Ontological Models for Information Retrieval of Product-Service: Trends and Open Issues∗

Ontological models for information retrieval of product-service: Trends and open issues∗

Liudmila Reyes-Alvarez Jaime Fernández Luis J. Rodríguez-Muñiz Dept. of Computer Science METALUX Company Dept. of Statistics and O.R. University of Oviedo C/Cerdeño, 33 University of Oviedo Oviedo, Asturias, Spain Oviedo, Asturias, Spain Oviedo, Asturias, Spain [email protected] [email protected] [email protected] Irene Díaz Dept. of Computer Science University of Oviedo Oviedo, Asturias, Spain [email protected]

ABSTRACT 1. INTRODUCTION More and more companies need a model for product-service A significant number of international companies are im- information retrieval. All businesses agree on the need of a mersed in a process of transformation from “product suppli- common vocabulary among customers, commercial partners ers” to “service providers of products”. This allow to save and suppliers. Building ontologies as models of knowledge costs on and increase their competitiveness. Undoubtedly, representation about product-service information is increas- the development of the Internet and software systems in ingly seen as a key to enable interoperability between soft- computer science brought a change in cultural thinking in ware agents and people on the Web or through to network industry. Employers want to move from simply selling a connections. In addition, in recent years it has strengthened product to sell “value propositions”[11] through the efficient the alliance between industry and scientific research com- management of stakeholders. These systems reduce costs munities. The development of ontology-based smart cata- on companies by representing information about their prod- logs captures their attention. This work surveys ontological ucts. These are used for the successful implantation of the models for information retrieval on product-service in the product-service in the society. Hence, during several years industry. Research trends previously addressed and open there has been a significant growth in the development of issues are discussed. Besides, some of the solutions on func- product-service systems (PSS) to create sustainable tools tionality and behavior of ontologies-based product-service for efficient collaboration between resources [2]. are presented as an alternative to achieve an optimal level Many researchers go through the design of such systems during information retrieval using smart catalogs in business over the years [2, 4, 11, 56]. In [11] it is performed an analysis scenarios. of PSS literature classifying PSS research into five broad areas: delivery, processes, value creation networks, knowledge management, and business models. Research on integration CCS Concepts of product-service between 2006 and 2010 is revised in [4]. •Information systems → Database management sys- This work emphasizes that research in this area is dominated tem engines; by theoretical contributions and therefore points out that an additional empirical research is required. Besides, it anal- yses how the concept of PSS has been characterized, con- Keywords cluding that the main elements characterizing these systems Business sceneries; Functionality and behavior; Ontological are: sustainability, environmental aspects, the centrality of models; Ontology; Product-Service the consumer and dematerialization. Most cited definitions of PSS are those introduced in [2] ∗(Produces the permission block, and copyright informa- and [41]. However, there is not a consensus with respect to tion). For use with SIG-ALTERNATE.CLS. Supported by what definition is the most suitable for PSS as it is shown in ACM. [56]. In this work recent developments regarding approaches to the design of sustainable PSS are introduced. In addition Permission to make digital or hard copies of all or part of this work for personal or the design of system components is classified in this work classroom use is granted without fee provided that copies are not made or distributed as: PSS ontology, requirements definition, design support for profit or commercial advantage and that copies bear this notice and the full cita- process for generating PSS concepts, and the evaluation of tion on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or re- PSS concepts. publish, to post on servers or to redistribute to lists, requires prior specific permission Although the work presented in [56] covers most areas and/or a fee. Request permissions from [email protected]. related to the design of PSS, the study about PSS ontolo- CERI ’16, June 14-16, 2016, Granada, Spain gies falls short because the design of a PSS should focus c 2016 ACM. ISBN 978-1-4503-4141-7/16/06. . . $15.00 on mitigating the problems for searching, selection, recom- DOI: http://dx.doi.org/10.1145/2934732.2934741 mendation, information retrieval and classification of prod- set of best practices for publishing and connecting structured ucts according to the services requested by customers. In data on the Web[5]. this sense, the use of metadata and ontologies represents a solution [3]. Hence, in the last few years, many software 2.1 Technologies solutions[29, 31, 32, 53, 57] have been developed based on Among the current technologies in the field of Semantic ontologies as a retrieval and classification model of informa- Web, the following are highlighted [3]: Extensible Markup tion about catalogs of product-service. languaje (XML), Resource Description Framework (RDF), Companies usually organize and classify offered product- Ontology Web Language (OWL), SPARQL Protocol and service by description models on the Internet. Some of these RDF Query Language (SPARQL). These technologies have models are based on ontologies [29, 31, 32, 53, 57]. Although created data stores on the Web, built vocabularies, and writ- encouraging results have been achieved, much remains to ten rules by handling data. be seen, because each provided product-service has specific XML[3] technology allows to structure a document but features. Few enterprises are dedicated only to the con- this structure has no meaning. The meaning is expressed struction and knowledge representation of the product and with RDF across 3-tuples that can be written in XML. It their distribution as suppliers. Examples about of this are allows to create its own markup language. presented in [12]. Recent results about the evolution, chal- RDF[3] data model is used for publishing and linked of lenges, and future of knowledge representation in product structured data on the Web. This data model is based on a design systems are described in this work. Others works are directed graph formed by triplets of type subject-predicate- engaged in the sale of a product or part of them, an exam- object, where the graph nodes are subject and object, and 1 ple is “schema.org” . However, others provide installation edges are the predicates. Subject, predicate and object are service of products in a given environment, in addition to identified by URIs (Universal Resource Identifier), which are selling the product. These are known as intermediaries in character strings used to identify a resource. URI enables the midst of customer and suppliers. Accordingly, to count interaction with representations of the resource over a net- with an ontological model that satisfies all needs for infor- work, typically the World Wide Web, using specific proto- mation retrieval on product-service in the industry is not cols. Schemes specifying a concrete syntax and associated easy. protocols define each URI. However, as the same concept In this work we survey the related work on ontological can be associated to different URIs, ontologies play an im- models used as a base for information retrieval on product- portant role. service on business sceneries. A comparison of the proposals OWL[3] is designed for applications that need to process on these models is performed based on the criteria used to the content of information instead of just presenting infor- specify and represent domain knowledge. Through a com- mation to humans. OWL is a computational logic-based parative analysis of trends followed by researches on onto- language such that knowledge expressed in OWL can be ex- logical models of product-service, we provide readers with a ploited by computer programs. OWL documents, known as comprehensive understanding of ontology as representation ontologies, can be published in the World Wide Web and model for information retrieval in the industry. In addition, may refer to or be referred from other OWL ontologies. Be- many open research issues are illustrated. This paper is sides, OWL is more machine interpretable than XML, RDF organized as follows. Section 2 introduces preliminary con- and RDF Schema (RDFS) as it provides additional vocab- cepts such as the semantic web, ontologies, knowledge base, ulary with a formal semantic. OWL has three increasingly- among others. Section 3 provides a review of current ap- expressive sublanguages: OWL Lite, OWL DL, and OWL proaches and trends about ontologies of products and ser- Full. vices, differentiating the contributions in the categories of SPARQL[3] is used to express queries across diverse data (1) ontologies as business models for PSS, (2) models to sources. SPARQL contains capabilities for querying required specify and communicate the domain knowledge based on in- and optional graph patterns along with their conjunctions ternational standards, (3) ontologies to structure and define and disjunctions. Also SPARQL supports extensible value the meaning of terms of a determined domain in a generic testing and constraining queries by source RDF graph. The way which is know as taxonomy and, (4) ontological repre- output of SPARQL queries can be result sets or RDF graphs. sentations as base of tools for the product-service description according to its form or composition. Section 4 discusses the 2.2 Ontologies approach of functionality and behavior of product-service All these technologies have as a cornerstone the efficient across ontologies, as an alternative to achieve an optimal creation and implementation of ontologies in the Semantic level of information retrieval about product-service in busi- Web [3]. From a computing point of view, ontology is a ness scenarios. Finally, Section 5 shows conclusions and software engineering tool that allows communication and open issues. exchange of information between different systems, institu- tions and agents in a given domain through the graphical 2. PRELIMINARIES representation of knowledge. The most commonly cited on- The Semantic Web is considered one of the most active tology definition in the literature and accepted by the sci- research areas in the global scientific community. It is not entific community is given by Gruber in [26] highlighting an extension of the current web but a more meaningful one the synthesis capacity and generalization power of ontolo- [3], where users and machines are also able to process the gies. In this framework an ontology is defined as an explicit content available on the Web. Linked data are the basis of specification of a conceptualization.This definition was then the underlying models. It refers to Linked Data refers to a refined by Borst years later in [10]. They defined an ontology as a formal specification of a shared conceptualization. 1schema.org/Product All ontology definitions share two cardinal ideas: Axiom These are elements that allow the modeling of truths that are fulfilled always on the relationships of elements that make up ontology. There are three types of axioms: • Relational: It establishes circumstances related to the class hierarchy of an ontology. • Non-relational: It establishes relationships between attributes of an specific application domain concept represented in an ontology. • Generals: All other axioms. The axioms satis- fying the Meronymy relationships are: 1)unre- flecting (no entity is part of herself), 2) asym- metry (If part-of (x, y) then part-of (y, x)) and, 3) transitive (if part-of (x, y) and part-of (y, z), then part-of (x, z)). In the literature concerning the area of Artificial Intel- ligence (AI), ontology and knowledge base terms tend to Figure 1: The relationships between general compo- come together so that they are frequently considered syn- nents of an ontology. onyms although they are not. Gruber in [26] explicits the difference between ontology and knowledge base by saying 1. The ontology specification is provided through a for- that A shared ontology only needs a vocabulary for describ- mal language that allows information processing not ing the domain, whereas a knowledge base may include the only by humans but also by software systems in an knowledge needed to solve a problem or answer to arbitrary automated way. queries about a domain. [26]. In [43] it is specified that a knowledge base is composed by an ontology together with 2. Knowledge included in an ontology must be the re- a set of classes instances. An ontology in computer science sult of an agreement between specialists and/or users will provide a set of concepts (classes, objects, relationships, within a workgroup restricted to a particular applica- among others) and terms to describe the scope of imple- tion domain, an element of common interest or a given mentation, while a knowledge base will use this terminology field. or vocabulary to represent what is true about a domain or real-world environment. Studies presented in [43] and [52] demonstrate that the In the field of AI, ontologies have moved from abstract components of an ontology vary according to the applica- concepts to an important engineering tool that gives mean- tion area and scope to cover developers needs. The general ing to many applications commonly used in the industry components of an ontology are described below ([21]). Fig- software. In product-service ontologies, an ontological model ure 1 represents the relationships between them. defines a common vocabulary for commercials who need to share information with respect to descriptions of functions Classes (or Concepts): These are the formal and explicit and behaviors of electromechanical artifacts. Some of the description of concepts or definitions of the implemen- reasons for developing an ontology model in this particular tation scope of the ontology. A class/concept describes case in industry are described below ( [43]). a set of objects (physical, tasks, functions, etc.). Each object in a class is an instance of this class. • To share common understanding about the structure of information among people and/or soft- Slots (or Roles, Properties or relationships): Used for ware agents. This is one of the more common goals describing class characteristics and attributes. They in developing ontologies, as well as clarifies in [25, 43]. also represent the interactions between classes through For example, the industry of implementation of elec- relationships. Some of the relationships most com- tromechanical devices assumes several different Web monly used are: or software applications which contain information or provide e-commerce services for electromechanical de- • Hyponymy: word whose meaning is included in vices. If these software applications share and pub- the other. Relationship “is-a”. lish the same underlying terms ontology, then software • Meronymy: a word that names a part of a whole. agents can extract and aggregate information from dif- Relationship “part-of”. ferent sites. Thus, the commercials partners or agents • Synonym: relationship associated to two terms can use this aggregated information to answer cus- with the same (or very similar) meaning. tomer queries or as input data to other applications or suppliers. Facets (or Role restrictions) Specifications, ranges and restrictions with respect to slots (for example, type, • To enable reuse of knowledge domain. this is cardinality). the backbone of research concerning the ontologies creation. For example, reusing top-level ontologies [53], Individuals (or Instances) They are objects, individu- ontology of properties [27], ontologies of complex spatio- als, members of a class which cannot be divided with- temporal processes description [28], ontologies of graph- out losing its structure and functional characteristics. oriented model [40]. • To make domain assumptions explicit. This property is useful for new users who must learn the meaning of terms in the represented domain. These assumptions about the world in an ontological model facilitate its location and modification.

• To separate domain knowledge from operational knowledge. Thus, configuration of products from its components according to a required specification can be described. Besides, this configuration is independent of the products and components themselves. For example, in the industry of implementation of electromechanical devices, an ontology of electrical installations components and characteristics can be developed and an algorithm to configure made-to-order elec- Figure 2: The key of business models for PSS on- trical installations (for buildings, homes, shopping cen- tologies is the value concept. ters and others) can be applied [43].

• To analyze domain knowledge. It is possible once one proposes approaches of ontological representations ori- a declarative specification of the terms is available. ented at service-product description according to its form or This is very valuable because it allows us to reuse and composition. Then, we discuss these four trends. understand existing ontologies. 3.1 Ontologies as business models for PSS Ontologies facilitate communication between people, orga- A business model [14] establishes a company revenues and nizations and applications because they provide a common profits. Hence, a business model is essential in companies domain understanding. So that conceptual and terminolog- to establish a dashboard to attract and retain customers. ical misunderstanding are reduced. They are also used to This model is also used to define both the product offers encourage communication between applications. Ontologies and the implementation of marketing strategies related to have become essential for both the Semantic Web and en- transform company resources in Value. In this line, some terprise management systems, among other things. These interesting proposals of ontologies as a basis for PSS business allows applications to agree with the terms they use when models have been devised [1, 22, 23, 24, 44, 46, 48]. All communicating one to each other. Ontological representa- these proposals develop approaches based on ontologies for tions ease information retrieval. Many enterprises work with describing PSS business models, being the value concept the semantic tools for managing and searching data. Some ex- key of this type of ontological models (see Figure 2). amples are: Autonomy2, FAST3, Endeca4 and Newsoft5. An interesting work is [23], which presents an ontology Ontologies serve to ensure that systems and humans can for an e-business model. The main contribution of this work work together in an automated way without effort. is the use of an e-business model ontology as core concept of value. It also describes how many value is created, interpreted and exchanged within a multi-party stakeholder 3. TRENDS IN ONTOLOGICAL MODELS network. This model is improved in a wider methodology OF PRODUCT-SERVICE for e-business modeling, called e3-valueTM [22]. The basic concepts defined in e3-valueTM ontology are actor, value Ontological models of product-service allow to catalog the object, value port, value interface, value exchange, value of- information in business sceneries by the meaning of words fering, market segment and composite actor. The definition related to the sector in question. Applications can retrieve of economic value, and how objects are created, exchanged data automatic or semi-automatically according to the knowl- and consumed are the keys in this ontology for e-business edge stored in these models. The purpose of the ontologies models. is to count with descriptions needed to process and to make The ontological model proposed by [46] is an e-business inferences on knowledge about product-service, as well as model which outlines what Value a company offers to which make decisions and negotiate with other agents or people. customer segments. This model represents the architecture Thus, solutions able to accommodate industry needs are a of company and its network of partners for creating, mar- challenge for software engineering. keting and delivering Value in order to generate profitable With respect to this topic, four research trends have been and sustainable revenue streams. identified. The first one develops ontologies as business mod- More recently, in [48] it is presented a specific contribution els for PSS. The second one creates models to specify and to the development of business models with an ontological communicate the domain knowledge based on international structure specially for Industrial PSS. In additon, the results standards. The third one describe taxonomies that are con- of the proposal are validated by a case study from a supplier. sidered ontologies to structure and define the terms meaning These ontological proposals describe basic concepts such as of a determined domain in the industry. Finally, the fourth value, organization, risk distribution, revenue streams, and 2http://www.autonomy.com/ property rights. 3http://www.fasttechnology.com/ All the proposals represent a significant step forward in 4http://www.oracle.com/us/corporate/acquisitions/endeca the development of ontologies as business models for PSS. /index.html In addition many of them have as central axis the Value 5http://www.newsoftinc.com/ concept representation, which is the differentiating feature for all of them. practical examples with the eCl@ss standard in e-business scenarios), the resulting ontologies serialization is very large. 3.2 Ontologies based on International Standards In addition, support for ontology reasoning is inadequate. The increase of categorization standards for product-service The results obtained using this methodology may serve as a has encouraged to make valuable scientific studies about the starting point to ontological modeling as a basis for building use of these standards as basis for the creation of ontolog- intelligent catalogs in business applications. The key points ical models that allow the classification of these product- of this proposal are the following service in a certain domain. In addition, isolated solutions have been developed to enhance the information retrieval • The resulting ontology is fractionated to take advan- and search relating to an specific product-service. Some ex- tage of the resulting semantic richness, according to amples of categorization standards are UNSPSC6, ETIM7, the application area of interest. 8 9 10 11 the RosettaNet standard , eCl@ss , SIC , eOTD , among • A greater number of axioms are identified as a sim- others. ple way for automatically add them because they can Each of these standards defines a rich set of terminolo- not be easily derived from standard input. The au- gies in a certain sector of product-service in the industry. thor clarifies in [31] that the resources needed for the Hence, they are used as a common vocabulary between cus- respective axiomatic enrichment in relation to the im- tomers, business partners and suppliers. Such standards are provement of the automation process must be identi- useful in the conceptualization stage for modeling an intel- fied. ligent catalog of product-service based on ontologies, since some classify product-service types according to the society • A feedback mechanism to validate the results of the area in which are implemented. This facilitates customiza- resulting ontological model should be established and tion of ontological models depending on the sector that cov- the efficiency of this mechanism should be evaluated ers product-service. The first results in this direction are in a real time e-business. those presented by [6] and [38], although both are ontological Hepp et al. present in [34] a lot of quantitative data on models generated from the UNSPSC and eCl@ss standards. more popular categorization standards of product and ser- However they use different technologies. These proposals vices related to its content, coverage and maintenance. It is are limited in their product semantic representation by the quite relevant becasue it describes a comprehensive frame- standard and do not face to any changes that may be in the work of metrics to analyze the content quality of all struc- general rule, so their applicability is limited. tural elements of these categorization schemes. They also Several works are focused on increasing the scope of on- propose a new set of key metrics: “Semantic Weight” and tological models in industry and E-business ([29, 30, 31, 32, “Semantic Value” which quantify the specific property map- 33]). On one hand, these works show that for mastery of ping in different business scenarios. These quality metrics product-service, the ontologies derivation of industrial stan- are of great scientific value because they can be applied to dards are more likely than the manual ontology engineering, the problem measurement in other application domains with due to the large number of concepts and the high conceptual similar structural characteristics. dynamics affecting these business. On the other hand, these The aforementioned works introduce useful tools to se- proposals show that during the modeling process the taxo- lect an appropriate standard to design an intelligent catalog nomic relationship of concepts comprising the categorization for offered product-service. However, their weaknesses and standard of input must be interpreted and semantically rep- shortcomings were revealed for the assessment of categoriza- resented. This fact is quite important as it determines the tion standards [34]. So their use can break down the model usefulness of the resulting ontology. Thus, in these works design for smart catalogs of product-service. Also, the ax- it is proposed a comprehensive methodology[31] to create ioms required for the efficient description of the relationships product-service ontologies based on OWL using the exist- between different ontology components must be specified for ing standards. Although the proposed methodology is feasi- allowing the inference of new knowledge through a semantic ble and useful in practice (the author demonstrates through reasoner. 6United Nations Standard Products and Services All these taxonomies are very important for simply clas- Code(UNSPSC). https://www.unspsc.org/ sification of product-service, taking into account that a tax- 7Elektro Technisches Informations Modell, or Electro- onomy simply requires its components to be organized in Technical Information Model(ETIM). http://www.etim- order to carry out a successful classification. However, it international.com/ 8 is not enough for information retrieval. The fact that the A consortium of major Computer and Consumer taxonomy does not require its components to be connected Electronics, Electronic Components, Semiconduc- tor Manufacturing, Telecommunications and Logis- by a relations specific type makes it unfeasible for model- tics companies working to create and implement ing of tools of information recommendation and retrieval of industry-wide, open e-business process standards. product-service in business scenarios. So, the interpretation https://supplier.intel.com/static/B2Bi/RosettaNet.htm of the taxonomic relationship is an important modeled de- 9eCl@ss is THE cross-industry product data standard for cision. classification and clear description of products and services. http://www.eclass.eu/ 3.3 Taxonomies of Product-Service 10 Standard Industrial Classification(SIC). Taxonomy is based on the need of managers to orga- http://siccode.com/ 11ECCMA Open Technical Dictionary(eOTD) was de- nize their contracts, invoices, reports and other documents, veloped to allow ECCMA members to improve the which should have a coherent organization for its further lo- quality of their Master Data and their descriptions. calization. Hence, computer engineers decide to study pro- http://www.eccma.org/whyeotd.php cess automation in companies based on these taxonomies. The taxonomy defined in [39], is empirically derived in or- element of common interest or a specific field in cor- der to provide partitions with regard to some criteria. respondence with the product-service offered by com- The development of systems to ease the delivery of product- pany. service started in 90s. Wemmerlöv [58] emphasizes that one 12 of the main problems of service delivery systems is their Examples related to the first idea includes PCS2OWL taxonomic nature. The author believes that the system in- tool, GoodRelations [32] vocabulary for e-commerce, and 13 terface characteristics and service process attributes are the schema.org vocabulary can be used with many different main dimensions of taxonomy. In 1998 a specific methodol- encodings such as RDFa, Microdata and JSON-LD. ogy of Domain Analysis is presented by [17]. A Thesaurus PCS2OWL tool is proposed for the semi-automatic trans- is built using this methodology because the domain repre- formation of product classification systems in OWL ontolo- sentation can be constructed semi-automatically. gies[53] divided into two groups: product classification stan- The term integrated product-service is introduced in [45] as dards and proprietary product category systems. The au- the integration of any product-service offer with regard to its thors show that the tool generates logically and semantically type(s), objective(s) and function(s). Besides, a taxonomy correct vocabularies. In addition they explain the prac- is proposed as the basis for any general configuration model tical benefits obtained with this tool. Resulting product in a business scenario. This taxonomy allows classification ontologies are compatible with the GoodRelations[32] and of concepts in two perspectives: marketing and engineering. schema.org. This tool can be used to enrich the product Certainly, this is a step forward in the integration of product- descriptions with information about the granular product service. Nevertheless, the work remains in a qualitative view type from existing data sources available on the Semantic of the problem without the necessary practical validation in Web. However, the main drawback of this tool is that it an enterprise. does not access to most of the OWL ontologies. The rea- A new approach is proposed in [30, 33]. It enables au- son is that some classification systems are subject to license tomated processing of taxonomies in RDF-S and OWL on- copyright and then publication terms and conditions must tologies based on the representation of the original taxonomy be arranged. In addition, the reasoning possibility is very node on two concepts: (1) one for the generic concept and simple and limited on ontologies to which it has access, so (2) other for the taxonomic concept. The approach is ap- this approach does not solve the problem of automated infor- plied to the task of product-service creation based on eCl@ss mation retrieval and recommendation about product-service industrial ontology. This resulting ontology can be used to offered by the various sectors studied. create real business applications for e-procurement, expense With regard to the second point, it goes beyond research- analysis, or catalog data integration. Thus, it serves as a development projects because the handled ontological rep- demonstration of the commercial benefits when ontologies resentations provide relevant information by nature about for modeling intelligent catalogs or recommendation systems product-service in a given area of the industry. These solu- are used. Although this approach increases the number of tions are the result of the tool evaluation in real time. This classes in the resulting ontology, this problem is compen- occurs as a the result of an agreement between the special- sated because this representation increases the possibility of ists and/or end users of the developed tool (see [18, 42, 49, using a simple semantic reasoner. 57, 59]). A taxonomy simply requires its components to be orga- In [42] a framework for semi-automatic ontology popu- nized in order to carry out a successful classification. The lation of tabular product information from Web shops is fact that the taxonomy does not require its components to proposed. This approach uses the semantics of product at- be connected by a relations specific type makes it unfeasible tributes and their corresponding values to better product for modeling of recommendation tools of product-service in comparison. Besides, parametric search applications can be business scenarios. However, the interpretation of the taxo- built in subsequent years. Moreover, a predefined ontology nomic relationship is an important modeled decision. compatible with GoodRelations[32] ontology for e-commerce is used in order to formalize the crude product information 3.4 Tools for Product-Service Description based on tables of formularies contained in the product stores on on Ontologies the web. This approach works well with tabular data from An efficient information retrieval with regard to a par- product shops, but not for textual descriptions. In addi- ticular product through suppliers, commercial partners and tion, the authors suggest that the value Instantiation process customers is allowed in business scenarios if and only a well- could be enhanced by adding new value extraction rules and defined conceptual design is available. Ontologies and meta- by creating new property assertions between individuals. On data have been considered an optimal solution for a concep- other hand, they propose the use of regular expressions for tual design of tools as basis of product-service description automatic pattern generation as a reliable way to analyze between company partners. The corresponding ontological and filter the values of properties in the ontology, although models identified two cardinal ideas. the accuracy of the overall framework could be affected. In [18] two major theoretical contributions are described. 1. The selection of a formal language to represent an on- First, mereological specifications for creating an ontological tology which allows the processing of it not only by model of pharmaceutical products are described. Second, humans but also by software systems of an automated procedure for reusing of mereological ontologies (known as manner. top-level ontologies) is presented. They also propose to incorporate axioms involving extensionality as future research 2. The knowledge included in the ontological model as direction. result of an agreement between the specialists and/or end users of the developed tool. The represented knowl- 12http://www.ebusiness-unibw.org/ontologies/pcs2owl/ edge responds to a particular application domain, an 13http://schema.org/Product An ontology for classifying and representing the configuration information related to Cloud-based IaaS services Functionality and behavior of product-service have been including computation, storage, and network is proposed studied by many researchers so there are a variety of pro- by [59]. The results of the implementation of the ontol- posals, especially for the development of systems to offer ogy in the Cloud-Recommender system are also presented. products. Some examples of these are the models described Besides, it is shown both capture static configuration as dy- by [9, 15, 16, 19, 20, 47, 50, 51, 54, 55, 56]. namic QoS configuration on the IaaS layer. This work also The definition of functionality and behavior of product defines the core IaaS-level Cloud computing concepts and in areas of industrial engineering is very general and am- inter-relationship between different service types. The au- biguous. This paper is consistent with the definitions of thors plan to extend the developed ontology to capture the function and behavior of artifact given by [54] because these service dependencies through the layers in cloud. The latter are valid for whatever product engineering. Functionality would be very helpful for tools of product-service because it refers to the description of the situation that is solved by will allow identifying the dependencies between service con- a product-service in a business scenario. Behavior refers to figurations and the type of artifacts that can be deployed the way its functionality is implemented, i.e. the specific over it. way that product-service supports a given event. In sum- In [49] it is proposed a knowledge-based engineering frame- mary, behaviors are streams of states through its functional work which uses an approach based on an ontology for se- process. Some researchers agree that functionality (in some mantic knowledge management. This work adopts a model- case known as functions) and behaviors of artifacts or de- driven architecture from the software engineering discipline vices in industrial deployment are key depictions [8, 36]. for developing platform-independent knowledge-based engi- Researchs concerning ontological models of product func- neering systems in the aerospace industry. Additionally, ex- tionality and behavior are primarily aimed at engineering perts within the aerospace and software engineering sector artifacts or devices [9, 7, 8, 13, 15, 35, 36, 37, 50]. The validated the strengths/benefits and limitations of the KBE goal of this research is the description of the function and framework. The developed approach reduces man-hours re- behavior engineering concepts of technical devices captur- quired for developing knowledge-based engineering systems ing the informal meanings that have the terms in the en- within the aerospace industry and maintains the knowledge gineering practice. In addition, the meanings based on on- required for developing knowledge-based engineering sys- tologies given by domain experts are adopted. Nonetheless, tems. the model diversity demonstrates a consensus lack about A proposed ontological model with a consistent seman- the meanings of these terms by researchers. On one hand, tic representation for variations in time on product infor- some studies [13] are based on foundational ontologies as mation is PRONTO[57]. This ontology allows the repre- DOLCE14 which only includes the concepts and relation- sentation of product data at different levels of abstraction. ships that are independent of engineering application do- They define an Abstraction Hierarchy and a Structural Hi- mains. Thus, they incorporate new engineering concepts of erarchy to get it. Each of these hierarchies has a role on functionality and behavior, allowing an ontological evalua- the ontological model. The unstructural representation of tion of these notions. DOLCE is then extended for its use information products at different levels of abstraction, the in various fields of engineering. aggregation process representation and the information dis- On other hand, other models as [15, 20, 54] are based on aggregation between these levels are allowed by Abstraction physical descriptions of the artifacts that are able to realize Hierarchy. Structural Hierarchy is used for information con- the functions. These models propose an analysis of the de- cerning products and components involved in product manu- sign process based on functions reasoning. The main idea of facture. This model handles concepts that are of interest for the different designs of ontological models for functionality research on ontologies of product-service to industry such as and behavior of products is the description of the functions Family, VariantSet, Product, which are the levels that inte- of the product with respect to its structural design and the grate Abstraction Hierarchy. The model also handles prod- results of their behavior as a result of the design. These mod- uct structures relations such as componentOf, derivateOf. els represent a significant contribution for product markers. One of the main advantages of this proposal is that it allows However it is not sufficient for business scenarios that act the representation of different material lists of products that as intermediaries between the product provider and the cus- are manufactured by assembly of component parts, given its tomer. level of hierarchy. Information related to functionality and behavior of product- The decision of whether a model is better than another service is an essential step in designing an ontological model is not possible. This depends on the type of information as basis for a smart catalog. The aim is to help business needed when offering product-service through a smart cat- managers with information retrieval according to customer alog. One element to consider is that the difficulty of de- requests and to place orders with suppliers. Customer re- signing an ontological model of product-service of interest quest answering is extremely necessary to manage several for business is directly proportional to the accuracy with elements that must converge in the model: (1) a charac- which information is represented regarding the functionality terization of how the composition of a product performs and behaviors of the product-service want to offer it. Hence, their functions, (2) product reactions given environmental next section discusses the work related to the functionality circumstances, (3) the time required by product to perform and behavior of product-service and some relevant aspects an action or to react, (4) systems or components that can be about the ontological representation of them. integrated into product, (5) product costs and, (6) attributes derived from the composition of product. Above elements 4. FUNCTIONALITY AND BEHAVIOR OF PRODUCT-SERVICE 14http://www.loa.istc.cnr.it/old/DOLCE.html are considered when commercial partners offer a product as fluctuation on knowledge representation of ontologies-based a service. The sales process of a commercial partner can product-service, (4) incorporation the stream data (exam- be very complex because usually the same product varieties ples: heat, water, temperature, etc.) on product-service handles each of the aforementioned elements. models for example application of electromechanical arti- The results achieved are the input to a successful ontologi- facts. cal model for commercial partners, because this is a process which is part of the information that describes the struc- 6. ACKNOWLEDGMENTS ture of a product such as their shape, composition, size, The authors acknowledge the financial support from the components, accessories, auxiliary contact, among others. 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