NeOn-project.org

NeOn: Lifecycle Support for Networked Ontologies  

D2.1.1 Collaborative Aspects of Networked Ontologies – State of the Art
Deliverable co-ordinator: 
Carola Catenacci
Deliverable authors: 
Carola Catenacci, Aldo Gangemi,  Jos Lehmann, 
Malvina Nissim, Valentina Presutti
(CNR) 
with Contributions from …

Abstract.
EU-IST Integrated Project (IP) IST-2006-027595 NeOn
Deliverable D2.1.1 (WP2.1)
We present a state-of-the-art survey for the representation of collaborative aspects of networked ontologies

Keyword list: networked ontologies, design rationales, collaboration

Document Identifier:	NEON/2006/D2.1.1/v0.1	Date due:	September 6, 2006	
Class Deliverable:	NEON EU-IST-2005-027595	Submission date:	September x, 2006	
Project start date:	March 1, 2006	Version:	V0.1	
Project duration:	4 years	State:	draft	
		Distribution:	public	

NeOn Consortium
This document is part of a research project funded by the IST Programme of the Commission of the European Communities, grant number IST-2005-027595. The following partners are involved in the project:

Open University (OU) – Coordinator
Knowledge Media Institute – KMi
Berrill Building, Walton Hall
Milton Keynes,  MK7 6AA
United Kingdom
Contact person: Martin Dzbor, Enrico Motta
E-mail address: {m.dzbor, e.motta} @open.ac.uk	Universität Karlsruhe – TH (UKARL)
Institut für Angewandte Informatik und Formale Beschreibungsverfahren – AIFB
Englerstrasse 28
D-76128 Karlsruhe, Germany
Contact person: Rudi Studer
E-mail address: studer@aifb.uni-karlsruhe.de	
Universidad Politécnica di Madrid (UPM)
Campus de Montegancedo 
28660 Boadilla del Monte 
Spain
Contact person: Asunción Gómez Pérez
E-mail address: asun@fi.upm.es	Software AG (SAG)
Uhlandstrasse 12
64297  Darmstadt
Germany
Contact person: Walter Waterfeld
E-mail address: walter.waterfeld@softwareag.com	
Intelligent Software Components S.A. (ISOCO)
Calle de Pedro de Valdivia 10 
28006  Madrid 
Spain
Contact person: Richard Benjamins
E-mail address: rbenjamins@isoco.com	Institut ‘Jožef Stefan’ (JSI)
Jamova 39
SI-1000 Ljubljana 
Slovenia
Contact person: Marko Grobelnik
E-mail address: marko.grobelnik@ijs.si	
Institut National de Recherche en Informatique et en Automatique (INRIA)
ZIRST – 655 avenue de l'Europe
Montbonnot Saint Martin
38334 Saint-Ismier
France
Contact person: Jérôme Euzenat
E-mail address: jerome.euzenat@inrialpes.fr	University of Sheffield (USFD)
Dept. of Computer Science
Regent Court 
211 Portobello street
S14DP Sheffield 
United Kingdom
Contact person: Hamish Cunningham
E-mail address: hamish@dcs.shef.ac.uk	
Universität Koblenz-Landau (UKO-LD)
Universitätsstrasse 1
56070  Koblenz
Germany
Contact person: Steffen Staab
E-mail address: staab@uni-koblenz.de	Consiglio Nazionale delle Ricerche (CNR)
Institute of cognitive sciences and technologies
Via S. Martino della Battaglia, 
44 - 00185 Roma-Lazio,  Italy
Contact person: Aldo Gangemi
E-mail address: aldo.gangemi@istc.cnr.it	
Ontoprise GmbH. (ONTO)
Amalienbadstr. 36
(Raumfabrik 29)
76227 Karlsruhe 
Germany
Contact person: Jürgen Angele
E-mail address: angele@ontoprise.de	Asociación Española de Comercio Electrónico (AECE)
C/Alcalde Barnils, Avenida Diagonal 437
08036  Barcelona
Spain
Contact person: Gloria Tort
E-mail address: gtort@fecemd.org	
United Nations Food & Agriculture Organization (FAO)
Viale delle Terme di Caracalla 1
00100  Rome
Italy
Contact person: Johannes Keizer
E-mail address: johannes.keizer@fao.org	Atos Origin S.A. (ATOS)
Calle de Albarracín, 25
28037  Madrid
Spain
Contact person: Jose Lopez
E-mail address: jose.lopez@atosorigin.com	

Work package participants
The following partners have taken an active part in the work leading to the elaboration of this document, even if they might not have directly contributed writing parts of this document:

United Nations Food & Agriculture Organization (FAO)
Universidad Politécnica di Madrid (UPM)
Open University (OU)
…

Changes
Version	Date	Author	Changes	
0.1	05-08-2006	Carola Catenacci	creation	

Executive Summary

Table of Contents

1. Introduction	6
1.1 The place of collaboration in the NeOn big picture	6
1.2 Informal description of our approach	6
2. Notion of Networked Ontology/ies	6
2.1 Formal description	6
2.2 Ontological description	6
3. Notion of Design Rationale/s	7
3.1 As in the literature	7
3.2 As in our definition	7
4. Notion of Collaboration	7
4.1 As in literary review	8
4.2 As in our view	8
5. Global vision	9
6. Bibliography	10

1. Introduction
1.1 The place of collaboration in the NeOn big picture
How WP2 fits in the project
1.2 Informal description of our approach
Anticipation of the notions we’ll use (with examples)
2. Notion of Networked Ontology/ies
2.1 Formal description
(As per WP1)
2.2 Ontological description
Our aim in the NeOn project is to provide an ontological model of networked ontology/ies. This model will be necessarily different from, though compliant with, the logical model developed in WP1. 
First sketch of an ontological definition of networked ontology/ies: 
I. Let us consider a single ontology which, as a whole, is linked to (at least one) other ontology; in this case, each of the linked ontologies is a  'networked ontology' 
II. Let us consider a COLLECTION of  networked ontologies (the focus here is on the set); in this second case, we have an 'ontology network'. The network emerges only if there is a description that unifies the collection (hence, on the basis of the definition of collection provided in [BOT06], there must be at least two networked ontologies). The network has (at least one) design rationale of its own, that is expressed by (?) the way in which the links among ontologies are established 
III. Let us consider one or more ontologies with DISTRIBUTED uri/s, that is the nodes or elements of which are distributed in the web; in this case, we have one or more 'distributed networked ontology/ies'. The network, here, emerges a posteriori  wrt ontology/ies’ creation. This third case is orthogonal with the previous ones. 
In the case of ontology networks, the relation unifying the collection is given by the network’s design rationale. In what follows, we will discuss types and dimensions of unifying relationships. These latter are the same we have identified for the design rationales of the single component ontologies, i.e. the three dimensions of content, task and sustainability (see Secs. 1.2 and 3.2).  
An example of unifying relationship is given by versioning. From the content point of view, the design rationale of versioning may consists in tracking an ontology (or ontology network) evolution through time, or verifying knowledge growth and dissemination, etc. 
All the functionalities included in the Niys model, however, need to be revised in the light of the above-given definitions. [Are they methods/tools for the solution of the problem implied by the task? To be discussed.] 
In any case, a network DOES NOT coicide with the ‘Niys scenario'. The latter is much wider, and includes also projects (with related goals), agents, and collaboration among agents. A network, however, can be a pre- or post-condition of said scenario. 

Moreover, on the basis of our definition of collaboration (see Secs 1.2 and 4.2), a network (of whatever kind) always implies collaboration, and viceversa.
As far as ontologies are concerned, since a lifecycle consists of a series of operations guided by an underlying ‘rationality’ (vs single, unrelated operations), functionalities must be located in the same scenario with ‘collaborative’ networked ontologies (or ontology networks). They support the network lifecycle via requirements, and play a role on the way design rationales impact on networked ontologies [this is an aspect on which we will research further]: 
lifecycle -> planning -> design rationale/s -> functionalities -> lyfecycle -> etc. 
It should be noted that rationality, per se,  always implies a comparison, hence – again, on the basis of our definition - at least a ‘weak’ form of collaboration [see Sec. 4.2 below]. Our aim, then, could be rephrased as consisting in establishing a mutual dependency between collaboration and design rationales (or rationality in general). Our working hypothesis is that each design rationale defines a type of collaboration, and that there are as many design rationales as collaboration types. 
3. Notion of Design Rationale/s
3.1 As in the literature
Design rationales are the solutions adopted to reach a given goal (cf. Simon Buckingham-Shum, Design rationale; and others?). 
3.2 As in our definition
(Stress importance of user requirements, take examples from those)
Wrt ontologies, design rationales are the reasons why a knowledge object is made in a given way. 
We will model design rationales as a kind of descriptions (cf. [MAS04] and [GAN05]), i.e. explicit definitions of the project (and project elements) underlying both the single (networked or non-networked) ontologies and the ontology networks.
Since descriptions are explicitations of viewpoints, design rationales are a kind of viewpoint. Again, wrt ontologies, another kind of viewpoint is given by evaluation diagnoses, with or without fully explicit parameters (as e.g. in the case of a ‘bad-good’ rating). 
We will analyse design rationales along three dimensions, which coincide with ontologies’ construction principles, that is:
•	content (which can be expressed by one or more design pattern/s)
•	task, or service (expressed by use-case requirements)
•	sustainability (“what use at what cost”, cf. Buckingham-Shum)
Hence, design rationale can be seen as a function of  (design pattern, use case, sustainability) 
These three dimensions are involved in various way in the different functionalities. For instance, selection can be seen as a process the output of which is a new knowledge object, since I have e.g. adapted a given ontology (taken as a whole) to a new task, modifying its original design rationale and ‘adding my viewpoint’.
Hypothesis: design rationales’ dimensions could be applied to the selection process, e.g. the latter could be performed via a matching of design patterns or tasks.
4. Notion of Collaboration
Collaborative aspects not necessarily limited to ontologies.
4.1 As in literary review
4.2 As in our view
A collaborative activity is concerned with the way a community carries out a complex task in a cooperative fashion.
When talking of knowledge communities like those targeted by ontology engineering and NeOn, we could assume a very comprehensive notion of collaboration, including e.g. the following different situations: 
1) social relationships whose participants are physically co-located, work in a same group and project and can communicate flawlessly in shared languages and with common tools. For example, two prospective NeOn users both working at UN-FAO, Rome, speaking a fluent English, both expert in their respective fields, competent on using the same communication tools, and collaborating on the design of an ontology for fishery regulations 
2) social relationships whose participants are geographically distributed, work in a same community for related projects and can communicate with some fluency in a language and with some common tools. For example, two prospective NeOn users working at UN-FAO, Rome, and CABI, Oxford, speaking a decent English, both expert in their respective fields, somehow competent on using at least one communication tool, and collaborating on the design of two ontologies for fishery regulations and for fishery techniques respectively 
3) social relationships whose participants are not co-located in either space or time, work in heterogeneous communities with compatible goals, but can't easily access their respective languages and communication tools. For example, two users that work respectively for UN-FAO, and as an independent farmer in the Maluti Mountains, Lesotho: they have never met, they have respectively unaccessible languages, while being both experts in their respective fields, but they are not necessarily competent on using the same communication tools, and certainly they are not going to make any joint work on the design of an ontology for farming techniques; but, in principle, the knowledge owned by the independent farmer can be relevant for that task 
4) social relationships whose participants belong to heterogeneous communities, live in disjoint space-time, work on unrelated projects, and have no accessibility to their languages and communication tools. For example, a UN-FAO user, and Aristotle. It's not completely absurd to think about a distinction by Aristotle to be reused by the UN-FAO user, e.g. that between matter and attribute (substance and accident in Aristotle's terms) 
While the third and fourth situations cannot be considered typical collaborative scenarios, nonetheless, collaboration can be generalized to occur even between agents living at disjoint space-time, and having apparently incompatible goals and communication means. 
Hence, at a very generic level, we model a collaborative activity (in a knowledge domain) as a subclass of interaction activity involving: 
- at least two rational agents (or the same agent at different times, e.g. as in revising one’s own work); 
- at least one public and explicitly formulated knowledge object (an information object);
- at least two different viewpoints (explicit descriptions, i.e. interpretations or 'contexts’); in the case of networked ontologies, viewpoints are typically design rationales (not so for e-pinions or ratings). 
To complete this definition, the project in which collaboration activities occur must be considered; this includes at least one task and one goal involving the development of a knowledge object (e.g. a ‘piece’ in natural language, or in a formal language, as in the case of an ontology or an ontology network). 
The project is a kind of plan, i.e. an explicit description of a course of action, and must be conceived or adopted by at least one of the rational agents involved in the collaboration activity (although, as said above,, in the typical case a project is ‘shared’ by all the involved agents; cf. [GAN05] and [BOT06]). 
This definition includes also the the ‘collaboration with Aristotle’ case. Since, however, this use of ‘collaboration’ is scarcely compliant with the intended meaning of the word (being, rather, a form of ‘interaction’), we will term this situation, as well as the thirdly-exemplified one above, a case of ‘weak collaboration’. On the contrary, we will talk of ‘strong collaboration’ for the first two above-listed situations, which imply a sharing of both goals and tools, as well as the performance (by each of the collaborating agent) of (at least one) task defined in a same project. [The performed tasks should be, typically, different, but maybe we should allow for ‘redundancy’….]
In order to better understand these ‘weak’ cases, as well as the role played by design rationales in ‘collaborative ontology’, we must consider in more detail the notion of information object (cf. [GAN05]).
An information object (hereafter, an IO) is a social (hence, non-physical) object which:
•	is realized by at least one information-realization (i.e., a support),  
•	is ordered by one or more code/s (i.e. combinatorial structure/s or grammar/s), 
•	expresses one or more descriptions (i.e., conceptualization/s or meaning/s), 
•	is about one or more entity/ies (i.e., the IO’s reference), which are in the setting/s of one or more situation/s, which in turn satisfy the description/s expressed by the IO, and
•	is interpreted by at least one rational agent.
Hence, every IO is intrinsically provided with a viewpoint (the original description its author/s meant the IO to express), regardless whether this viewpoint is known to – or deemed interesting by - the agent/s that is/are currently considering the IO. NB: The rational agent which is the original author/designer of a given IO can also be a knowledge collective.
The relation interprets implies that an expressed description is internally represented  by an agent; i.e., when an agent interprets an IO, it internally represents the description expressed by the IO; of course, two agents can represent different descriptions, then resulting in different interpretations. As a consequence, a same IO can be seen as many different IOs, according to the different viewpoints from which it is interpreted.
In the case of networked ontologies, these viewpoints can be design rationales (cf. Secs. 2.2 and 3.2).
 [NB: the locution ‘collaborative ontology’ has been around since the early 1990’s (cf. Yiling Lu, 1994, and A. Farquhar, Richard Fikes, and James Rice, "The Ontolingua Server: a Tool for Collaborative Ontology Construction," presented at 10th Knowledge Acquisition Workshop, Banff, Canada, 1996). Should we link networked ontologies and collaboration at the very beginning, or as a result of the literary review, or maybe at the end, in the global vision?]

5. Global vision
(integration of all of above and interaction with functionalities)

6. Bibliography
[1]	Behrendt W., Gangemi A., Maass W. and Westenthaler R. Towards an Ontology-Based Distributed Architecture for Paid Content. In Proceedings of The Semantic Web: Research and Applications: Second European Semantic Web Conference, ESWC, May 29 - June 1, 2005, volume 3532, pages 257–271, Heraklion, Crete, Greece, 2005. Springer-Verlag GmbH.
[2]	Bottazzi E., Catenacci C., Gangemi A. and Lehmann J. From collective intentionality to intentional collectives: an ontological perspective. Cognitive System Research - Special Issue on Cognition and Collective Intentionality, 2006.
[3]	Gangemi A. and Mika P. Understanding the semantic web through descriptions and situations. In CoopIS/DOA/ODBASE, pages 689–706, 2003.
[4]	Gangemi A., Borgo S., Catenacci C. and Lehmann J. Task Taxonomies for Knowledge Content. Deliverable D07 of the Metokis Project, http://www.loa-cnr.it/Papers/D07 v21a.pdf, 2005.
[5]	Gangemi A., Catenacci C., Battaglia M. The Inflammation Ontology Design Pattern: an Exercise in Building a Core Biomedical Ontology with Descriptions and Situations. In Ontologies in Medicine, pages 64–80. IOS Press, Amsterdam, 2004.
[6]	Gangemi A., Catenacci C., Ciaramita M., Lehmann J. Modelling Ontology Evaluation and Validation. In Proceedings of the Third European Semantic Web Conference. Springer, 2006.
[7]	Gangemi A., Fisseha F., Keizer J., Pettman I., Taconet M. A Core Ontology of Fishery and its use in the Fishery Ontology Service Project. In First International Workshop on Core Ontologies, EKAW Conference, CEURWS, volume 118, 2004.
[8]	Gruber, T.R. A translation approach to portable ontology specifications. Knowledge Acquisition, 5:199–220, 1993.
[9]	Lu, Y. Roadmap for Tool Support for Collaborative Ontology Engineering. Master thesis, XiAn Transportation University, Department of Computer Science, (1994), ©2003, http://www.cs.uvic.ca/~chisel/thesis/YilingLu.pdf 
[10]	Masolo C., Gangemi A., Guarino N., Oltramari A. and Schneider L. WonderWeb EU Project Deliverable D18: The WonderWeb Library of Foundational Ontologies. http://wonderweb.semanticweb.org/deliverables/documents/D18.pdf, 2004.
[11]	Masolo C., Vieu L., Bottazzi E., Catenacci C., Ferrario R., Gangemi A. and Guarino N. Social roles and their descriptions. In D. Dubois, C. A. Welty, and M.-A. Williams, editors, KR, pages 267–277. AAAI Press, 2004.
[12]	Oberle D., Lamparter S., Grimm S., Vrandecic D., Staab S., Gangemi A. Towards Ontologies for Formalizing Modularization and Communication in Large Software Systems. Journal of Applied Ontology, 2006, to appear.
[13]	Oberle D., Mika P., Gangemi A., Sabou M. Foundations for service ontologies: Aligning OWL-S to DOLCE. In Proceedings of the World Wide Web Conference (WWW2004), volume Semantic Web Track, 2004.