Ontological Modelling of Information Systems from Bunge's Contributions, SI Herrera, D Pallioto, GN Tkachuk

Tags: ontological model, BWW, social systems, Information Systems, ontological, Mario Bunge, SS, structures, Weber, BSS, concrete systems, ontological models, concrete system, Santiago del Estero, Argentina, abstract models, logical Model, alternative model, Universidad Nacional de Santiago del Estero, models, Social System, social model, economic system, biological system, political system, social innovation, presentation model, information system, abstract model
Content: Ontological Modelling of information systems from Bunge's Contributions Susana I. HERRERAa, Diana PALLIOTOa, Gregorio TKACHUKa, Pedro A. LUNA b aDepartamento de Informбtica, Universidad Nacional de Santiago del Estero (4200) Santiago del Estero, Argentina. E-mail: sherrera, dpalliot, gregorio @unse.edu.ar bConsultor, Colegio Mayor Universitario Ex Prof. Titular Departamento de Informбtica, Universidad Nacional de Santiago del Estero (4200) Santiago del Estero, Argentina. E-mail: [email protected] Abstract. The aim of this paper is to determine aspects to be considered in Bunge's ontological models in order to obtain an Integrated Onto logical Model of Information Systems (IOMIS). This alternative model would make up for one of the most important weaknesses of the Info rmation Systems ontological model put forward by Wand and Weber (BWW model): it does not take into account the particular cultural features of Information Systems. To this purpose, Bunge's on to logical model of social systems (BSS model) is approached. Starting from this model, some aspects are proposed to be included in the BWW model in order to obtain an integrated alternative model that will include characteristics of the social systems. 1 Introduction From the beginning until a few years ago, research in ontologies related to Informa tics was limited to Artificial Intelligence and Knowledge Engineer fields, focus ing on topics about knowledge representation and management, and natural language pro cessing. Over the last few years, however, ontologies have stressed their influence in the Information Systems (IS) discipline, transferring the research focus to topics related with systems analysis and design, enterprise systems and Web Services [15, 16, 17]. Today such researches are oriented to two well-differentiated lines: ontologies as technologies of IS (covering the ontology -driven IS that use domain, task and application ontologies) and the ontological models of IS (ontologies as abstract models supporting the core of the Information System discipline and contributing to the improvement of reality-modelling techniques). Within the framework of Research Project: Systematic Study of Informatics, Development of Methods -Techniques of Applied Informatics (psycho -bio -socio -techno -
cultural), a team of experts in Information Systems are devoted to researching ontologies as abstract models. For many years, the theories about real world structure were the specific concern of philosophers who worked on the ontology field. There are ontologies (categorizations) proposed by several philosophers such as R. Carnap [10], M. Bunge [5, 6, 7], F. Chisholm [12]. Ontologies not only state what exists, according to a certain ph ilosophical view, but also how such things should be classified and described; and this constitutes an "intellectual lense", a certain "way of looking", through which the real world is observed. Fig. 1. Relationships between BS Model (Bunge), BWW Model, BSS Model (Bunge) and IOMIS Model. Today, researches in IS and Informatics (from now on called Information Sy stems/Informatics1) have captured the philosopher's initiative and developed their own ontological theories [21]. The essence of an IS is that it provides a representation of real world phenomena [32, 33]. Thus, the main concern of the members of the discipline should be how to build good representation of such phenomena. And, in order to build good representations, it is necessary to have good theories leading to the way in which real world phenomena are structured. IS ontological models provide such theoretical foundations that constitute the support of the discipline core. Within the various ontological models proposed, this paper deals with the models based on Bunge's ontology [6, 7], since it belongs to t he scientific realism which re- 1 The disciplines Informatics and Information Systems are considered equivalents to the effects of this paper, in accordance with the curricular model of the IS discipline in force proposed in 1997 by ACM, AIS and AITP [1, 2].
quires a profound and detailed theoretical understanding of reality (peculiar of contemporary science). The main objective of this paper is to deal, from a critical point of view, with Bunge's Ontology-based models and to emp hasize the weaknesses of the BWW model of IS. The development of a hypothetical IOMIS model (in progress) is proposed as an answer to solve the lack of social orientation of the BWW model. Aspects to be considered in order to obtain an Integrated Ontologic al Model of Information Systems (IOMIS) based on Bunge's ontological model (BS model), Wand and Weber's ontological model of Information Systems (BWW model) and Bunge's ontological model of Social Systems (BSS model) are presented. It is also sought to obtain an ontological model that lays the foundations for Information Sys tems as technically implemented social systems (Fig. 1). In this way there would be a contrib ution to the definition of the disciplinary basis core of Information Systems. Regarding the structure of this paper, the second section deals with BS model, a real world ontological model put forward by Bunge in his Treatise of Philosophy [6, 7]. In section 3 the BWW model [29], Bunge-Wand -Weber ontological model with a strong influence in the IS community, mainly in the evaluation of object-oriented modelling methods [13, 21, 25, 26]. Section 4 deals with a comparison of the features that the BWW inherits from the BS. In addition, the criticisms to the BWW model are presented emphasizing the main weaknesses inherited from Mario Bunge's philosophicalscientific conception when he proposed his ontological model: it does not take into account the cultural features that are part of an IS. The BSS model [9], ontological model proposed by Bunge for the social systems, is briefly presented in the fifth section. Aspects to be considered from the BSS model in order to obtain an Integrated alternative model of Information Systems, IOMIS, are presented in section 6. This model would have the BWW model as the basis and it would also have features which are present in the BSS model but not in the BWW. Section 7 deals with the conclusions regarding the proposed model and a reflection of future expectations related to its construction and validation. 2 Bunge's Ontological Model Mario Bunge [5, 6, 7] assumes the universe is a world of interconnected systems. His philosophical theories in his Treatise on Basic Philosophy [6, 7] are formulated in certain exact mathematical languages (definitions, axioms, corollaries), so that they are consistent with contemporary science. He presents the basic notions of substance, property, thing, possibility, change, space and time [6], as well as wholeness (or systemicity), variety, and change [7]. The primary concepts concerning Bunge's ontological model (BS model) are the following. ­ A n object can be concrete or conceptual. Things belong to the material world. Concepts are fictions. ­ Other basic notions: property, change, space, time.
­ System. A set of things is a system if, for any bi-partitioning of the set, cou - plings exist among things in the two subsets. A system is itself a thing. Every system can be analyzed into its composition (collection of components), environment (things that are not in the system but interact with things in the system) and stru cture (collections of relations). ­ Systemicity. The universe is a world of interconnected systems. Every thing is a system or component of a system. ­ Dynamics, development, history. The fundamental property of a concrete system is the transformation of its state. An other characteristic of systemicity is history. D e velopment is the qualitative change of a system patterned by laws. ­ Level. The universe is enormously varied; its components can be grouped into a number of levels: physical, chemical, biological, social and technical. ­ Evolution. There are mechanisms of qualitative novelty; new properties could emerge during a process; giving way to evolutions by which new systems emerge. 3 BWW Model Wand and Weber [32, 33] have investigated the branch of philosophy known as O ntology as a foundation for understanding the process in developing an information system. They have taken, and extended, Bunge's ontology [6, 7] and applied it to the modelling of information systems. They adapted and used Bunge's ontology to study information systems design and development tools. They proposed a formal abstract model called Bunge-Wand -Weber (BWW model) [29]. The BWW models consist of the representation model, the state-tracking model, and the good decomposition model [27, 29]. The representation model defines a set of constructs that, at this time, are thought by the researchers to be necessary and sufficient to describe the structure and behavior of the real world. The essential constructs of the representation model (inherited from BS model) are: thing, property, class, kind, state, coupling, system, compos ition, environment. Properties can be: in general, in particular, intrinsic, mutual binding, emergent, etc. In the state -tracking model, Wand and Weber identified necessary and sufficient conditions that must be satisfied by an IS. The good decomposition model focuses in how a decomposition transfers to the users the meaning of the real world system to be represented. This work focus on the re presentation model since it has the main structures and relationships.
4 Bunge's Ontological Model and BWW Model Analysis The primary properties the BWW model inherited from the BS are briefly presented in this section as well as the criticisms of the scientific community towards the BWW model, emphasizing the fact that cultural aspects are not considered in IS. 4.1 Similarities between Bunge's BS Model and the BWW Model The BWW model is an adaptation of Bunge's ontology ­ related to the real world ­ to Information Systems. As an adaptation, it inherited important aspects that may cause positive as well as negative effects. The BWW model has inherited the primary representational structures from Bunge's model: Thing or entity, property and attribute, status, event, history, coupling, Type/kind, compound thing, system, composition, environment, structure, subsystem, inputs and outputs, properties (inheritance, emergency, intrinsic, mutual, generalizations, part of). This characteristic makes the BWW model have a rigorous scientific formality. Although it is a positive characteristic from the disciplinary point of view it constitutes a handicap, as it will be seen in the following section, since it causes an inco mprehensibility gap within the members of the discipline. Being an adaptation of Bunge's model, the BWW model inherits its realistic (it assumes the existence of an external reality independent of the human experience) and also objective (it assumes that the world is made up of entities, properties and relations that may have a one -to-one correspondence with a set of technical sy mbols) ontology. This will, in the next section, lead to the criticisms related to the lack of consideration of non-formal cultural aspects. 4.2 Criticisms to the BWW model A twofold criticism is raised for the BWW model. On the one hand, lack of understanding of the models and, consequently, the difficulty in evaluating the gra mmars with them [27, 28, 23, 29, 31]. On the other hand, lack of socio-cultural a s pects in the model that makes information systems be considered merely technological sys tems and not socio-technical systems inserted in a human social organization [18, 19, 25, 24]. Both lines will next be discussed. Two issues emerged within the IS research community at the time the BWW ontological models were being developed and used. First, the incomprehensibility of the structures within the models has been criticized by several sectors of the scie ntific community. Wand and Weber originally defined the structures using a strictly theoretical language. In spite of the fact that in previous works the researchers sought to simplify and clarify the structures using plain English, the criticism of the incomprehensibility gap remained. Second, Wand and Weber had difficulties in applying the models to the grammars using those modelling grammars, comparison gap. This diffi-
culty is due to the fact that, although Wand and Weber's structures have clearly defined theoretical definitions, the grammars to which they apply have vague definitions. Consequently, the analysis developed using the BWW models is largely based on the knowledge and experience of the researches doing the analysis, applicability gap. Such a situation leads to limitations in the results of the works in the area. In order to solve the problems of incomprehensibility, comparison and applicability, various researchers have developed semiformal descriptions of Wand and Weber's main ontological structures in metamodels based primarily on the Entity-Relation models [14, 27, 28]. Structuring the relationships between ontological structures of the model in an accurate way would facilitate the clarification of any inconsistency and anomalies that might exist in the BWW models. Likewise, this will simplify the communication of this approach and would facilitate the integration of ontologies as subject matter of IS curricula. The second critical line is based on the fact that the BWW ontological model considers IS as a grapho of software components or useful modules to analyze the graphic properties such as coupling and good decomposition. It does not take into account the core and main components of IS based on non-formal definitions [24]. This criticism points out that IS are social systems that are technically implemented. They are social systems by nature, since their very existence depends on Social Institutions such as language, legitimization and energy control, and other ways of social influences and other norms of behavior. Data modelling deals with concepts like information, knowledge, meaning and language. Many of the IS design problems can be framed according to the beliefs and conceptions about the nature of social reality. This IS conception grew stronger with Hirschheim [18]. The strength of his position is his effort to point out the relevance of social aspects of IS development, which are generally ignored by IS engineers, who consider their activity to be only technical. IS must not be reduced to technological aspects. Moreover, any techno logy that can change the way people live and work is necessarily a social and philosophical subject. Alternative IS models were proposed according to these ideas. Some researchers state that for non -formal information systems or with strong social characteristics it is convenient to adopt an alternative ontological model like Chisholm's [21, 22], based on a common sense realism. Other authors proposed alternative formal IS models [24] that try to save for the absence of socialism in the BWW model and the weaknesses of other models like that of Alter's [3,4].These models do not have the same epistemological strength as those based on philosophical ontologies referred to the world and its modelling. Other researchers considered that the theory of Agency should be included in the ontological models [19]. They state that IS are never designed to represent what is in the world for its own sake: they are designed to be used by human actors and to achieve certain goals. Thus, an IS is one component of a larger socio -technical sys tem that allows one or more human actors to achieve certain goals. There are other criticisms within the same line, Opdahl [25], for example, argues that the BWW model does not take into account different perspectives regarding Things and Properties, as well as the Classes they belong to. He proposes four metaconstruc-
tions that are essential to understand the multiple perspectives of some discourse universe: Things, Properties, Conceptions and Perspectives 5 Bunge's Social System Model In 1993 Mario Bunge proposed an ontological (formal) model of the social systems (SS) [9]. Here it is called Bunge's Social System Model (or BSS model). He assumes that ignoring that society is a real system of concrete systems, rather than either a solid block or an unstructured aggregate of free individuals, precludes the understanding of its peculiar properties and processes [8, 9]. In the BSS model, Bunge proposes definitions of the general concept of a system. Then he lays down some definitions and principles concerning SS. After that he proposes some methodological maxims concerning the systemic study of social facts. He starts from general systems concepts to formulates axioms on an SS and a society. He states and discusses general principles regarding SS. He also establishes method ological principles to deal with them [9]. The BSS model is formulated using basic hypotheses (axioms, postulates, principles) and their immediate consequences (corollaries). It has remarks and examples that make it easy to understand. The main ontological structures of Bunge's social model related to the SS and soc iety concepts are the following. ­ Social system. It's a concrete system composed by animals that (a) share an environment and (b) act upon other members of the system, either directly or in directly, in ways that are cooperative in at least one respect. A human SS is a social system composed of human beings and their artifacts. It can be natural (or sponta neous) if and only if it is self -organized -families, bands of hominids- or artificial (or formal or an organization) if and only if it is other-organized ­schools, churches, business firms. ­ Human society. It's a system composed by four subsystems: (i) the biological system, the members of which are held together by the relations of descent, sex, reproduction, child rea ring, or friendship; (ii) the economic system, held together by relations or production and exchange; (iii) the political system, the specific function of which is to manage the social activities in the society; and (iv) the c ultural system, the members of which are engaged in discovering or inventing, teaching or learning, designing or planning, and the like. ­ Social process (or activity). It's a process involving at least two members of a SS (getting married or divorced, making friends or enemies). ­ Social movement. It's a social process occurring in at least one artificial SS (or organization) and dragging a number of people not belonging to the latter (social re form movements, religious movements). SS principles derived from Bunge's proposals for concrete systems of any type ­ physical or chemical, biological or social- will be stated next. They constitute the core of a systemic and naturalistic world view or ontology.
­ Every human being is a member of at least one SS. SS are held together by links of various kinds: biological, psychological, economic, political or cultural. ­ A person's beliefs, preferences, expectations, choices and actions are socially conditioned as well as inner-directed. ­ Every SS has a specific function. Every SS is engaged at all times in some pro c - ess or other, continuous or discontinuous, of quantitative or qualitative change, causal, stochastic, or mixed. ­ All of the members of a SS cooperate in some respects while competing in oth - ers. Co mpetition stimulates initiative and innovation, whereas cooperation favors efficiency and security. ­ A SS emerges if and only if its existence contributes to meeting some of the needs or wants of some of its members. A SS breaks down if and only if it ceases to benefit most of its members, or if the intensity of conflicts in the system is greater than that of cooperation. ­ Every social innovation benefits some members of a SS while harming others. Every social innovation is bound to be resisted by those who believe that the may be harmed by it. To minimize the conflicts generated by social innovation it is desirable to enhance the participation of all the stakeholders as well as the cooperation of experts in the design, planning and implementation of the innovations in que s tion. Some of the methodological maxims concerning the systemic study of social facts are the following. ­ Every SS can by analyzed into its composition (collection of persons and art i- facts), environment (nature and society at large) and structure (collection of p h y s ical, biological, economic, political and cultural relations among the members of the systems and among they and members of other systems, social and nonsocial). ­ social science studies SS, such as families and factories. ­ An adequate understanding of any SS involves the (empirical and theoretical) investigation of its composition, environment and structure. An adequate understanding of any society involves investigation of its biological, economic, political, and cultural subsystems. ­ The efficient management of SS involves the consideration of their composi- tion (e.g., the personnel and management of a firm), environment (e.g. the market), and the structure (as represented by organization charts, schedules, budgets, etc.). 6 IOMIS Model It is necessary to achieve an IS ontological model which may serve as a theoretical foundation for every kind of IS, hard as well as soft, with either strong techn ological or socio-cultural characteristics. For this purpose it is proposed to take the BWW model (based in Bunge's BS model) as a basis and incorporate social chara cteristics from
Bunge's BSS model. In this way an integrated ontological model of IS, IOMIS, would be obtained. The hypothesis in this work is that in order to achieved the IOMIS model, the fo llowing aspects should be considered. ­ According to points 2, 3 and 5.3 the primary structures of the BS and BWW ontological models (composition, environment and structure) are applic able ­as Bunge states- to the social systems. ­ The IS are social systems. Their composition is made up of artifacts as well as people. The latter are socially conditioned and have various beliefs, pre ferences and expectations. Thus, two types of IS components should be differentiated in an integrated ontological model. ­ IS have an essential property for the SS that has to be added to the IOMIS model: intelligent organization, a property that emerges from learning (Knowledge Management) and from the evolution of human components. ­ In modelling the environment, three levels should recognized: the closest where the social movements occur; the context, where the social processes happen; the universe or the level of human society. All of them should be included in the IOMIS. ­ Regarding the IOMIS model the following relations should be considered: b io - logical, economic, political and cultural as well as cooperation and competition. ­ The IS generally have technological components (artifacts) that bring about strong social innovations. As such they are rejected by some human components because they foun d themselves damaged or threatened; IS arise in order to satisfy the needs of their human comp onents, needs which are coherent with the mission, function and activities of the organizations. ­ Information Systems/Informatics is a bio -p s y c h o-socio -cultural discipline that studies IS while SS have elements that are biologically, psychologically, economically, politically and culturally related. 7 Conclusions Some researches conjecture that there are alternative ontologies like Chis holm's (based in the common s ense realism) that are useful for modelling phenomena related to application domains where social o human issues prevail [21]. In this work, however, it is maintained that its convenient for the IS discipline to have theoretical foundations based on a scientific ontology. Even though Bunge's ontology and its adaptation to IS (BWW model) are criticized, they hold a scientific formalism (based on the objective and scientific realism). This scientific formalism should be kept as a support of the groundwork and applications of the discipline being valid for any type of IS. The very evolution of Bunge's philosophical thinking lends itself well to improve his ontological contribution to the IS foundations. His ontology has been consolidated from the 70s [5, 6, 7] to his last proposition in 1993 [9]. His model has made progress towards the mastery of the social systems, their organizations and applications.
Therefore, it is necessary to guide researches in order to elaborate integration attempts of the IS models with Bunge's latest characteristics, either by developing IOMIS or any other model. The IOMIS model is a proposal in process of becoming a formal hypothesis. If a hypothetical-deductive perspective [5] were adopted, the contrasting of IOMIS should be submitted to successive applications (by means of grammars evaluated with IOMIS or founded on it). This would allow academic criticism similar to the ones made to the BWW model. This will, in turn, contribute to the progress of scientific knowledge in the Information Systems/Informatics discipline. References 1. ACM, AIS, AITP. Model Curriculum and Guidelines for Undergraduate Degree Programs in Information Systems, 1997. 2. ACM, IEEE-CS. Computing Currнcula 2001 Task Force, 2001. 3. Alter, S. A general yet useful theory of information systems. Proceedings of the AMCIS Conference, Long Beach, CA, 2000. 4. Alter, S. Are the fundamental concepts of information systems mostly about work systems? CAIS, 5 (11), 2001. 5. Bunge, M. Teorнa y Realidad, Ed. Ariel, Barcelona, 1972. 6. B u n g e , M . Treatise on Basic Philosophy: Ontology I, Reidel, 1977. 7. Bunge, M. Treatise on Basic Philosophy: Ontology II, Reidel, 1979. 8. Bunge, M. A system concept of Society: Beyond individualism and holism, Theory and Decisiуn, 10, 1979. 9. Bunge, M. Social Systems, In ternational Systems Science Handbook, Ed. Ro drнguez- Banathy, ISBN 84-604-6236-6, Espaсa, 1993. 10. Carnap, R. The Logical Structure of the World: Pseudoproblems in Philosophy. University of California press, 1967. 11. Chisholm, R. Language, Truth, and Ontology. Ed. Mulligan, K.Kluwer Academic Publis hers, Dordrecht, 1992. 12. Chisholm, R. A Realistic Theory of Categories ­ An Essay on Ontology. Cambridge Un i- versity Press, 1996. 13. Colomb, R. Formal versus Material Ontologies for Information Systems Interoperation in the semantic web. School of ITEE, The University of Queensland, 2002. 14. Davies, I., Green, P., Milton, S., Rosemann, M. Using Meta Models for the Comparison of Ontologies. Eighth CAiSE/IFIP8.1, Austria, 2003. 15. Guarino, N. Semantic Matching: Formal Ontological Distinctions for Information Organiza- tion, Extraction, and Integration. Springer Verlag: 139 -170, 1997. 16. Guarino, N. Understunding, Building, and Using Ontologies: A Commentary to "Using Explicit Ontologies in KBS Develoment", by van Heijst, Schreiber, and Wielinga. Intern ational Journal of Human and Computer Studies (46): 293-310, 1997. 17. Guarino, N. Formal Ontology in Information Systems. Proceedings of FOIS'98, Trento, Italy, 6-8 June 1998. Amsterdam, IOS Press, 1998.
18. Hirschheim, R. Information systems develo pment and data modeling. Ed Kein H., Lyytinen K., Cambridge Universtity Press, New York, NY, 1995. 19. Johnston, R, Milton, S. The Foundational Role for Theories of Agency in Undestanding of Information Systems Design, Australian Journal of Information Systems 9, 40 -49, 2002. 20. Jurisica, I., Mylopoulos, J., Yu, E. Using Ontolgies for Knowledge Managing, An IS Perspective. Annual Conference of the American Society for Information Science, W a s h ington D.C., November 1-4, 1999. 21. Milton, S., Kazmierczak, E. Enriching the Ontological Foundations of Modelling in Information Systems. Proc of the IS Foundations Workshop, Macquarie Un iversity, 1999. 22. Milton, S., Kazmierczak, E., Keen, C. An Ontological Study of Data Modelling Languages using Chisholm's Ontology. Proc. 11th European-Japanese Conference Informa tion Mode lling and knowledge bases, 21 -32. Maribor, 2001. 23. Milton, S., Kazmierczak, E., Thomas, L. Ontological Foundations of Data Modeling in Information Systems. Proc. of Sixth Americas Conference on Information Systems, 2000. 24. Mora, M., Gelman, O., Cervantes, F., Mejia, M. & Weitzenfeld, A. A Systemic Approach for the Formalization of the Information Systems Concept: Why Information Systems are Systems? ISNB: 1-59140-040-6, Editorial Idea-Group, Mйxico, 2002. 25. Opdahl, A. A Comparison of Four Families of Multi-Perspective Problem Analysis Methods. Department of Information Science. University of Bergen, 1998. 26. Opdahl, A., Henderson-Sellers, B. Evaluating and Improving OO Modelling La nguages Using de BWW-Model. Proc. of the IS Foundations Workshop, Sydney, 1998. 27. Rosemann, M., Green, P. Developing a meta model for the Bunge-Wand-Weber ontological constructs. Information Systems, 27, 75-91, 2001. 28. Rosemann, M., Green, P. Integrating Multi-Perspective Views into Ontological Analysis. In Proc. Twenty-Third International Conference on Information Systems, 618-627, 2002. 29. Siau, K., Rossi, M.. Evaluating of Information Modeling Methods ­ Review. Prodeed ings of the 31th Hawaii International Conference on Systems Science, 1998. 30. Wand, Y. and R. Weber. An Ontological Model of an Information System . IEEE Trans ac tions on software engineering. November, pp. 1282 -92, 1990. 31. Wand, Y., Monarchi, D. Parsons, J., Woo, C. Theoretical foundations for conceptual modelling in information systems development. Decision Support Systems (15), 1995. 32. Weber, R. Ontological Foundations of Information Systems. Queensland, Australia, Coopers & Lybrand, 1997. 33. Weber, R. The Information Systems Discipline: The need for and nature of a Foundational Core. Proc. of the IS Foundations Workshop, Macquarie Unive rsity, 1999.

SI Herrera, D Pallioto, GN Tkachuk

File: ontological-modelling-of-information-systems-from-bunges-contributions.pdf
Title: Ontological Modelling Information Systems.doc
Author: SI Herrera, D Pallioto, GN Tkachuk
Author: susana
Published: Mon Apr 18 23:22:57 2005
Pages: 11
File size: 0.09 Mb

, pages, 0 Mb

Speed Simulation Environment, 14 pages, 0.59 Mb

The tooth trip, 2 pages, 0.01 Mb

ofDIVERSITY, 14 pages, 0.63 Mb

Contrastive rhetoric, 18 pages, 0.78 Mb
Copyright © 2018 doc.uments.com