A Comprehensive Framework for Semantic Annotation of

Web Content

Manuel Fiorelli

, Maria Teresa Pazienza

and Armando Stellato

Department of Civil Engineering and Computer Science, University of Rome, Tor Vergata, Rome, Italy

Department of Enterprise Engineering,University of Rome, Tor Vergata, Rome, Italy

Keywords: Semantic Annotation, Semantic Web, User Interface, Software Engineering.

Abstract: Studies on Semantic Annotation reveal how trying to match heterogeneous requirements leads to divergent

methodologies, models and processes for annotation management and exchange. Community efforts

towards the development of shared solutions are important to reduce the “entropy” of the field; nonetheless,

any agreement on the ultimate annotation system is unlikely to be achieved. We propose a solution to this

problem by defining a comprehensive framework, unbound to any specific design/annotation model, and

instantiable into concrete system implementations, to meet different requirements. Towards this goal, we

commit to fairly general assumptions, valid across disparate systems and not excessively constraining.

Firstly, most systems deal with combined management of ontologies and Web content. Secondly, these

systems can be described through a common behavioural model, in terms of an assignment of handlers to

predetermined events. This behavioural model can be then enriched through progressive levels of

specification, thus fostering a convention-over-configuration approach in detailing its characteristics. Then,

recurring design fragments can be identified, in order to provide abstractions and specifications for the

definition of concrete handlers.

1 INTRODUCTION

In the envisioned Semantic Web (Berners-Lee et al.,

2001) the meaning of resources, possibly including

services (Payne and Lassila, 2004), is captured

through annotations with respect to well-defined

ontologies. Formalized knowledge is believed to

allow software agents to better interact with Web

resources and perform intelligent tasks on behalf of

humans, such as buying a vacation package from a

virtual travel agency.

The actual deployment of the Semantic Web

required further investigation on pragmatic aspects

related to the publication and the reuse of disparate

knowledge on the Web. This line of development

eventually flowed into the Linked Open Data

movement which elaborated a collection of best-

practices (Heath and Bizer, 2011) aimed at better

connecting the Semantic Web to the architecture of

the Web. About this topic (Heath, 2009) states that

“Linked Data isn’t about rebranding the Semantic

Web, it’s about clarifying its fundamentals”.

The interest on data publication and integration

is complementary to the idea of annotating

traditional information resources (documents,

images, audio and video material), since the former

provides a sound technological and methodological

framework supporting the latter. In line with this

idea, the W3C defines the SKOS vocabulary (W3C,

2009) as a means to establish a link between the

Linked Open Data cloud and the world of

Knowledge Organization Systems (Hodge, 2000),

historically employed by museums, libraries and

other large organizations to better manage and use

their large body of resources.

So far, systems for annotating information

content with respect to formalized knowledge have

followed different and occasionally contrasting

theories. These theories differentiated in many

aspects: the primary focus of the annotation (e.g. is

the traditional content which needs to be annotated

with respect to a generic category, or are specific

ontological resources to be grounded on existing

documentation?), the granularity of the information

to be reported, and the nature of the annotated

elements. Therefore, even the offer of Semantic

Annotation applications is variegated, and it is often

difficult to see all of the requirements for a particular

245

Fiorelli M., Pazienza M. and Stellato A..

A Comprehensive Framework for Semantic Annotation of Web Content.

DOI: 10.5220/0004545702450252

In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (KEOD-2013), pages 245-252

ISBN: 978-989-8565-81-5

 2013 SCITEPRESS (Science and Technology Publications, Lda.)

usage scenario satisfied by a single system.

We propose here a framework for supporting the

development of systems for combined management

of ontological knowledge and Web content,

including, but not limited to Semantic Annotation

Systems. The framework is a subsystem of Semantic

Turkey (Pazienza et al., 2012), a fully-fledged

environment for knowledge management and

acquisition based on RDF technologies (W3C,

2004), with a user interface deployed as a browser

extension. Such an offer guarantees to end

applications a high level of integration among

browsing capabilities, ontology editing and cross-

boundary features concerning both.

The rest of the paper is organized as follows. In

section 2, we review the state-of-the-art in the field.

In section 3, we motivate our work. In section 4, we

elicit requirements for our framework, while we

discuss its architecture in section 5. Finally, in

section 6, we conclude and outline future works.

2 BACKGROUND

We can shortly state that an annotation establishes a

link between two resources, asserting that one is

“somewhat” about the other. The nature of this

association is heavily domain and application

dependent. For instance, informal free-text

annotations are usually found as comments in a

document to drive its edition, while structured

annotations are the output of numerous NLP tasks,

including named entity recognition and relation

extraction. These scenarios depend on different

assumptions regarding the nature of the annotations,

their granularity, their level of formality and the use,

if any, of formal ontologies.

Early works on the annotation of Web resources

include Annotea (Kahan and Koivunen, 2001),

which aimed at establishing a framework for the

collaborative annotation of Web resources. Initially

thought for supporting the collaborative

development of specifications within the W3C, the

project aimed at establishing standards for textual

annotations of marked-up documents.

Later initiatives within the bioinformatics

community, Annotation Ontology (Ciccarese et al.,

2011) and Open Annotation Model (Sanderson and

Van de Sompel, 2010), had a wider breath, aimed at

the annotation of any media type possibly with

respect to a supplied ontology. Those projects

flowed into the Open Annotation W3C community

project, whose mission is to develop an RDF based

model for the annotation of digital artefacts. The

Domeo annotation system developed by (Ciccarese,

et al., 2012) supports the Annotation Ontology and it

is expected to adopt the results of the novel W3C

Community Group. With respect to early attempts, it

is worth of notice that a shared data model is

deemed sufficient, whereas dedicated protocols for

querying and manipulating the annotations are no

longer considered necessary, thanks to the

availability of standards for performing such tasks

developed meanwhile (e.g. SPARQL

(Prud'hommeaux and Seaborne, 2008)).

In the context of these RDF models an

annotation is established though the assertion of at

least a statement relating a resource (the target) to

another (the body) which represents the desired

attachment. In case of Semantic Annotation the

latter is found within a formally defined ontology.

The choice of a domain/application ontology should

reflect the particular point of view behind the

annotation process. (Ma et al., 2011) introduced a

higher order semantics for capturing the meaning of

semantic annotations with respect to the ontological

nature of the attached resource and how it is related

to the target. They also show how different levels of

analysis (i.e. linguistic and semantic) can cooperate,

for example to suggest annotations or highlight

possible errors.

Beyond the problems inherent to the

representation of annotations, there is need for a

clear process to create and maintain them.

According to (Staab et al., 2000), this process should

cope with the evolution of the domain ontology and

the presence of mirrors or altered version of the

annotated resources.

The production of annotations by human users is

often regarded as the bottleneck limiting the scale of

the annotation process. (Kiryakov et al., 2004)

discussed the design issues related to an holistic

system integrating semantic annotations, indexing

and (semantically powered) retrieval. They propose

the reengineering of state-of-the-art NLP tools for

automatically producing semantic annotations with

respect to a lightweight upper ontology, called

KIMO. The existence of a reference upper ontology,

possibly extensible to address domain and

application specific needs, is a distinctive feature,

since most works assume that semantic annotations

are taken against any arbitrary domain ontology.

This idea was implemented in the platform KIM

(Popov et al., 2003), which was heavily tested for

the automatic annotation of news stories.

Finally, (Uren et al., 2006) provided an overview

of Semantic Annotation systems by comparing them

on the basis of a set of requirements that the authors

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consider key-features for the annotation task.

3 MOTIVATION

In the previous section we outlined the main

research lines in the field of Semantic Annotation,

showing how conflicting requirements demand

diverging design decisions, making the definitive

annotation system unlikely to appear.

Even a strong agreement on a universal data

model for annotations is difficult to achieve: recent

proposals focus on widely accepted usage scenarios,

therefore failing to satisfy very specific needs.

Divergent methodologies have been proposed to

support manual annotation rather than automatic

generation of annotations. The latter can benefit, as

shown by KIM, of the reuse of state-of-the-art IE

tools; this entailing complex integration challenges.

Incompatible design decisions tend to cumulate,

leading to very different system architectures and

implementations. Therefore, pursuing the goal of

realizing the ultimate annotation system appears to

be fruitless, while it appears reasonable to aim at the

definition of a comprehensive framework supporting

alternative designs.

Analogously, designing a framework unbound to

any prior assumption makes no sense as well,

because an architecture is always based on some

grounding which characterizes its offer to the user.

Therefore, our contribution narrows its scope to

Semantic Web annotation systems and, in general,

any application combining ontological knowledge

with Web content. This is a fairly general model

which avoids any commitment to specific goals,

interaction patterns, methodology (e.g. human

labour vs machine learning) or presentation

mechanisms.

For what concerns the scope of our architecture

(RDF and Web Documents), RDF is by no means

the only formalism to capture semantics, though it is

now widely spread and there are different W3C

recommended vocabularies supporting different

modelling needs. The choice for supporting Web

documents is mostly a starting point (which does not

contradict the generality of the approach), and future

evolutions may foresee extensions for other kind of

sources, different in format or media type.

4 SYNTHESIS OF

REQUIREMENTS

In order to design the architecture of a

comprehensive framework for Semantic Annotation,

we have both analysed state-of-the-art systems, and

taken into consideration principles for their design

acquired from literature.

While we take into account the results of the

discussed standardization efforts (see section 2), we

decided not to commit to a specific model, and have

instead an agnostic approach, which starts from the

mere annotation acts and allows for the adoption of

arbitrary models.

We have thus adopted and incremented the

feature classification provided by (Uren et al., 2006),

and positioned the class of systems that can be

realized with our framework, with respect to those

requirements:

 Standard Formats: RDF(S), OWL and SKOS for

the representation of semantic descriptors;

pluggable models for Semantic Annotation (most

notable models provided by default as libraries);

concrete implementations for different ranges

should be provided as component libraries (e.g.

offset or XPointer (DeRose et al., 2002) based

ranges).

 User Centred/collaborative Design: the UI for

ontology editing/annotation should be deployed

as a web browser extension, while the browser

itself hosts the web content. This approach

exploits an environment the user is well

acquainted with (the browser), while providing

new functionalities.

 Ontology Support: the framework should support

the editing of arbitrary ontologies to be used as

domain for annotations;

 Support of Heterogeneous Document Formats: it

is indeed a desirable feature, though currently

our framework is tailored to Web documents;

however, this is a technological limitation of the

current implementation and not a theoretical

choice.

 Document Evolution: different choices in the

annotation format and in data preservation may

be more or less prone to degradation with respect

to the evolution of the annotated content; the

framework should permit to retain metadata

about the target document to be able to detect

changes. Option for XPointers guarantees better

resilience to changes than plain offsets;

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 Annotation Storage: as noted in the (Uren et al.,

2006), there is no universally winning choice for

storing the annotation content: the framework

should thus allow annotations to be stored

separately from the annotated resources (offline

annotations), or to be embedded into them.

 Automation: hosting of components for

automatic annotation of content should be

supported, as well as productive exploitation of

their results and suitable interaction with the user

for validating and refining these results.

 Granularity: both coarse grain and fragment

level;

5 ARCHITECTURE

This section is organized as follows: we introduce

by first the concepts that have driven the synthesis of

the architecture; we then detail specific design

choices; finally, we describe the end-user

customizability.

5.1 Concept

The proposed framework has to support applications

interacting with Web content. (Kahan and Koivunen,

2001) distinguish two strategies to meet this

requirement: whether dedicated capabilities are

injected into the browser, or into the content

provided by a proxy. Our research effort focuses on

the first approach, by relying on the extensibility of

modern Web browsers to develop the additional

capabilities. The user experience with the browser

does not change in traditional web navigation, and is

only minimally affected when users explicitly

trigger one of the extended annotation capabilities.

Despite being tightly coupled with the Web, a

browser extension is under all aspects a desktop

application, with all the advantages deriving in terms

of robustness, integration with the local system, and

customizability.

In our usage scenario (see ), the traditional

browser frame for visualizing the web content is

complemented with a dedicated panel showing the

reference domain model (e.g. an OWL ontology or a

SKOS concept scheme).

Possible interactions fall into three main

categories, with respect to the resources they affect.

The first category comprises the interactions devoted

to the navigation of the Web, for instance, activating

a hyperlink to reach another Web page. As discussed

in section 3, those interactions are completely

managed by the hosting browser. The user might as

well modify the domain model through interactions

falling into the second category. Finally, there are

interactions that encompass both realms: for

instance, when the user drags a selection of text

from a Web page and drops it onto a resource, as

common in most annotation systems.

Our work develops from this scenario, by

identifying a framework for realizing applications

tied to both ontological resources and Web content,

and not necessarily limited to semantic annotation.

In our setting, we envision unlimited binding

possibilities between annotated content fragments,

their originating sources and the resources belonging

to the domain model. This should allow, for

instance, to generate new ontology individuals while

annotating their occurrences within web pages, to

create and annotate relationships between

individuals, etc..

The framework abstracts a collection of events

out of gestures involving concrete user interface

elements. These events are, to an extent,

independent from the underlying presentation

mechanism and the supporting technology. The

framework dispatches events to suitable handlers,

which implement application dependent logic. Event

handlers must implement a given signature, whereas

there is no prescription on their internal structure.

Within this framework, collections of event

handlers define concrete applications, which might

be characterized through a variety of (possibly

orthogonal) dimensions, including, but not limited

to, the following:

 annotation model;

 presentation mechanism;

 relevant ontological resources.

While two applications might differ along a few

of those dimensions, they could be very close to

each other along others. Therefore, applications are

rarely completely orthogonal and in most cases share

part of their user interface, behaviour and data

management.

The paradigm based on the assignment of

handlers to events meets the requirement of

minimum commitment to the application goals.

Nonetheless, the fact that most applications have

overlapping designs would force the developers to

implement the same user interfaces and behaviours

multiple times. Therefore, a collection of ready-to-

use components for common design fragments is

required.

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5.2 Design

In the forthcoming we refer to a combination of an

annotation model, events and related handlers as an

annotation family, and by a slight abuse of language

we will identify possible applications with distinct

annotation families. We discuss here three different

levels for characterizing a family.

Currently, the framework (see ) declares the

following events:

 selectionOverResource: when a selection from a

Web page is dropped onto an ontological

resource

 resourceOverContent: upon gestures for the

association of Web content with an ontological

resource regardless of their occurrence in the text

 contentLoaded: triggered when Web content is

loaded, in order to execute presentation related

activities, e.g. highlighting the annotated

fragments

So far, this basic set of events provides a core

specification, which is sufficient to implement the

entire machinery for an annotation system: handlers

for the first two events encapsulate the logic for the

creation of new annotations, whilst a handler for the

third event is in charge of retrieving and properly

visualizing annotations for a Web content (and for

injecting the code to manage them). For instance,

operations such as the deletion of annotations can

actually be invoked by code which is injected into

the content by handlers intercepting the

contentLoaded event, thus leaving the specification

of these functions opaque to the framework.

The framework treats different genres of RDF

resources (e.g. classes, individuals, and properties)

in a uniform manner, by declaring events concerning

only generic resources. The uniform treatment of

resources entails that the same event might be

handled differently on the basis of the target

resource. Moreover, applications might foresee the

binding of multiple distinct handlers (see ) to an

event related to a single resource, each handler

implementing a distinct way for consuming that

event. A mechanism based on preconditions allows

guarding the execution of handlers on the basis of

contextual information. Standard preconditions are

also defined and provided with the framework. The

basic preconditions include filters based on the role

of the resource (e.g. a class, individual etc..), so that

a given handler may be activated only for certain

resources. The discussion above might be more

accessible through an example concerning the event

selectionOverResource. As stated previously this

event is fired when a selection from a Web page is

dropped onto a resource, regardless of its type.

Actually, this event might be processed in several

ways. By first, a handler may simply annotate an

occurrence of that resource within the Web page.

Other handling strategies include more complex

activities, which are valid only on a subset of the

events. For instance, when the target is a class, a

handler might create and annotate a new instance for

that class, basing on the selected content; otherwise,

if the target is a SKOS concept, another handler

might create and annotate a narrower concept.

Figure 1: Overview of the Annotation Framework. The Web page is annotated with concepts (insects, plants and pesticides)

and relations (isPestOf) from the thesaurus AGROVOC.

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Figure 2: Event Based Architecture.

By following a convention-over-configuration

approach to design, we provided a further level of

specification, consisting in a set of interfaces which,

if implemented, can be exploited by the framework

on the basis of the previously defined events. The

following abstract services can thus be implemented

for each family:

 checkAnnotationsForContent(contentID)

This function checks whether a given content

source has been annotated. By default, this

function is invoked by a framework

predefined handler, upon triggering of the

contentLoaded event

 getAnnotationsForContent(contentID)

This function returns the annotations taken

over a specific content source. Actually, it

returns proxies for the annotations (which

depend on the model) exposing some

framework mandatory fields, such as the id

and range of the annotations. The

implementation/serialization of these

annotation elements is left to the specific

family, and must be consistent with the other

services implemented in the family.

This function is automatically invoked by the

framework after a positive (returned value =

true) check performed by the previous

function (in the context of a contentLoaded

event).

 getAnnotationsForResource(RDFResource)

Analogous to the previous one, this function

retrieves all annotations associated to a given

RDF resource.

When constructing a description for a RDF

resource in the UI, the framework may exploit

this function to produce a list of actionable

links to annotated content sources.

 decorateContent(annotations)

This is a client function for injecting elements

inside the content, usually to show the

annotations which have been previously taken

over it.

A standard text highlighting mechanism for

web documents is provided by the system and

invoked on the result of a

getAnnotationsForContent(), in the context of

a contentLoaded event. This mechanism can

be overridden by implementing this function

with custom content decorators.

 deleteAnnotation(annotID)

This function takes care of removing all the

information related to a given annotation. The

standard highlighter injects calls to this

function for each annotation shown on the

web document.

The system thus, in line with the convention-

over-configuration paradigm, allows for high

flexibility, while reducing effort and need for

detailed specification through massive availability of

conventions (and in some cases, implementations).

5.3 Implementation

The annotation framework we presented is

embedded in the Knowledge Management and

Acquisition Platform Semantic Turkey (Pazienza et

Handlers

Families

bookmarking

open annoation

(coarse grain)

open annoation

(fine grain)

Events

 selectionOverResource

 resourceOverContent

 contentLoaded

 selectionOverResource

 resourceOverContent

 contentLoaded

 selectionOverResource

 resourceOverContent

 contentLoaded

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Figure 3: End-user Customization: handlers are enabled for a given event and can then be filtered – by editing their

preconditions – when that event is fired.

al., 2012), and comes out-the-box with a few

annotation families which differ in the underlying

annotation model and, notably, in the tasks they

support. The default handlers take into consideration

the annotation of atomic ontological resources, and

complex activities that are provided as macros, e.g.

the creation of new instances, the definition of new

subclasses in OWL, or of narrower concepts in

SKOS. Semantic Turkey works on a per-project

basis, and by default, annotations are stored as

further RDF metadata inside the RDF repository of

the managed project.

Semantic Turkey allows the deployment of third-

party annotation families, additional preconditions,

or the enrichment of existing ones by the addition of

further handlers. The hosting platform offers to the

implementers a wide choice of reusable capabilities.

The browser provides technologies for the definition

of user interfaces, the manipulation of information

resources and the interaction with the Web. An

annotation family might exploit them to support

inline annotations (included in the document itself),

which can then be saved in a updated copy of the

web page. An annotation family may depend on core

services provided by Semantic Turkey as well as

define new ones for dealing with the specifics of its

annotation mechanism. There is however no limit to

the features that can be provided by adding new

services, e.g. dedicated export mechanisms and

ontology evolution management.

5.4 End-user Customizability

For any given family of annotations, even final users

(i.e. human annotators) may customize their

experience to some extent, with no need of coding

intervention nor of performing complex

configuration on the system.

Concretely, a user can customize a family (see )

by enabling only a portion of the annotation

functionalities associated to each event, or by

refining the preconditions of its associated handlers.

Most usage scenarios in fact, only concern with a

subset of the possible interactions which a given

family may offer, and users may want to enable only

those actions which they are using in their setting.

Users are normally prompted with the list of suitable

handlers (obviously, well presented through

appropriated descriptors) after they trigger an event

as a consequence of performing an action; as an

automatic shortcut, when such a list reduces to a

single handler, it is executed without prompting the

user.

6 CONCLUSIONS AND FUTURE

WORKS

The proposed framework has been experimented in

its evolution, through the development of several

concrete applications for semantic annotation

(Fallucchi et al., 2008; Pazienza et al., 2009;

Pazienza et al., 2012). These experiences have

helped us in understanding the features which a core

framework for semantic annotation should exhibit,

and the right trade-off in flexibility which should be

granted to system developers, while still benefiting

them with concrete support from the software.

Evaluation of frameworks in general is difficult

to perform and is based on non-standard

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251

considerations (e.g. the set of features must be

decided arbitrarily), which are inherently highly

biased by the aspects being put into examination.

However, we plan for the future to offer an overall

view of the features offered by most notable

annotation systems at the current state of the art, and

observe if these can be enabled in our framework.

By emphasizing the amount of development effort

necessary when developing a system with specific

features, and the effort that is required to master our

framework and build those same features over it, we

can obtain a fair map of the improvements and

benefits in adopting it. Regarding further evolutions,

while the framework seems to us general enough in

its basic assumptions, we want to improve it in terms

of concrete support to developers. We will thus

increment the set of available conventions and create

template libraries for recurring annotation patterns.

These libraries will provide partial implementations,

which can be bound to specific needs through

dedicated extension points. Our interest in semi-

supervised processes for knowledge acquisition

(Fiorelli et al., 2010) motivates our attention to

integrating automatic extraction engines and to

combining them with proper human interaction, into

more virtuous acquisition workflows. We have

already explored this approach in (Pazienza et al.,

2012), with the development of a text analytics

system for the discovery of new semantic relations

among concepts belonging to the AGROVOC

thesaurus (Caracciolo et al., 2012). We plan to

integrate this system to the proposed framework and,

in the meanwhile, extend its scope to the projection

of arbitrary information onto an ontology.

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