Carneiro, Bruno G.

Guizzardi, Renata

English

This paper proposes a method for Decision Making Documentation that is founded on a formal ontology. To do this, we first proposes an extension to DMO, a decision making ontology founded on a foundational ontology named UFO, to include concepts on on Value Proposition and Economic Preference. [Guizzardi et al. 2020] Finally, we propose a template whose slots represent concepts in the Extended DMO and should be filled with sentences in natural language representing instances of these concepts. The goal of the template is to represent the rationale in the selection alternative phase of the Decision Making. Once the slots are filled, they can be converted to an OWL ontology using gUFO, a lightweight implementation of the Unified Foundational Ontology (UFO), suitable for Semantic Web OWL 2 DL applications, to enable automatic reasoning over the document.</p

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A Tool for Automatic Reasoning over Decision Documentationusing gUFOBruno G. Carneiro1, Renata Guizzardi1,21Ontology and Conceptual Modeling Research Group (NEMO)Federal University of Espı́rito Santo (UFES)Av. Fernando Ferrari, 514, 29075-910, Vitória, Brazil2Industrial Engineering and Business Information SystemsUniversity of TwenteP.O. Box 217 7500 AE Enschede, The Netherlandsguimaraescarneiro@gmail.com, r.guizzardi@utwente.nlAbstract. This paper proposes a method for Decision Making Documentationthat is founded on a formal ontology. To do this, we first proposes an extension toDMO, a decision making ontology founded on a foundational ontology namedUFO, to include concepts on on Value Proposition and Economic Preference.[Guizzardi et al. 2020] Finally, we propose a template whose slots representconcepts in the Extended DMO and should be filled with sentences in naturallanguage representing instances of these concepts. The goal of the templateis to represent the rationale in the selection alternative phase of the DecisionMaking. Once the slots are filled, they can be converted to an OWL ontology us-ing gUFO, a lightweight implementation of the Unified Foundational Ontology(UFO), suitable for Semantic Web OWL 2 DL applications, to enable automaticreasoning over the document.1. IntroductionDecision Theory is an interdisciplinary topic that has been investigated by biologists,social scientists, philosophers, computer scientists, and others. Speaking and making de-cisions are related elements of the human nature: ”Darwinian considerations suggestthat language may have developed because it leads to improved decision making and sur-vival, justifying the study of language’s contribution to decision making.” [Losee 2001]Nowadays, decision-making is an essential part of the everyday life of any organiza-tion. In this context, decisions are generally documented in unstructured natural lan-guage. [Guizzardi et al. 2018] In Computer Science, the study of Decision Making isgenerally focused in to built Decision Support Systems (DSS). By our informal literaturerevision, even though there are many works using ontologies and natural language to sup-port decision-making, most do not use Formal Ontologies and use the Natural Languageonly to data processing, not to documenting decisions.According to the purpose for which the natural language is used, proposals canbe classified into two groups. One group proposes the use of natural language be-fore the decision is taken in order to assist this process [Demner-Fushman et al. 2009],[Gkatzia et al. 2016] and [Martı́nez et al. 2015]. The second group uses natural lan-guage after the decision is taken in order to explain this process [Goodall 2014]Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).and [Papamichail and French 2003]. To handle natural language, different techniquesare used like Natural Language Processing [Losee 2001] and Computing with Words[Martı́nez et al. 2015].In our master dissertation, we propose that decisions are documented in a toolthat provides slots to be filled by texts in natural language. Our work started byevolving a Decision Making Ontology [Guizzardi et al. 2018], by reusing some notionsof existing ontologies on Value Proposition [Sales et al. 2017] and Economic Prefer-ence [Porello and Guizzardi 2018, Porello et al. 2020]. This first result is presented at[Guizzardi et al. 2020]. The slots provided by our tool will reflect the concepts of this ex-tended Decision Making Ontology. Once the slots are filled, they will be instantiated as anOWL ontology using gUFO [Almeida et al. 2019] to enable reasoning over the decisiondocumentation.With this proposal, we aim at supporting documentation of a decision making innatural language by formally representing the rationale behind the decision process.2. Research GoalsOur main goal is to provide computational support for decision documentation, allowingreasoning over the decision making process.To achieve our main goal, we have established these secondary objectives:• To propose a core ontology on the decision making process.• To support reasoning over the decision making process by implementing the afore-mentioned ontology.• To implement a computational tool to support ontology documentation, based onthe implemented ontology.3. Research in ProgressOur starting point is that the decision maker wants to move from a INITIAL SITUATIONto a new, and most valuable, DESIRED SITUATION. To do that, he finds some ALTERNA-TIVES that are possible actions to be performed that could bring him from the INITIALSITUATION to the DESIRED SITUATION. We have identified in the literature some phasesfor this process: “problem definition”, “alternative discovery”, “alternative selection” and“decision evaluation [Frisk et al. 2014]. In this work, we focus on the documentation ofthe “alternative selection” phase, because a precise documentation with verbalization inthis phase can improve the general process, particularly impacting the “decision evalua-tion” phase.Important challenges in this scenario are the complexity and uncertainty of the de-cision situation or the existence of multiple conflicting objectives [Martı́nez et al. 2015].This work is founded on some fundamental assumptions about the decision maker. Manyworks assume that the decision maker is an Economic Man, i.e. a man that is (1) com-pletely informed, (2) infinitely sensitive, (3) rational, and (4) able to order situations bysome criterion that should be maximized. However, this is a perspective that exceedsactual human cognitive capabilities [Fjellman 1976].The decision making process is a cognitive process, i.e. it is based on mentalproperties of the DECISION MAKER. To make a decision, the agent simulates in his mindthe possible consequences of his actions, and chooses one alternative based on these con-sequences. This simulation runs over the decision maker mental model of reality. Thismental model defines the premises of the decision and the simulation defines a sequenceof logic operations. This process consists of evaluating and comparing alternatives. In[Guizzardi et al. 2020], we included concepts on Value Proposition [Sales et al. 2017]and Economic Preference [Porello and Guizzardi 2018, Porello et al. 2020] to enable rea-soning in the “alternative selection” phase. This ontology is the first result of this work.By documenting the decision maker’s reasoning over possible alternatives, we areinterested in understanding how people actually make decisions. It is trivial to show thatthe decision maker has no total knowledge of his context and of the different end statesthat he can reach as a result of his actions. Therefore, the aforementioned EconomicMan’s properties (1) and (2) are discarded. Still, we keep properties (3) and (4). Inthis context, it is important to emphasize that to be rational does not means not havingemotion, but to be able to reason over premises founded on emotions or values. Premisescan be objective or subjective and are considered beliefs.3.1. Performing an evaluation of the Decision Making OntologyWe aim at evaluating the core ontology on decision making presented in[Guizzardi et al. 2020], by comparing it with other works. So far, we have identifiedthree related works:The GRADE taxonomy [Papatheocharous et al. 2018] was created to establish thevocabulary for supporting decisions regarding architectural aspects of software-intensivesystems. The main categories of this taxonomy are Goals, Roles, Assets, Decision andEnvironment.The Strategic Decision Making (SDM) Ontology [Gómez et al. 2017] has beencreated with special focus in managing quality in Agile Software Development processes,although the authors claim it is general enough to be used in other contexts.The Decision Making Ontology (DMO) [Kornyshova and Deneckere 2012] hasbeen developed aiming at: clarifying the concepts of the domain of Decision Making,also supporting the specification of Decision Making requirements; and serving as basisof a specification of the components a DM method. To be more specific, it is part of anapproach called MAke Decisions in Information Systems Engineering (MADISE).We aim at extending our literature review to identify other relevant related initia-tives.3.2. Supporting reasoning over the decision making processTo enable the reasoning over the decision documentation, we aim at representing theDecision Making Ontology using gUFO [Almeida et al. 2019], a lightweight implemen-tation of the Unified Foundational Ontology (UFO), suitable for Semantic Web OWL 2DL applications.gUFO is an OWL 2 DL ontology that is intended for reuse in the definitionof UFO-based ontologies. It consists in instantiating and/or specializing the variousclasses, object properties and data properties defined in the ontology, inheriting from itthe domain-independent distinctions of UFO.To support reasoning, we aim at represent the Decision Making Ontology special-izing the classes defined in gUFO.To validate our approach, we intend to test many examples of decision documen-tations, using an OWL reasoner, checking if the model is able to identify the intendeddecision result.3.3. Implementing the decision documentation supporting toolOnce all the above mentioned items are realized, we intend to implement a tool where theuser can fill slots coming directly from the ontological concepts defined in the DecisionMaking Ontology. The tool will convert the documented decision into an OWL ontologybased on gUFO and then calculate the final decision.Documented decisions may be used by the decision-maker herself to justify andinform her future decisions. Moreover, when considering an organizational environment,documenting and further reusing the documented decisions may be an adopted practiceto make sure that the organizational members act consistently, to guarantee the qualityof the Decision Making process and to train newcomers joining the work. By using thistool, the user will be able to validate whether the data provided will actually imply theexpected decision. On the other hand, future readers of this documentation will findit easier to understand the reasoning on which the decision was based since it will beformally documented.4. Work PlanThe work plan to finalize our master dissertation is comprised of the following sevenactivities:1. Evaluating the decision making ontology2. Implementing the ontology based on gUFO3. Generating examples to test the gUFO ontology4. Implementing the decision documentation supporting tool5. Evaluating the implemented tool6. Writing the master dissertation7. Defending the master dissertationTable 1 details the work plan, scheduling its activities in the coming months, start-ing from November 2020 and going until July 2021.Activity Months11/20 12/20 1/21 2/21 3/21 4/21 5/21 6/21 7/211 x x2 x3 x4 x x x5 x x6 x x x x x x7 xTable 1. Work plan for the completion of the master thesisReferencesAlmeida, J. P. A., Guizzardi, G., Sales, T. P., and Falbo, R. A. (2019). gufo: A lightweightimplementation of the unified foundational ontology (ufo).Demner-Fushman, D., Chapman, W. W., and McDonald, C. J. (2009). What can naturallanguage processing do for clinical decision support? Journal of biomedical informat-ics, 42(5):760–772.Fjellman, S. M. (1976). Natural and unnatural decision-making: a critique of decisiontheory. Ethos, 4(1):73–94.Frisk, J. E., Lindgren, R., and Mathiassen, L. (2014). Design matters for decision mak-ers: Discovering it investment alternatives. European Journal of Information Systems,23(4):442–461.Gkatzia, D., Lemon, O., and Rieser, V. (2016). Natural language generation enhanceshuman decision-making with uncertain information. arXiv preprint arXiv:1606.03254.Goodall, N. J. (2014). Ethical decision making during automated vehicle crashes. Trans-portation Research Record, 2424(1):58–65.Guizzardi, R., Carneiro, B., Porello, D., and Guizzardi, G. (2020). A core ontology ondecision making. In Proceedings of the 13th Seminar on Ontology Research in Brazil.Guizzardi, R., Perini, A., and Susi, A. (2018). Aligning goal and decision modeling. InInternational Conference on Advanced Information Systems Engineering, pages 124–132. Springer.Gómez, C., Ayala, C., Franch, X., López, L., Behutiye, W., and Martı́nez-Fernández, S.(2017). Towards an ontology for strategic decision making: The case of quality inrapid software development projects. In Advances in Conceptual Modeling: ER 2017,pages 111–121. Springer.Kornyshova, E. and Deneckere, R. (2012). Using an ontology for modeling decision-making knowledge. In 16th International Conference on Knowledge-Based and Intel-ligent Information Engineering Systems, pages 1553–1562. IOS Press.Losee, R. M. (2001). Natural language processing in support of decision-making: phrasesand part-of-speech tagging. Information processing & management, 37(6):769–787.Martı́nez, L., Rodriguez, R. M., and Herrera, F. (2015). Linguistic decision making andcomputing with words. In The 2-tuple Linguistic Model, pages 1–21. Springer.Papamichail, K. N. and French, S. (2003). Explaining and justifying the advice of adecision support system: a natural language generation approach. Expert Systems withApplications, 24(1):35–48.Papatheocharous, E., Wnuk, K., Petersen, K., Sentilles, S., A., C., Gorschek, T., andShahb, S. (2018). The grade taxonomy for supporting decision-making of asset selec-tion in software-intensive system development. Information and Software Technology,100:1–17.Porello, D. and Guizzardi, G. (2018). Towards an ontological modeling of preferencerelations. In 17th International Conference of the Italian Association for ArtificialIntelligence, pages 152–165. Springer.Porello, D., Guizzardi, G., Sales, T., and Amaral, G. (2020). A core ontology for eco-nomic exchanges. In 39th International Conference on Conceptual Modeling (to ap-pear).Sales, T., Guarino, N., Guizzardi, G., and Mylopoulos, J. 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A tool for automatic reasoning over decision documentation using gUFO

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A tool for automatic reasoning over decision documentation using gUFO

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