=Paper=
{{Paper
|id=None
|storemode=property
|title=Pundit: Semantically Structured Annotations for Web Contents and Digital Libraries
|pdfUrl=https://ceur-ws.org/Vol-912/paper4.pdf
|volume=Vol-912
|dblpUrl=https://dblp.org/rec/conf/ercimdl/GrassiMNFL12
}}
==Pundit: Semantically Structured Annotations for Web Contents and Digital Libraries==
https://ceur-ws.org/Vol-912/paper4.pdf
Proceedings of the 2nd International Workshop on Semantic Digital Archives (SDA 2012)
Pundit: Semantically Structured Annotations for
Web Contents and Digital Libraries
Marco Grassia,1 , Christian Morbidoni b,1 , Michele Nucci c,1 , Simone
Fonda d,2 , and Giovanni Ledda e,1
1
Semedia Group, Università Politecnica delle Marche, Italy
a
m.grassi@univpm.it, b christian.morbidoni@gmail.com, c m.nucci@univpm.it,
e
g.ledda@univpm.it
http://www.semedia.dibet.univpm.it/
2
NET7, Italy
d
fonda@netseven.it
http://www.netseven.it
Abstract. This paper introduces Pundit3 : a novel semantic annotation
tool that allows users to create structured data while annotating Web
pages relying on stand-off mark-up techniques. Pundit provides support
for different types of annotations, ranging from simple comments to se-
mantic links to Web of data entities and fine granular cross-references
and citations. In addition, it can be configured to include custom con-
trolled vocabularies and has been designed to enable groups of users to
share their annotations and collaboratively create structured knowledge.
Pundit allows creating semantically typed relations among heterogeneous
resources, both having different multimedia formats and belonging to dif-
ferent pages and domains. In this way, annotations can reinforce existing
data connections or create new ones and augment original information
generating new semantically structured aggregations of knowledge. These
can later be exploited both by other users to better navigate DL and Web
content, and by applications to improve data management.
Keywords: Digital libraries, Semantic Web, Ontology, Data Model
1 Introduction
Since the advent of the digital era, cultural heritage preservation has been in-
creasingly dealing with the conservation and the management of digital contents
in Digital Libraries (DLs). These contents can be the digital reproduction of
non-digital artefacts and manuscripts or more and more often born-digital mul-
timedia contents. As this amount of data multiplies everyday faster and faster,
its proper classification and management is becoming an increasingly complex
task but nevertheless more and more crucial to make such information effectively
consumable.
3
www.thepund.it
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Proceedings of the 2nd International Workshop on Semantic Digital Archives (SDA 2012)
With such purpose, in recent years, Semantic Web technologies and guide-
lines have been finding growing application in DL libraries scenario. RDF data
model is currently employed by Europeana4 initiative to aggregate indepen-
dently provided digital contents. Several DLs have also made their data publicly
available over the Web following the Linked Data recipes to join the giant and
interconnected knowledge base of the Linked Open Data cloud [1]. Several efforts
have also been done to introduce common accepted ontologies and schema for
metadata encoding of DL contents, as BIBO5 , OAI-ORE6 and Europeana Data
Model7 .
Since the advent of the Web 2.0, the capability to annotate Web content,
even with simple approaches based on plain-text comments or tags, has been
growingly recognized as an highly beneficial feature not only for the user, making
the navigation a more engaging and profitable experience, but also for the content
providers that can leverage on user created metadata to better classify and
search their published resources. Nevertheless, in several research scenarios, the
annotation of DL contents and more in general of Web resources represents a
fundamental activity daily performed by scholars. Also, in most of these cases an
higher level of accuracy and granularity is typically required in the annotations to
encode information about multimedia resource fragments, such as text excerpts
or image regions, according to specific controlled vocabularies.
Most of the existing systems rely on simple textual comments and tags.
Such approach is relatively easy to implement and very intuitive for users but
it suffers from several issues related with the ambiguity of natural language and
limits the accuracy and the efficiency of resource classification and retrieval. The
founding idea of this research is that, if properly structured and provided with
clearly-defined and machine-processable semantics, annotations can constitute
themselves a primary information which can enrich the original contents and
provide added value for other users as well as for third party applications. On
this line, Semantic Web technologies are employed to foster the flexibility and
interoperability of user created annotations, to promote their linkage with the
Web of Data and to permit their reuse by other people or applications beyond
the context they originated from.
This paper introduces Pundit8 , a novel semantic annotation tool, developed
in the context of the Semlib project9 [1]. Pundit has been conceived not only
to permit the annotation of generic Web pages and multimedia resources but to
be also specifically tailored to and integrated in existing DLs. Pundit provides
support for different types of annotations, ranging from simple comments to
semantic links to Web of data entities, to fine granular cross-references and
citations. Pundit can be configured to include custom controlled vocabularies
4
http://www.europeanaconnect.eu/
5
http://bibliontology.com/specification
6
http://www.openarchives.org/ore/1.0/primer
7
http://pro.europeana.eu/edm-documentation
8
Pundit: http://www.thepund.it
9
http://www.semlibproject.eu/
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Proceedings of the 2nd International Workshop on Semantic Digital Archives (SDA 2012)
and has been designed to enable groups of users to share their annotations and
collaboratively create structured knowledge. This paper is organized as follows:
Sec. 2 shortly provides a brief overview of related works; Sec. 3 explains the
proposed data model for the annotations; Sec. 4 discusses Pundit prototype and
its main functionalities.
2 Related Work
Nowadays, Web content annotation has become a common practice users are
familiar with. In particular, textual comments and plain tags are supported in
several mainstream Web applications like Facebook and Flickr.
In recent years, a growing number of tools have also been specifically created
to allow user to annotate digital resources. Some of those found on Semantic Web
technologies to improve the efficiency and the productivity of user created anno-
tations. An exhaustive state of the art in Semantic Annotation goes beyond the
purpose of this paper and can be found in literature [3], [2]. This section briefly
discusses some of the most interesting annotation approaches implemented in
the recently developed semantic annotation tools.
Semantic tagging paradigm, which exploits publicly available Linked Data
knowledge bases to retrieve unambiguous concept to use in resource tagging,
has been implemented in several application. Faviki10 is a social bookmarking
tool that uses DBpedia concepts as tags for Web pages. Zemanta11 uses natu-
ral language processing techniques to automatically extract semantic tags from
pages. Europeana Connect Media Annotation Prototype (ECMAP) [7], an on-
line media annotation suite based on Annotea [8], allows to augment textual
comment linking Dbpedia resources.
Other tools also allow the use of entities belonging to restricted vocabularies
or ontologies in the annotations. One click annotation [9] and CWRC-Writer
[10] allow to annotate entities in text excerpts by choosing between predefined
categories (as person, location, etc, ...) or creating new ones. LORE(Literature
Object Reuse and Exchange)[11], a Mozilla plugin developed inside the Aus-e-
Lit Project, allows to annotate Web pages fragment adding textual comments
and specifying tags selected from the AustLit thesaurus or entered as free text.
Some annotations tools enable also the creation of more expressive annota-
tions other than textual comments or tags. LORE allows to create the so called
“compound objects’, by bookmarking Internet resources and describing them
using standard terms coming from a bibliographic ontologies. A graphical user
interface is provided to create and visualize typed relationships among individ-
ual objects based on LORE Relationship Ontologies. CWRC-Writer provides an
experimental interface for the creation of subject-object-predicate statements.
If most of these tools focus on the annotation of text, some of those support
the annotation of other types of digital items. ECMAP in particular permits
also the annotation of maps, video fragments and images.
10
http://www.faviki.com/
11
http://www.zemanta.com/
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Proceedings of the 2nd International Workshop on Semantic Digital Archives (SDA 2012)
Fig. 1: Creating semantically structured aggregations of knowledge by means of anno-
tations
3 Semantically structured annotations
The main idea in Pundit is that of enabling users not only to comment, book-
mark or tag Web pages, but also to create semantically structured data while
annotating, thus enriching the so called Web of Data. The ability to express
semantically typed relations among resources, relying on ontologies and specific
vocabularies, not only enables users to express unambiguous and precise seman-
tics, but also, more interestingly, fosters the reuse of such collaboratively created
knowledge within other Web applications. In Pundit annotations contain a set
of RDF triples that connects annotated object (e.g. text excerpts) among each
other and with entities in the Linked Data Web. Thanks to the nature of RDF
data model (where triples can be flexibly combined to form arbitrary graphs)
and to the use of URIs as identifiers for both entities and annotated objects, dif-
ferent annotations independently authored by different users, can be combined
to form a semantic network that applications can retrieve via SPARQL endpoint
and dedicated REST API. The resulting RDF graph is exemplified in Fig. 1.
Annotations acquire full significance in relation with the target resource and
other contextual information, such as their author, their creation date and the
vocabulary terms used. Such metadata are encoded in RDF relying on the OAC
ontology, which provides a framework to represent annotations context in a stan-
dard way. The OAC data model uses the aoc:hasTarget property to define the
target to which the annotation is attached. The target of an annotation can be
entire Web pages or media objects, or their fragments (basing on Media Frag-
ments and XPointer standards). Annotations also contain a payload, defined by
the oac:hasBody property, which represents the user-created informative con-
52
Proceedings of the 2nd International Workshop on Semantic Digital Archives (SDA 2012)
2011-01-27 10:30:56
:MarcoGrassi
dcterms:created
Marco's annotation
dcterms:creator
rdfs:label
oac:Annotation The image photo-45, which is included in the exhibit-2011-1
rdf:type by photographer John Smith, is commented in this text excerpt
ex:ANNOTATION- oac:hasBody
ID-1 from my blog.
oac:hasBody
oac:hasTarget
ex:named-graph-1
http://johns-gallery/
http://johns-gallery/ exhibit-2011-1.htm
exhibit-2011-1.htm
oac:hasTarget
oac:hasTarget
ex:includes
"http://myexampleblog.it/ "http://myexampleblog.it/
http://johns-gallery/
article1.html#xpointer(start-point article1.html#xpointer(start-
photo-45.htm ex:comments
(string-range(//DIV[2]/P[1]/text() point(string-range(//DIV[2]/P
[9],'',40))/range-to(string-range(// [1]/text()[9],'',40))/range-to
DIV[3]/P[1]/text()[9],'',46)))" http://johns-gallery/ (string-range(//DIV[3]/P[1]/text
photo-45.htm ()[9],'',46)))"
Fig. 2: The representation of an annotation using a named graph
tent. At the time of writing, the OAC (Open Annotation Collaboration) model12
has been merged with the Annotation Ontology13 to form the OA (Open An-
notation) specification14 that only recently reached its first stable state and is
considered the de facto standard for representing annotations on the Semantic
Web. It’s worth to remark that, among other news, OA explicitly validates the
use of named graphs that has been already put in place in Pundit. At the time
of writing, full compliancy with such a specification is currently under devel-
opment. In Pundit, named graphs are used as “bodies’ (using the OA jargon)
of annotations, which in our system is composed by RDF triples itself. This
allows to keep separated statements belonging to different annotations, while
still being able to aggregate them into “composite’ graphs and query them using
standard SPARQL language. For example, one could query for all the annota-
tions whose target is a specific image and whose author is one (or more) specific
user, and then extract all the resources that “comments’ the image according to
the selected annotations. Fig. 2 illustrates how annotations are represented in
our system.
While the OAC ontology is used to represent contextual information, the se-
mantic content cannot be represented based on a fixed ontology. Different users
communities operating in specific domains need specific shared vocabularies (on-
tologies) of terms and relations that they can use in annotations. At RDF data
storage level, the system is therefore agnostic with respect to the domain ontolo-
gies used in structuring annotation informative semantic content, and specific
configuration at application level can be used to build an ad-hoc vocabulary
for each community addressed. Pundit supports both “open”, relatively flat vo-
12
http://www.openannotation.org/
13
http://code.google.com/p/annotation-ontology/
14
http://www.openannotation.org/spec/core/
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Proceedings of the 2nd International Workshop on Semantic Digital Archives (SDA 2012)
ex:Notebook-ID-1
oac:hasBody oac:hasBody
ex:ANNOTATION- ex:ANNOTATION-
ID-2 ID-1
oac:hasBody oac:hasBody
ex:named-graph-2 ex:named-graph-1
http://johns-gallery/ http://johns-gallery/
photo-45.htm exhibit-2011-1.htm
http://www.youtube.com/
watch?v=_rsEeYsFnaM ex:includes
ex:mentions http://johns-gallery/ "http://myexampleblog.it/
ex:is-similar-to
photo-45.htm article1.html#xpointer(start-
ex:comments point(string-range(//DIV[2]/P
[1]/text()[9],'',40))/range-to
(string-range(//DIV[3]/P[1]/
http://www.youtube.com/ text()[9],'',46)))"
watch?v=_fg67GHTyN
Fig. 3: The RDF representation of a notebook including two distinct annotations
cabularies like Freebase (leveraging the reconciliation APIs15 ) and restricted
controlled vocabularies and taxonomies, e.g. based on the SKOS model.
In Pundit, “notebooks” are resources that aggregate a set of annotations so
that they can be retrieved and queried. By default, each user has a proprietary
notebook where all her annotations are collected. Notebooks have a central role
in collaborative annotation. These can in fact have read/write privileges and
can be used for giving users control over her annotations, allowing to set them
as private or public and to select what notebooks are relevant. More precisely,
Pundit supports the concept of “active notebook”: when a notebook is active
for a given user the annotations in it will be shown by default. As a big number
of public notebooks might be available, this mechanism allows a user to restrict
the amount of annotations visualized to only those she expressed interest in.
While such notebooks management features are fully implemented by the Pundit
annotation server, their full support at UI level is still under development.
4 Pundit prototype
Pundit has a client-server architecture. The client-side component comprises a
set of sub-modules developed in Javascript using the dojo framework16 to fa-
cilitate cross-browser support. The client-side module implements the graphical
user interfaces to create and browse annotations as well as modules dedicated
to the communication with the server. The storage module defines a completely
generic interface, designed to support different kinds of storage systems rang-
ing from traditional relational databases to NoSQL databases (eg. RDF triple-
15
http://wiki.freebase.com/wiki/Freebase API
16
http://dojotoolkit.org/
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Proceedings of the 2nd International Workshop on Semantic Digital Archives (SDA 2012)
SemLib Annotation Server
Triplestore
Application Logic
RESTful API
User
Pundit Client
Read/write Notebook
annotations sharing Sharing/Collaborative
Annotations
Web Browser
Pundit Client
Groups of User
SMEs digital archives
or generic Web pages
Web Browser
Query/import Other web (and non web)
structured semantic data Annotation Reuse
application
"on the y"
Creates/explores annotations
while sur ng the web
User
Fig. 4: Simplified architecture of the annotation system
stores). In the prototype version, the storage is implemented using the Sesame
triplestore17 as this greatly simplifies handling and exporting RDF data. The
storage module, besides keeping user annotations, stores also user profiles and
related contextual information (e.g.: user’s metadata, user’s permissions, etc.).
The Annotation Server supports Open-ID18 for users authentication with single
sign-on. Different authentication systems can be easily implemented developing
dedicated plugins. The use of single sign-on approach simplifies the integration
of the annotation system with existing DL, which may already provide facili-
ties for users authentication. In the following subsections, some of Pundit main
features are discussed.
4.1 Annotations of different multimedia contents and at different
levels of granularity
Pundit provides specific Fragment Handlers to assist users in selecting and high-
lighting parts of different contents and turn them into actual addressable re-
sources (e.g. using XPointer or Media Fragments Uri) to be used into annota-
tions. This means that with Pundit it is not only possible to attach annotations
to single resource but also to establish semantic relations between different re-
sources fragments also of different type. Also, selected resources can be added to
“favourites’ (My Items) and stored to the server to be displayed also in different
pages other than the one in which they have been selected. This is fundamental
to create cross-page and cross-domain annotations as discussed in more details in
Sec. 4.4. At the time of writing Pundit prototype provides support for text frag-
ment and image selection, while image fragment annotation is currently under
17
http://www.openrdf.org/
18
http://openid.net/
55
Proceedings of the 2nd International Workshop on Semantic Digital Archives (SDA 2012)
Fig. 5: The Pundit Triple Composer (a) and an example of Pundit taxonomy (b)
development. In addition, the annotation of video and of temporal and spatial
video fragments has been already implemented in Semtube prototype[15]: a Web
tool for semantic video annotation of YouTube videos, which has been recently
developed basing on Pundit client API and Annotation Server.
4.2 Annotations at different levels of complexity and structure
Pundit provides support for different types of annotations, ranging from simple
textual comments and semantic tags to semantic statements. Annotations can
be created using different GUIs.
The Comment/tags Panel allows the user to type a comment and to auto-
matically extract tags from it using Dbpedia Spotlight service. User can remove
suggested tags that are not considered relevant or add others using Dbpedia
Lookup service.
The Recognizer Panel, Fig. 6 is intended to be used when a user wants to
mark the occurrence of a specific entity that is mentioned in text. Once one or
multiple words have been selected, the recognizer searches in a set of different
sources (including custom taxonomies, Freebase, DBpedia and Wordnet) and
suggests matching entities. Once “recognized’, entities mentioned in the text are
semantically disambiguated and enriched with structured data.
Fig. 6: The recognizer panel in action
56
Proceedings of the 2nd International Workshop on Semantic Digital Archives (SDA 2012)
Fig. 7: A screenshot of Pundit in action
Finally, the Triple Composer is the most expressive way of creating structured
data, providing a specific GUI for editing semantic statements (triples) in the
form of subject-object-predicate. All kinds of items (selected text, taxonomy
entries and web of data resources) can be used in statements and put in relations
by choosing from a customizable set of predicates. Statement can be create both
dragging and dropping items or choosing between suggested items as shown in
Fig. 5.a).
Fig. 5.b) shows the taxonomies tab. The ability of customizing Pundit with
domain specific taxonomies is an important feature of Pundit. Digital Library
maintainers can add custom taxonomies ”on the fly” just by adding a simple
markup to their pages, linking to a JSON file containing the taxonomy.
Fig. 7 shows the overall prototypal user interface to compose semantic anno-
tations and to display contextually created annotations.
4.3 Named Content
DLs, like other Web 2.0 applications, change over time. Presentation can be
restyled, changing page layout and mark-up, and content can be re-organized
and moved to different pages. In addition, the same content (e.g. a page of an
essay) can be accessible via different Web location (e.g. a summary page and
the whole essay page). In order to grant annotation consistency in such cases,
in particular when they are shared in communities and not under a centralized
control, it is not sufficient to attach annotations to the Web page.
To overcome this issue, Pundit relies on specific page mark-up. Compliant
digital libraries can benefit from a more intelligent behaviour by using the simple
named content specification (documented on the web site) to mark-up atomic
portions of their content as exemplified in Fig. 8. Each marked content should
57
Proceedings of the 2nd International Workshop on Semantic Digital Archives (SDA 2012)
Fig. 8: Using Named Contents to allow annotations to be attached to content
have a resolvable URI associated, to which annotations are attached. In this
way, annotations regarding the same content, but created in different pages, can
automatically be merged and consistently displayed in all the pages where such
content appears.
4.4 Cross-page and cross-domain annotations
Cross-pages annotation constitutes a key feature of the proposed annotation
system that captures the distributed nature of the Web, in which information
is often spread between different sources and can be augmented linking and
referencing additional information beyond the boundaries of single Web site or
DL. Properly structured annotations can allow weaving a semantic net in order
to interconnect and merge fragments of information into a unique knowledge
base. For example, an expert of literature can augment the information about
Dante Alighieri appearing on a Web page of a DL with text excerpts of the
Divine Comedy taken from another Web source. The implementation of such
feature requires the system be able to:
– create annotations on every Web page
– create relations between different resources (as text fragment, images, etc...)
belonging to different pages.
The former requirement is supported by the availability of the application as a
bookmarklet, which allows running the annotation system in every Web pages
injecting the required javascript. With such purpose, particular care has been re-
quired in protecting Pundit css and variable namespace, in order to avoid clashes
that could result in page style and layout alteration as well as in application mal-
functioning.
Regarding the latter requirement, it’s worth to remark how RDF data model
is perfectly suitable to cope with it, being in fact specifically conceived to create
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Proceedings of the 2nd International Workshop on Semantic Digital Archives (SDA 2012)
statements that connect two resources by means of a property. From an imple-
mentation point of view, such requirement is fully fulfilled by means of the Triple
Composer and by the MyItems mechanism, described in the previous subsection.
These allows, for example, a user to add an image to My Items later assert that
a text excerpt selected on another page describes the image.
5 Conclusions
In this paper, Pundit annotation system, which at the time of writing has reached
its first stable release, has been introduced. Pundit data model leverages on OAC
annotation model and further extends it to fully support the embodiment of se-
mantic statements in the annotation payload by means of named graphs. This
provides high flexibility to annotate and interconnect heterogeneous resources
over the Web and to be potentially applied in every application scenario. Pundit
prototype enables the creation of semantically rich annotations at high granu-
larity levels. These allow to interconnect different resources distributed over the
Web and augment original information generating new semantically structured
aggregations of knowledge. These can in turn be exploited both to provide user
with a more engaging and productive experience in consuming DL and Web
content, and effectively reused by other applications.
Compared with other existing semantic annotation tools, Pundit not only
provides support all the main annotation approaches introduced by others tools
(textual comments, semantic tagging, named entities recognition and the use of
taxonomies and ontologies) but enable also more expressivity and flexibility in
annotations. In particular, it allows the creation of semantic statements that en-
able to put in link resources, resource fragments, named entities and vocabulary
resource according to semantically defined relations.
In addition, differently by other tools, Pundit has been conceived to provide
specific support for annotation sharing, relying on the mechanism of notebooks
to aggregate relevant information and make these available both to other users
and third party applications by means of a dereferenciable URI and to be easily
consumed by means of RESTfull API.
A user evaluation of the tool has been conducted for the video annotation
prototype. The obtained results can be found in [15] and are driving the current
Pundit development. Further user evaluations are going to be performed on the
continuation of the development.
6 Acknowledgments
The research leading to these results has received funding from the European
Union’s Seventh Framework Programme managed by REA-Research Executive
Agency19 ([FP7/2007-2013][FP7/2007-2011]) under grant agreement n. 262301.
19
http://ec.europa.eu/research/rea
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Proceedings of the 2nd International Workshop on Semantic Digital Archives (SDA 2012)
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