find as well comments about postings which have republished his picture. Tim
uses RepuSearch which is the fictive Semantic Web search engine specialized
in querying the republishing-sphere. RepuSearch provides a simple search form
allowing users to specify what they are searching for and formulates SPARQL
queries in the background. Tim copies the URI of his picture into the main
22
http://sioc-project.org/wordpress/
23
http://clauwa.info/download
24
http://sindice.com/
25
http://flickr.com
1
edit and/or
publish
user
republish 2
4
ping
3
SIOC Exporter
export
Fig. 2. Semantics-aware reblog process: republish and disseminate data and semantic
metadata
search box, specifies that he wants to find comments about his picture which
have been created in the last month and pushes the search button. RepuSearch
displays as a result a list of comments created in the last month which refer to
resources (e.g. posts) embedding Tim’s picture.
Based on our work a scenario like this can be realized in the future Web where
Semantic Web search engines exist allowing and supporting users in querying the
Web like a huge database.
4 Related Work
There has been a significant amount of research in publishing and interlinking
data on the Social Semantic Web. Social Semantic Web applications, such as
semantic blogs [14] [12] [5] [18], semantic wikis [16] or semantic microblogs [15],
allow average users to publish and interlink their data in a machine-interpretable
way. Our work distinguishes from aforementioned work by focusing on republish-
ing data. The requirements and challenges of publishing and modelling already
published data slightly differ from publishing unpublished data and additional
topics such as data privacy and usage rights arise in this context (see section
2.3).
SemiBlog [13] [3] illustrates how users can annotate their blog posts with
existing metadata from desktop applications. SemiBlog and our prototype both
focus on reusing existing semantic metadata. However, unlike semiBlog our Se-
mantic Reblog prototype reuses semantic metadata of web resources. On the
contrary semiBlog reuses metadata stored on desktop applications.
The Snippet Manager [6] and PiggyBank [8] are tools which allow users to
collect, manage and share information found on the Web. Both tools are cen-
tralized services, which store the information snippets of a user in his or her
personal semantic bank or knowledge base. Users can share information with
other users by granting them access to parts of their knowledge base or semantic
bank. On the contrary our Semantic Reblog prototype is not a centralized ser-
vice, but generates semantically enhanced information snippets which are stored
on distributed web applications. Furthermore, the Semantic Reblog prototype
allows republishing information snippets or modified versions of them in a new
context.
The work by Bojars et al. [4] shows how Semantic Web technologies can be
used to ensure portability of user-specific data and content. In particular they
propose to use FoaF and SIOC ontologies to model user information and user-
generated content in a machine-interpretable way. Current application specific
SIOC Importers and Exporters26 demonstrate how data can be migrated from
one Social Web application to another. After the portability process of a certain
resource (e.g., a blog post) the target site holds a replica of the original resource.
Our work distinguishes from their work by addressing another scenario in which
a user does not want to generate and republish a replica of the original resource.
On the contrary a user wants to generate a new resource which embeds and/or
discusses the original resource or parts of it.
Semantic Clipboards aim to realize Data Portability across all kinds of ap-
plications. The Semantic Clipboard idea was first presented by [2] and describes
how Semantic Web technologies can be used for moving structured content across
application boundaries. The source and destination application negotiate the for-
mat of the data to be transferred and the clipboard itself either holds a copy of
the RDF description of data or a reference pointing to the data’s RDF graph. A
first implementation of the Semantic Clipboard is presented in [17] and allows
copying RDF metadata from any source application to any desktop applications.
Other implementations of the Semantic Clipboard idea such as the RDFa Clip-
board27 and Semsol’s Web Clipboard28 exist as well. As the Semantic Clipboard
idea aims to solve a very generic problem our work can be seen as an easy-to-
use, lightweight and pragmatic solution for a specific problem in the context of
the current republishing trend of the Social Web. Furthermore, Semantic Clip-
boards are made to act on an ideal Semantic Web where all published data are
described in machine-interpretable way. Only semantically annotated data can
26
http://rdfs.org/sioc/applications/
27
http://www.w3.org/2006/07/SWD/RDFa/impl/js/rdfa-clipboard/
28
http://bnode.org/blog/2006/06/12/web-clipboard-adding-liveliness-to-
live-clipboard-with-erdf-json-and-sparql
be clipped and reused by using Semantic Clipboards. Our Semantic Reblog pro-
totype however is designed to be used on the current Web where not all data
are semantically annotated, but can be republished.
5 Conclusions and Future Work
In this paper we discussed the current republishing phenomenon on the So-
cial Web, highlighted related privacy issues and illustrated the benefits of using
Semantic Web technologies for Data Republishing. We introduced the concept
of Semantic Data Republishing and described requirements and potentials of a
new generation of semantics-aware Republishing tools. We presented a first im-
plementation of such a tool, namely a Semantic Reblog tool, which allows users
to republish data and their semantics, found on the Web, and annotates them
with ontology-based metadata exposing their provenance. However, a number
of issues still need to be addressed including how Semantic Republishing tools
should handle the republishing of private and/or usage restricted data and how
current Social Web applications can export their privacy policies in a machine-
interpretable way to make them reusable for other applications. We plan to
address these issues in future versions of our Semantic Reblog tool. Further-
more, we plan to improve the user interface of our Reblog tool to separate the
semantic annotations from the editable (X)HTML code and hide them from the
user.
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