Creation and extension of ontologies for describing communications in the context of organizations

Thesis submitted to Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, in partial fulfillment of the requirements for the degree of Master in Computer ScienceThe use of ontologies is nowadays a sufficiently mature and solid field of work to be considered an efficient alternative in knowledge representation. With the crescent growth of the Semantic Web, it is expectable that this alternative tends to emerge even more in the near future. In the context of a collaboration established between FCT-UNL and the R&D department of a national software company, a new solution entitled ECC – Enterprise Communications Center was developed. This application provides a solution to manage the communications that enter, leave or are made within an organization, and includes intelligent classification of communications and conceptual search techniques in a communications repository. As specificity may be the key to obtain acceptable results with these processes, the use of ontologies becomes crucial to represent the existing knowledge about the specific domain of an organization. This work allowed us to guarantee a core set of ontologies that have the power of expressing the general context of the communications made in an organization, and of a methodology based upon a series of concrete steps that provides an effective capability of extending the ontologies to any business domain. By applying these steps, the minimization of the conceptualization and setup effort in new organizations and business domains is guaranteed. The adequacy of the core set of ontologies chosen and of the methodology specified is demonstrated in this thesis by its effective application to a real case-study, which allowed us to work with the different types of sources considered in the methodology and the activities that support its construction and evolution

TechMiner: Extracting Technologies from Academic Publications

In recent years we have seen the emergence of a variety of scholarly datasets. Typically these capture ‘standard’ scholarly entities and their connections, such as authors, affiliations, venues, publications, citations, and others. However, as the repositories grow and the technology improves, researchers are adding new entities to these repositories to develop a richer model of the scholarly domain. In this paper, we introduce TechMiner, a new approach, which combines NLP, machine learning and semantic technologies, for mining technologies from research publications and generating an OWL ontology describing their relationships with other research entities. The resulting knowledge base can support a number of tasks, such as: richer semantic search, which can exploit the technology dimension to support better retrieval of publications; richer expert search; monitoring the emergence and impact of new technologies, both within and across scientific fields; studying the scholarly dynamics associated with the emergence of new technologies; and others. TechMiner was evaluated on a manually annotated gold standard and the results indicate that it significantly outperforms alternative NLP approaches and that its semantic features improve performance significantly with respect to both recall and precision

An Extended Semantic Interoperability Model for Distributed Electronic Health Record Based on Fuzzy Ontology Semantics

Semantic interoperability of distributed electronic health record (EHR) systems is a crucial problem for querying EHR and machine learning projects. The main contribution of this paper is to propose and implement a fuzzy ontology-based semantic interoperability framework for distributed EHR systems. First, a separate standard ontology is created for each input source. Second, a unified ontology is created that merges the previously created ontologies. However, this crisp ontology is not able to answer vague or uncertain queries. We thirdly extend the integrated crisp ontology into a fuzzy ontology by using a standard methodology and fuzzy logic to handle this limitation. The used dataset includes identified data of 100 patients. The resulting fuzzy ontology includes 27 class, 58 properties, 43 fuzzy data types, 451 instances, 8376 axioms, 5232 logical axioms, 1216 declarative axioms, 113 annotation axioms, and 3204 data property assertions. The resulting ontology is tested using real data from the MIMIC-III intensive care unit dataset and real archetypes from openEHR. This fuzzy ontology-based system helps physicians accurately query any required data about patients from distributed locations using near-natural language queries. Domain specialists validated the accuracy and correctness of the obtained resultsThis work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2021R1A2B5B02002599)S

A framework for semantic checking of information systems

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de ComputadoresIn this day and age, enterprises often find that their business benefits greatly if they collaborate with others in order to be more competitive and productive. However these collaborations often come with some costs since the worldwide diversity of communities has led to the development of various knowledge representation elements, namely ontologies that, in most cases, are not semantically equivalent. Consequently, even though some enterprises may operate in the same domain, they can have different representations of that same knowledge. However, even after solving this issue and establishing a semantic alignment with other systems, they do not remain unchanged. Subsequently, a regular check of its semantic alignment is needed. To aid in the resolution of this semantic interoperability problem, the author proposes a framework that intends to provide generic solutions and a mean to validate the semantic consistency of ontologies in various scenarios, thus maintaining the interoperability state between the enrolled systems

SWA-KMDLS: An Enhanced e-Learning Management System Using Semantic Web and Knowledge Management Technology

In this era of knowledge economy in which knowledge have become the most precious resource, surveys have shown that e-Learning has been on the increasing trend in various organizations including, among others, education and corporate. The use of e-Learning is not only aim to acquire knowledge but also to maintain competitiveness and advantages for individuals or organizations. However, the early promise of e-Learning has yet to be fully realized, as it has been no more than a handout being published online, coupled with simple multiple-choice quizzes. The emerging of e-Learning 2.0 that is empowered by Web 2.0 technology still hardly overcome common problem such as information overload and poor content aggregation in a highly increasing number of learning objects in an e-Learning Management System (LMS) environment. The aim of this research study is to exploit the Semantic Web (SW) and Knowledge Management (KM) technology; the two emerging and promising technology to enhance the existing LMS. The proposed system is named as Semantic Web Aware-Knowledge Management Driven e-Learning System (SWA-KMDLS). An Ontology approach that is the backbone of SW and KM is introduced for managing knowledge especially from learning object and developing automated question answering system (Aquas) with expert locator in SWA-KMDLS. The METHONTOLOGY methodology is selected to develop the Ontology in this research work. The potential of SW and KM technology is identified in this research finding which will benefit e-Learning developer to develop e-Learning system especially with social constructivist pedagogical approach from the point of view of KM framework and SW environment. The (semi-) automatic ontological knowledge base construction system (SAOKBCS) has contributed to knowledge extraction from learning object semiautomatically whilst the Aquas with expert locator has facilitated knowledge retrieval that encourages knowledge sharing in e-Learning environment. The experiment conducted has shown that the SAOKBCS can extract concept that is the main component of Ontology from text learning object with precision of 86.67%, thus saving the expert time and effort to build Ontology manually. Additionally the experiment on Aquas has shown that more than 80% of users are satisfied with answers provided by the system. The expert locator framework can also improve the performance of Aquas in the future usage. Keywords: semantic web aware – knowledge e-Learning Management System (SWAKMDLS), semi-automatic ontological knowledge base construction system (SAOKBCS), automated question answering system (Aquas), Ontology, expert locator

SMART Protocols: seMAntic represenTation for experimental protocols

Two important characteristics of science are the ?reproducibility? and ?clarity?. By rigorous practices, scientists explore aspects of the world that they can reproduce under carefully controlled experimental conditions. The clarity, complementing reproducibility, provides unambiguous descriptions of results in a mechanical or mathematical form. Both pillars depend on well-structured and accurate descriptions of scientific practices, which are normally recorded in experimental protocols, scientific workflows, etc. Here we present SMART Protocols (SP), our ontology-based approach for representing experimental protocols and our contribution to clarity and reproducibility. SP delivers an unambiguous description of processes by means of which data is produced; by doing so, we argue, it facilitates reproducibility. Moreover, SP is thought to be part of e-science infrastructures. SP results from the analysis of 175 protocols; from this dataset, we extracted common elements. From our analysis, we identified document, workflow and domain-specific aspects in the representation of experimental protocols. The ontology is available at http://purl.org/net/SMARTprotoco

Implementing OBDA for an end-user query answering service on an educational ontology

In the age where productivity of society is no longer defined by the amount of information generated, but from the quality and assertiveness that a set of data may potentially hold, the right questions to do depends on the semantic awareness capability that an information system could evolve into. To address this challenge, in the last decade, exhaustive research has been done in the Ontology Based Data Access (OBDA) paradigm. A conspectus of the most promising technologies with data integration capabilities and the foundations where they rely are documented in this memory as a point of reference for choosing tools that supports the incorporation of a conceptual model under a OBDA method. The present study provides a practical approach for implementing an ontology based data access service, to educational context users of a Learning Analytics initiative, by means of allowing them to formulate intuitive enquiries with a familiar domain terminology on top of a Learning Management System. The ontology used was completely transformed to semantic linked data standards and some data mappings for testing were included. Semantic Linked Data technologies exposed in this document may exert modernization to environments in which object oriented and relational paradigms may propagate heterogeneous and contradictory requirements. Finally, to validate the implementation, a set of queries were constructed emulating the most relevant dynamics of the model regarding the dataset nature

KNOWLEDGE BASE REPRESENTATION WITH AXIOMATIC DESIGN RULES FOR CONCEPT LEVEL UP IMPLEMENT IN ONTOLOGICAL FRAMEWORK

Axiomatic Design has been applied and developed as a tool, offering a scientific basis for design and improving design activities. Axiomatic Design has been used in various fields such as software system design, structure design, and product design. However, several challenges and limitations exist in Axiomatic Design including: the inconsistency in identifying design parameters, existence of coupled design, and multiple groups of functional requirements and design parameters. Aimed at using Axiomatic Design to generate conceptual solutions in engineering design while overcoming its limitations, a formal ontology is developed. The ontology defines functional requirements, design parameters, concepts, components and variables and their relationships. Axioms and rules of the Axiomatic Design ontology are discussed and summarized, which helps users understand the design issue deeply. The Axiomatic Design ontology is demonstrated to the car seat design as an example. Specific axioms and rules are generated and analyzed while the classes of concepts and components are built. With the help of the Axiomatic Design ontology and its axioms and rules, several example concepts are generated and then compared and analyzed. The Axiomatic Design ontology provides numerous design concepts and potentially helps users increase their creativity. The Axiomatic Design ontology allows coupling system to exist as the possible solutions. Besides, other factors need to be considered and other tools are necessary for evaluating design solutions