FOAF-Academic Ontology: a vocabulary for the academic community

Edlira Kalemi Department of Computer Science

Faculty of IT, “Aleksander Moisiu” University Durres, Albania

edlirakalemi@uamd.edu.al

Edlira Martiri Department of Applied Informatics

Faculty of Economy, University of Tirana Tirana, Albania

edlira.martiri@unitir.edu.al

Abstract— The aim of Semantic Web is to add machine processable information to the Web. Our focus is on information related to people. This problem in Semantic Web is addressed by the FOAF Vocabulary. FOAF Vocabulary describes people, their activities and the people they know. The terms defined in this vocabulary let us say general things about us and people we know. But the terms in FOAF define people generally, and for example don’t let us talk about professional achievements and bring us near to specific academic communities of our interest. The entire social network is composed of communities, and we have chosen to contribute on academic community. In this article we introduce a new vocabulary, FOAF-Academic, which we have built up on the FOAF vocabulary by restricting it to communication in academic communities (e.g., exclude personal data), as well as extending it were required to cover academic-specific terms and relationships (e.g., add the co-author relationship). We have described this ontology and the technologies under which it is implemented. This ontology will help the academic community in saying anything about their achievements, their qualifications, activities and the communities that are near to them, in a machine readable format in order to be processed by both human and machine.

Keywords-component Ontology, FOAF, FOAF-Academic, vocabulary

I. INTRODUCTION Semantic technologies represent meaning using

ontologies and provide reasoning through the relationships, rules, logic, and conditions represented in those ontologies. With FOAF-Academic vocabulary we will express meaning related to people that are part of the academic community. The terms of the vocabulary will help in expressing it in a machine processable format for example the qualifications, the articles published by an author etc. After having a consistent and a well-defined ontology, the ontology may be populated through the profiles that will use it. Storing data in this knowledge based system may generate more and more knowledge based on the information that we add. All this can even be used very efficiently for different statistics, for example we can see how many articles does a certain author publish in the period of one year and if he do so in the same journal or in different ones, if he writes as a co-

author, if the other co-author is from the same department or he cooperates with other authors in other universities etc. Using and extending the knows property with subproperties like co-author or colleague will help in getting closer individuals with same research area or common professional interests. We will use the Web Ontology Language (OWL) [1] to build our ontology. We use OWL DL which is designed to support the existing Description Logic [2] and has computational properties for reasoning systems. Another language to write ontologies is RDF [3], the Resource Description Framework, but OWL has greater machine interpretability and a righer vocabulary than RDF. To extend the axioms and declare more complicated relationships between instances we will take advantage of the possibilities offered by SWRL, Semantic Web Rule Language [9]. Since an OWL-DL ontology can be translated into a Description Logic representation we have used a Description Logic reasoner [3] to perform automated reasoning over the ontology. A Description Logic reasoner performs various inferencing services, such as computing the inferred superclasses of a class, determining whether or not a class is consistent (a class is inconsistent if it cannot possibly have any instances), deciding whether or not one class is subsumed by another, etc.

In section 1 we describe ontologies and the Web Ontology Language that we use to create our ontology and some information about rules and how to write them. This section also gives the idea and explains the most used terms of the FOAF-Academic ontology, the rules that work inside the ontology. Section gives the idea and explains the most used terms of the FOAF-Academic ontology. The last section contains concluding remarks and discusses the potential future work in our problem domain.

II. ONTOLOGIES According to Gruber [4] an ontology is a formal

specification of the elements of a certain field of interest. It first was a branch of Philosophy as the “science of being”. Ontology comes from a Greek word which means “onto” – being and “logos” – speech.

The main reason why we use ontologies in our work is to model and describe the world, which in this case can be seen as a set of types, properties, relationships, etc. A Semantic

2011 Third International Conference on Intelligent Networking and Collaborative Systems

978-0-7695-4579-0/11 $26.00 © 2011 IEEE

DOI 10.1109/INCoS.2011.94

440

Web vocabulary can be considered as a special form of (usually light-weight) ontology, or sometimes also merely as a collection of URIs with an (usually informally) described meaning. An ontology provides a shared vocabulary, which can be used to model a domain, the type of objects and/or concepts that exist, and their properties and relations.

An ontology describes the concepts in the domain and also the relationships that hold between those concepts. The standard ontology language from the World Wide Web Consortium (W3C) is OWL [1]. The OWL (Web Ontology Language) is designed for use by applications that need to process the content of information instead of just presenting information to humans. OWL language may be categorized into three species or sub-languages: OWL-Lite, OWL-DL and OWL-Full. A defining feature of each sub-language is its expressiveness. OWL-Lite is the least expressive sub-language. OWL-Full is the most expressive sub-language. The expressiveness of OWL-DL falls between that of OWL-Lite and OWL-Full. OWL-DL may be considered as an extension of OWL-Lite and OWL-Full an extension of OWL-DL.

An OWL ontology consists of Individuals, Properties, and Classes. In Figure 1 is shown the relation between this features.

Figure 1. OWL properties, classes, relations[19]

Individuals, represent objects in the domain that we are interested in. Individuals are also known as instances.

Properties are binary relations on individuals - i.e. properties link two individuals together. For example the teaches connects the class Professor with the class Course Properties can have inverses i.e. the property hasResearchField has an inverse property isResearchFieldof. Datatype properties describe relationships between individuals and data values.

The OWL adds considerable expressive power to the Semantic Web. However, for a variety of reasons, including retaining the decidability of key inference problems in OWL DL and OWL Lite, OWL has expressive limitations. Many of the limitations of OWL stem from the fact that, while the language includes a relatively rich set of class constructors, the language provided for talking about properties is much weaker. In particular, there is no composition constructor, so it is impossible to capture relationships between a composite property and another (possibly composite) property. An alternative way to overcome some of the expressive

restrictions of OWL is to extend it with some form of “rules language”.

The extended language, called the Semantic Web Rules Language (SWRL) which we use to write the rules, is considerably more powerful than OWL DL.

A. FOAF Vocabulary and syntax FOAF Vocabulary it is defined by the namespace URI

http://xmlns.com/foaf/0.1/. FOAF offers a vocabulary for putting machine readable code into a webpage, making it possible to link from one site, person, company etc to others that are expressed in the same format. This vocabulary depends on XML, XML Namespaces, RDF, and OWL and is managed as an Open Source rather than industry standardization. We have listed in Table 1 the main classes and properties of FOAF ontology divided by category.

TABLE I. FOAF TERMS DIVIDED BY CATEGORIES

III. FOAF-ACADEMIC

The foafacademic ontology is composed of the following classes, some of which are the one derived from the foaf ontology like the class Person, for instance. This ontology

Personal Info Online Accounts / IM

weblog knows interest currentProject pastProject plan based_near age workplaceHomepage workInfoHomepage schoolHomepage topic_interest publications geekcode myersBriggs

OnlineAccount OnlineChatAccount OnlineEcommerceAccount OnlineGamingAccount account accountServiceHomepage accountName icqChatID msnChatID aimChatID jabberID yahooChatID skypeID

FOAF Basics Documents and Images

Agent Person name nick title homepage mbox mbox_sha1sum img depiction (depicts) surname familyName givenName firstName lastName

Document Image PersonalProfileDocument topic (page) primaryTopic (primaryTopicOf) tipjar sha1 made (maker) thumbnail logo Projects and Groups Project Organization Group Member

441

will contain even elements for describing universities and activities that occur at them [5]. Here we will introduce some of the main classes that compose the ontology and a clear definition of the role that they play. During the class declaration, there are used two different namespaces foaf and afoaf, and they are respectively used to represent the FOAF ontology and the FOAF-Academic ontology.

TABLE II. FULL LIST OF CLASSES OF THE FOAF-ACADEMIC

afoaf:Academic_Staf afoaf:Course afoaf:Discipline afoaf:Magazine afoaf:Professor afoaf:Publications_

Event afoaf:Researcher afoaf:Study_Program afoaf:Staf afoaf:Student foaf:Project afoaf:Undergraduated

afoaf:Student afoaf:University afoaf:Asistant afoaf:Doctorate_

School afoaf:Event afoaf:Master_Student foaf:Organization afoaf:Professors_

Council afoaf:Reasearcher afoaf:School_Event afoaf:Research_

Field afoaf:Schoolarships afoaf:Scientific_

Event

afoaf:Administrativ_Staf afoaf:Book afoaf:Conferenc afoaf:Department afoaf:Faculty afoaf:Graduated foaf:Group afoaf:Journal afoaf:Lecturer foaf: Person afoaf:PhD_Student afoaf:Workshop

Figure 2 gives the list of classes in a hierarchical view.

Figure 2. Fig. 2 The hierarchical view of all classes.

Some examples of classes are: a) University

The class University is one of the main classes. It is the class that collects the individuals that most probably will take us near to the academic community.

In OWL DL this will be expressed with the following syntax: <!-- http://www.owl-ontologies.com/Afoaf.owl#University --> <owl:Class rdf:about="&Afoaf; University "> </owl:Class>

b) Academic Staff

This class represents the persons that work in a university as an academic staff i.e. a lecturer, a professor etc. Academic Staff is a subclass of the class Staff.

http://www.owl-ontologies.com/Afoaf.owl#Academic Staff

sub-class of: http://www.owl-ontologies.com/Afoaf.owl#Thingsub-class of: http://www.owl-ontologies.com/Afoaf.owl#Staffone of: {Lecurer, Assistant, Profesor}

c) Student

We use this class to collect the individuals that are still in the status of a student. This class is a subclass of the class University and has two subclasses Graduated and Undergraduated.

http://www.owl-ontologies.com/Afoaf.owl#University sub-class of: http://www.owl-ontologies.com/Afoaf.owl#Thing

http://www.owl-ontologies.com/Afoaf.owl#Student

sub-class of: http://www.owl-ontologies.com/Afoaf.owl#Thing sub-class of: http://www.owl-ontologies.com/Afoaf.owl#University

442

d) Department A faculty is organized in departments, this class represents a department.

http://www.owl-ontologies.com/Afoaf.owl#Department

sub-class of: http://www.owl-ontologies.com/Afoaf.owl#Thing sub-class of: http://www.owl-ntologies.com/Afoaf.owl#University sub-class of: http://www.owl-ontologies.com/Afoaf.owl#Faculty

This is the list of object properties: • disciplineOf • hasResearchInterest • hasDiscipline • hasauthor • directorof • deanof • member • page • primaryTopic • topic • fundedBy • pastProject • currentProject • publications • authorof • works • teaches • supervises • studies-at • researchInterestOf • rectorof • partof • issupervised-by • is-tought-by • headof • knows • same-project • same-department • colleague • co-supervisor • same-subject • co-author Some examples of object properties are: e) knows

A person known by this person. The foaf:knows property relates a foaf:Person to another foaf:Person that he or she knows. This is a property of the foaf ontology and, we have extended it with some subproperty that specify the academic connection that this two known persons have.

http://www.owl-ontologies.com/foaf.owl#knows

domain: http://www.owl-ontologies.com/foaf.owl#Person

range: http://www.owl-ontologies.com/foaf.owl#Person

f) co-author

This property connects two persons that are authors of the same publication. http://www.owl-ontologies.com/co-author

sub-property of: http://www.owl-ontologies.com/foaf.owl#knows domain: http://www.owl-ontologies.com/foaf.owl#Person

range: http://www.owl-ontologies.com/foaf.owl#Person

g) co-supervisor

The co-supervisor property connects two professors that supervise the same student. http://www.owl-ontologies.com/foaf.owl# co-supervisor

sub-property of: http://www.owl-ontologies.com/foaf.owl#knows domain: http://www.owl-ontologies.com/foaf.owl#Person

range: http://www.owl-ontologies.com/foaf.owl#Person

h) colleague

Connects two individuals that are colleagues to each other. http://www.owl-ontologies.com/foaf.owl# colleague

sub-property of: http://www.owl-ontologies.com/foaf.owl#knows domain: http://www.owl-ontologies.com/foaf.owl#Person

range: http://www.owl-ontologies.com/foaf.owl#Person

i) same-department

A relation between individuals that are part of the same department. http://www.owl-ontologies.com/foaf.owl# same-department sub-property of: http://www.owl-ontologies.com/foaf.owl#knows domain: http://www.owl-ontologies.com/foaf.owl#Person

range: http://www.owl-ontologies.com/foaf.owl#Person

443

j) same-project A relation that exists between individuals that are working or have worked in the same project. http://www.owl-ontologies.com/foaf.owl# same-project

sub-property of: http://www.owl-ontologies.com/foaf.owl#knows domain: http://www.owl-ontologies.com/foaf.owl#Person

range: http://www.owl-ontologies.com/foaf.owl#Person

B. Rules We have seen in detail the classes, object properties and

data properties of the ontology. Another important part of foafacademic is the definition of the axioms which will help in generating more knowledge. Not only the information inferred will be richer but also the level of assurance about the right signification of the data will be greater. Let’s see one by one the rules defined in foafacademic. Every rule is labeled by a number, expressed in the SWRL language, and explained next.

University(?A), Person(?B), Person(?C), works(?B, ?A), works(?C, ?A) -> colleague(?B, ?C)

Rule 1: If both person B and person C work at the university A than they are colleagues.

Department(?d), Person(?x), Person(?y), works(?x, ?d), works(?y, ?d) -> same-department(?x, ?y)

Rule 2: If person x and person y work at department d than they are in the same department. The fact of being in the same department includes even the fact that they are colleagues.

Person(?y), studies-at(?y, ?a) -> Student(?y) Rule 3: If a person studies at any university, than he/she

is a student. So it directly becomes part of the class Student. To illustrate how these rules affect the instances, here is a view (see Figure 3) of the instance Ejona. This is an instance of the class person which studies at an university named UAMD. The part highlighted in yellow is the part generated by the reasoner witch has concluded that since Ejona studies at some university she is a student.

a.

b.

Figure 3. a, b. Values of the instance with the name Ejona.

Book(?x), authorof(?D, ?x), authorof(?P, ?x) -> co-author(?P, ?D)

Rule 4: If D is author of x and P is also author of x than P

and D are co-authors. It is the case when a book or article is written by two or more authors. Only with rules we were able to express the situation of coauthors, using just OWL-DL was impossible to write it. In Figure 4 we see that the instance Nepravishta is the author of the book titled Arkitekture and bellow is generated that is coauthor with the instance Deshira_Imeri. This because of the fact that Deshira_Imeri is also author of the same book and because of the rule 4.

a.

b.

Figure 4. Values of the instance with the name Nepravishta.

IV. CONCLUSIONS This article describes ontologies, which are the backbone

of the Semantic Web, their development and the advantages that bring their usage. The introduction of the FOAF (friend of a friend) ontology highlights the advantages of using such technologies on publishing data on the in order to reach the semantic web vision so that the computer comes near to our understanding. Convinced on these abilities of

444

using ontologies we describe the development of a new ontology FOAF-Academic which will help the academic communities to add to the web semantic data. This ontology will be about creating a network between people based on their background of study, their research area, their origin of the Universitys or Educational Institutions where thay have studiet or worked etc. This ontology except having well defined terms it is also reach of logical rules in order to generate more and more knowledge by the human the machine too.

Ontologies have the potential of enabling true knowledge sharing and reuse among heterogeneous agents, both human and computer. One major open challenge is still the alignment of different ontologies in order to allow inter-operation between heterogeneous agents.

References

[1] http://www.w3.org/TR/owl-features/ [2] http://en.wikipedia.org/wiki/Description_logic [3] Thomas B. Passin, “Explorers guide to the Semantic Web”, Manning

Publications Co, 2004

[4] T. Gruber, "A translation approach to portable ontology specifications", (1993)

[5] http://www.cs.umd.edu/projects/plus/SHOE/onts/univ1.0.html [6] Peter Mika , “Social Networks and the Semantic Web”, in Springer

Science+Business Media, LLC, 2007 [7] Tom Gruber, "Where the Social Web Meets the Semantic Web",

Keynote presentation at ISWC, The 5th International Semantic Web Conference, November 7, 2006

[8] Steffen Staab and Rudi Studer, “Handbook on Ontologies”, Springer (2009)

[9] A. De Nicola, M. Missikoff, R. Navigli, "A Software Engineering Approach to Ontology Building". Information Systems, 34(2), Elsevier, 2009

[10] Gruber T., “Towards Principles for the Design of Ontologies Used for Knowledge Sharing”, International Journal of Human-Computer studies, (1995).

[11] Guarino N. & Welty C., “Evaluating Ontological Decisions with OntoClean”, in Communications of the ACM, 2002

[12] Guarino N, “Formal Ontologies and Information Systems”, in Guarino N. (ed.), Proc. of FOIS98, IOS Press, p.,(1998)

[13] Halpin T., “Information Modeling and Relational Databases: from conceptual analysis to logical design”, Morgan-Kaufmann, San Francisco (2001)

[14] http://www.owl-ontologies.com/foaf.owl##sec-foafsw [15] http://www.ibm.com/developerworks/web/library/wa-semweb/ [16] http://en.wikipedia.org/wiki/Semantic_Web [17] http://en.wikipedia.org/wiki/Ontology_%28information_science%29 [18] http://semanticweb.org/wiki/Ontology [19] http://www.w3c.it/talks/2009/athena/slides.html#(52)

445