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knowledge representation of coffee agribusiness system

Knowledge Representation of the Specialty Coffee Agribusiness System

By Café, Cafés Especiais, Coffee, Domain Ontology, Knowledge Engineering, Knowledge Representation, Ontology, Sem categoria, Specialty CoffeeNo Comments

In a short time we will have the publication here. This article will be presented at IFKAD in July. 2018.
After that we will publish the main results.

Purpose–  This article addresses fundamental knowledge of the Back-End of the Coffee Agribusiness System that can influence the final quality of the product, integrating the areas of agronomy, medicine and business. The representation will be made through an ontology that will contribute to clarifying for the scientific community the possible impacts of the use of coffee with compromised qualities in clinical research as well as informing and educating consumers with regard to coffee choice. ## Knowledge Representation of the Specialty Coffee Agribusiness System ##

Design/methodology/approach– Six steps were followed 1) Targeted search; 2) Literature review; 3) Systematic search in the target interest of the three areas of literature: agronomy, medicine and business; 4) Field research through six semi-structured interviews with the purpose of validating the research problem; 5) Organisation of knowledge with the aim of forming a common knowledge base as a starting point for ontology and 6) Ontology development.

Originality/value –Coffee is one of the most researched substances in the world. There are more than 25,000 scientific articles published just from the clinical point of view (Illy, 2016), but little is available integrating results from clinical research, agronomy and management. Improvements in coffee quality could be developed with the knowledge integration of these areas.

Practical implications– The Specialty Coffee Agribusiness System Knowledge Representation will improve subsidies funding for the scientific community because of the importance of using good quality coffee in clinical research. It will also guide professionals in the coffee agribusiness system to produce better quality coffee and offer a common vocabulary for the principal properties and influences during the Back-End process for researchers in the three areas.

Keywords –Knowledge Representation, Specialty Coffee, Agribusiness System, Ontology, Human Health.

Eduardo Trauer– PhD Student in Engineering and Knowledge Management, with a research focus on the representation of knowledge of the agribusiness system of specialty coffees at the Federal University of Santa Catarina (UFSC). He is a member of the Humane Smart Cities Laboratory (LabCHIS) at UFSC. In 1998, he completed his Master’s degree in Applied Intelligence at Production Engineering at UFSC where he worked with Interactive Marketing and Virtual Reality and was one of the founders of the second Virtual Reality Laboratory in Brazil. He completed a specialization course in International Economics and Foreign Trade at the State University of Santa Catarina (Esag/Udesc). He was coordinator of the administration courses at Estácio de Sá, Santa Catarina and coordinator and head of the Department of Business Administration at ESAG/Udesc where he has been Professor of Marketing for undergraduates since 1998. He was one of the founders of Junior Enterprise of Esag/Udesc. Professional photographer focusing on fine art photography. His areas of interest are knowledge engineering, agribusiness system, specialty coffees, humane smart cities, marketing, communication and fine art photography. He was a member of the judging panel of the Micro and Small Business Award of Brazil – Sebrae in Santa Catarina from 2009 to 2016.

Aline de Brittos Valdati– PhD Student and Master’s in Engineering and Knowledge Management at the Federal University of Santa Catarina (UFSC), researcher at the Nucleus of Studies in Intelligence, Management and Technologies for Innovation (IGTI) and in the Nucleus of Engineering of Integration and Knowledge Governance (ENGIN). Holds a degree in Information and Communication Technologies (UFSC). Worked with project management in the area of systems development and as a teacher in the area of Information Science at the Catarinense Federal Institute – Sombrio Advanced Campus. Current research focuses on the processes of innovation, especially on the initial processes, which concentrate the creative capital of an organization. He has published works on the themes: Front End of Innovation, Selection of Ideas, Management of Ideas, Management Systems of Innovation (IMS) and identification of opportunities.

José Leomar Todesco– Professor at the Post-Graduate Program on Knowledge Management at the Federal University of Santa Catarina (EGC/UFSC), Florianopolis, Brazil. Graduate in Mathematics from UFSC (1987), graduate in Physical Education from UFSC (1985), Master’s at Production Engineering from UFSC (1991) and PhD at Production Engineering from UFSC (1995). Has experience in Computer Science, acting on the following subjects: data warehouse, information systems, ontology engineering, business intelligence, semantic web and interactivity on Digital TV.

Eduardo Moreira da Costa– Professor at the Post-Graduate Program on Knowledge Management at the Federal University of Santa Catarina (EGC/UFSC), Florianópolis, Brazil, and founder of the Pi-Academy, a private company that promotes innovation for large corporations. His research focuses on the development of more humane, smart and sustainable cities. He is the Coordinator of Humane Smart Cities Laboratory (LabCHIS) at UFSC. Served as an Innovation Director at FINEP from 2007 to 2010. From 1993 to 1997, he served as a Director at CNPq. Prior to that, he served as a Researcher at CPqD. Member of the Order of Scientific Merit from the Brazilian Government. He served as an Independent Director of Algar Telecom S/A. He is also a Member of the Board and a Member of the Advisory Board at Algar Holdings, Senior Sistemas S.A., and at HOPLON Infotainment S.A. Was the Member of the Advisory Board of Associação Brasileira de Private Equity & Venture Capital. Holds a PhD in Electronics from the Southampton University, and a M.Sc. in Computer Science and a B.S. graduate in Electrical Engineering from UFMG. He is a Consultant at BID for the innovation, electronic businesses and electronic government and Venture Partner at FIR Capital Partners – Gestão de Investimentos S/A.

Introduction

Coffee is one of the most consumed beverages in the world, surpassing 3 billion cups daily (Illy, 2016). It is ingested mainly for the stimulating effects of caffeine, as well as for its role in social bonding and its aromatic properties but is rarely drunk for its beneficial properties to human health (Shaposhnikov et al., 2018). The world coffee production forecast for 2018 is 159,9 million bags of 60kg[1](USDA, December 2017) equivalent to the sum of US$ 57,9 billion and this represents a commodity of great economic importance.

Before it is consumed, coffee goes through many stages of activity that make up the agribusiness system. In this type of system, all the producers and processors of commodities in semi-finished/finished products are joined to the suppliers of inputs and technology until they reach the final consumers (Wilk & Fensterseifer, 2003; Neves & Sonka 2017). Non-controllable factors that encompass both the environment and policy decisions are linked to consumer decision-making regarding product choice and brand choice (Wilk & Fensterseifer, 2003).

In this article, the activities of the Specialty Coffee Agribusiness System (SCAS) that treat it as a commodity will be called Back-End, for example: cultivation and harvesting, green coffee processing and roasting. Concomitantly, the knowledge about the stages that follow the commodity once transformed into the final product, we will call Front-End, specifically the roasted blendings, grindings, packaging, brewing and coffee preparation by the final consumers.

Although coffee is considered a simple product, seed-to-cup transformations involve knowledge-intensive processes (Trauer, Valdati, Costa, Trzeciak and Varvakis, 2017) and numerous complex tasks (Hatzold, 2012) given that coffee can have several quality standards, from coffees with a very dark-roast – known as Italian or French roast (Melo, 204; Lokker, 2016) – to coffees composed of defective, green, burnt, mouldy and0 old harvests to gourmet and specialty coffees.

Coffee is not born bad, it gets bad (Kasai, 2016). The final quality of this product may influence the health of its consumers, as well as scientific research that may be biased by the use of food derived from transformations that have deteriorated part of its substances.

[1]Calculation based on the average price per kilogram of arabica and robust green coffee for the month of March 2018 according to data from The World Bank Commodities Data (The-Pink-Sheet) http://pubdocs.worldbank.org/en/346911520263101497/CMO-Pink-Sheet-March-2018.pdf

Thus, in the SCAS, the market, agronomy and medicine have their own interests about characteristics present in the productive process that are sometimes not perceived, shared and used among these areas because they are implicit in the agents and in the activities of each area. Therefore, it is necessary, not only to explain the knowledge, but also to obtain a consensus on this knowledge present in the agents/activities involved in the SCAS.

This article aims to address information and fundamental knowledge of the Back-End of the SCAS that can influence the final quality of the product, integrating the three areas previously mentioned. The representation will be made through an ontology that will contribute to clarifying for the scientific community the possible impacts of the use of coffee with compromised qualities in clinical research as well as informing and educating consumers with regard to coffee choice.

This article is divided into five sections including this first one that contextualises the problem. The second is a review of the literature on the SCAS and knowledge representation through ontologies. In the third section the research design is presented. In the fourth section we present the ontology as the main result and, lastly, the final considerations in the fifth section.