KEOD 2020 Abstracts


Full Papers
Paper Nr: 6
Title:

Emerging Named Entity Recognition in a Medical Knowledge Management Ecosystem

Authors:

Christian Nawroth, Felix Engel and Matthias Hemmje

Abstract: In this paper, we present a knowledge engineering project in the medical domain. The objective of the project is to identify recent medical knowledge represented by emerging Named Entities. Hence, we introduce the concept of emerging Named Entities and present our studies on their occurrence and use in medical document corpora. We derive an approach for the emerging Named Entity Recognition utilizing textual and temporal features through Natural Language Processing and Machine Learning and present detailed evaluation results. Furthermore, we present a complementary system design that utilizes emerging Named Entity Recognition support several KE use cases in the medical domain.

Paper Nr: 11
Title:

Modeling Semantic and Syntactic Valencies of Tibetan Verbs in the Formal Grammar and Computer Ontology

Authors:

Aleksei Dobrov, Anna Kramskova and Maria Smirnova

Abstract: This article presents the current results and details of modeling the Tibetan verbal system in the formal grammar and computer ontology. The partially automated model uses an ontological editor to construct semantic classes for verbs based on their syntactic and semantic valencies following the corpus data. The resulting system plays a necessary pragmatic role in automatic syntactic and semantic analysis and disambiguation of Tibetan texts. The research covers a range of problems concerning Tibetan verbal system, such as modeling auxiliary verbs and copulas, verb compounds, verbs with special case government and others.

Paper Nr: 15
Title:

An Ontology of Chinese Ceramic Vases

Authors:

Tong Wei, Christophe Roche, Maria Papadopoulou and Yangli Jia

Abstract: Extensive collections of Chinese ceramic vases are housed in museums throughout China. They could serve as rich sources of data for historical research. Although some data sources have been digitized, the vision of heritage institutions is not only to display objects and simple descriptions (drawn from metadata) but also to allow for understanding relationships between objects (created by semantically interrelated metadata). The key to achieving this goal is to utilize the technologies of the Semantic Web, whose core is Ontology. The focus of this paper is to describe the construction of the TAO CI (“ceramics” in Chinese) ontology of the domain of ceramic vases of the Ming (1368-1644) and Qing (1644-1911) dynasties. The theoretical and methodological approach adopted to construct the TAO CI ontology is term-and-characteristic guided, i.e., it relies on a morphological analysis of the Chinese terms used in the domain, and respects the ISO principles on Terminology (ISO 1087 and 704), according to which concepts are defined by means of essential characteristics. The research presented in this article aims to publish the resulting structured data on the Semantic Web for the use of anybody interested, including museums hosting collections of these vessels, and to enrich existing methodologies on domain ontology building. To our knowledge, there are no comprehensive ontologies for Chinese ceramic vases. TAO CI ontology remedies this gap and provides a reference for ontology building in other domains of Chinese cultural heritage. The tool used is Protégé. The TAO CI ontology is open access here: http://www.dh.ketrc.com/otcontainer/data/OTContainer.owl.

Paper Nr: 17
Title:

Semantic Representation of Physics Research Data

Authors:

Aysegul Say, Said Fathalla, Sahar Vahdati, Jens Lehmann and Sören Auer

Abstract: Improvements in web technologies and artificial intelligence enable novel, more data-driven research practices for scientists. However, scientific knowledge generated from data-intensive research practices is disseminated with unstructured formats, thus hindering the scholarly communication in various respects. The traditional document-based representation of scholarly information hampers the reusability of research contributions. To address this concern, we developed the Physics Ontology (PhySci) to represent physics-related scholarly data in a machine-interpretable format. PhySci facilitates knowledge exploration, comparison, and organization of such data by representing it as knowledge graphs. It establishes a unique conceptualization to increase the visibility and accessibility to the digital content of physics publications. We present the iterative design principles by outlining a methodology for its development and applying three different evaluation approaches: data-driven and criteria-based evaluation, as well as ontology testing.

Paper Nr: 24
Title:

CODO: An Ontology for Collection and Analysis of Covid-19 Data

Authors:

Biswanath Dutta and Michael DeBellis

Abstract: The COVID-19 Ontology for cases and patient information (CODO) provides a model for the collection and analysis of data about the COVID-19 pandemic. The ontology provides a standards-based open source model that facilitates the integration of data from heterogenous data sources. The ontology was designed by analysing disparate COVID-19 data sources such as datasets, literature, services, etc. The ontology follows the best practices for vocabularies by re-using concepts from other leading vocabularies and by using the W3C standards RDF, OWL, SWRL, and SPARQL. The ontology already has one independent user and has incorporated real world data from the government of India.

Paper Nr: 25
Title:

Towards Construction of Legal Ontology for Korean Legislation

Authors:

Thi T. Phan, Ho-Pun Lam, Mustafa Hashmi and Yongsun Choi

Abstract: Automating information extraction from legal documents and formalising them into a machine understandable format has long been an integral challenge to legal reasoning. Most approaches in the past consist of highly complex solutions that use annotated syntactic structures and grammar to distil rules. The current research trend is to utilise state-of-the-art natural language processing (NLP) approaches to automate these tasks, with minimum human interference. In this paper, based on its functional aspects, we propose a legal taxonomy of semantic types in Korean legislation, such as definitional provision, deeming provision, penalty, obligation, permission, prohibition, etc. In addition to this, a NLP classifier has been developed to facilitate the automated legal norms classification process and an overall F1 score of 0.97 has been achieved.

Paper Nr: 29
Title:

Ontology-based Processing of Dynamic Maps in Automated Driving

Authors:

Haonan Qiu, Adel Ayara and Birte Glimm

Abstract: Autonomous cars act in a highly dynamic environment and consistently have to provide safety and comfort to the passengers. For a car to understand its surroundings, a detailed, high-definition digital map is needed, which acts as a powerful virtual “sensor”. Compared to traditional digital maps, high-definition maps require significantly more storage space, which makes it largely impossible to store a complete map in a navigation system. Furthermore, map data is provided in numerous heterogeneous formats. Consequently, interoperability and scalability have become the main challenges of existing map processing solutions. We address these challenges by providing an interoperable knowledge-spatial architecture layer based on ontologies and confirm the scalability in an empirical evaluation.

Paper Nr: 39
Title:

Supporting Named Entity Recognition and Document Classification in a Knowledge Management System for Applied Gaming

Authors:

Philippe Tamla, Florian Freund and Matthias Hemmje

Abstract: In this research paper, we present a system for named entity recognition and automatic document classification in an innovative knowledge management system for Applied Gaming. The objective of this project is to facilitate the management of machine learning-based named entity recognition models, that can be used for both: extracting different types of named entities and classifying textual documents from heterogeneous knowledge sources on the Web. We present real-world use case scenarios and derive features for training and managing NER models with the Stanford NLP machine learning API. Then, the integration of our developed NER system with an expert rule-based system is presented, which allows an automatic classification of textual documents into different taxonomy categories available in the knowledge management system. Finally, we present the results of a qualitative evaluation that was conducted to optimize the system user interface and enable a suitable integration into the target system.

Paper Nr: 51
Title:

Systemic Business Process Simulation using Agent-based Simulation and BPMN

Authors:

Jácint Duduka and Sérgio Guerreiro

Abstract: The current paradigm of a business process model is that it is a representation of a sequence of tasks that act upon some data input, to produce an output, aiming the production of a new service or product to be delivered from a producer to a customer. Although this is a valid way of thinking, it neglects to consider in enough detail the influence of some phenomenon on inputs, e.g. human behaviour, communication, social interactions, the organisational culture which can have a significant effect on the output delivered by a business process. As the dynamics of these phenomena are non-linear, they can be interpreted as a complex system. This holistic way of thinking about business processes opens the doors to the possibility of combining different simulation methods to model different aspects that influence a process. A BPMN engine and an agent-based simulation (ABS) engine are chosen to serve the basis of our framework. In its conception, we not only consider the technical aspects of the framework but also delve into exploring its management and organizational dimensions, with the intent of facilitating its adoption in enterprises, as a tool to support decision support systems. We analyse how accurate the simulation results can be when using these two tools as well as what considerations need to be considered within organizations.

Short Papers
Paper Nr: 2
Title:

Measuring Design Complexity of Cultural Heritage Ontologies

Authors:

Bilal Ben Mahria, Ilham Chaker and Azeddine Zahi

Abstract: Nowadays, Ontologies have become widely used to design formalism for knowledge representation, and are considered as the foundation for the Semantic Web. However, with their widespread usage, a question of their complexity evaluation increased even more, especially in some domains that currently know a cruise number of ontologies like Cultural Heritage. In this paper, we present an analysis of the advanced metrics for measuring the design complexity of existing cultural heritage ontologies (CH). In this context, the main goals of this study are to (i) present advanced metrics such as the size of vocabulary, the tree impurity, coupling, average number of path per concept, and average path length, in order to analyze the advanced complexity features of the CH ontologies and their impact on the reuse and evolution of the CH ontologies; (ii) Help developers to decide whether the ontology is over complex that it needs some simplification or re-building; (iii) Make developers clearly realize the impact of the size and scale of ontology. In order to reach these goals, a set of twenty CH ontologies are gathered from the web to measure and analyze their advanced complexity metrics. By analyzing the size of vocabulary, the average number of paths per concept, and average path length, the evaluation results exhibit that the CH ontologies studied are highly complex. In addition, the CH ontologies cannot be easily maintained due to the findings reached through the analysis of the tree impurity and coupling.

Paper Nr: 7
Title:

Harmoney: Semantics for FinTech

Authors:

Stijn Verstichel, Thomas Blommaert, Stijn Coppens, Thomas Van Maele, Wouter Haerick and Femke Ongenae

Abstract: As a result of legislation imposed by the European Parliament, in order to protect inhabitants from being exposed to a too high financial risk when investing in a variety of financial markets and products, Financial Service Providers (FSPs) are obliged to test the knowledge and experience of potential investors. This is oftemtimes done by means of questionnaires. However, these questionnaires differ in style and structure from one FSP to the other. The goal of this research is to manage in a more cost-effective manner (aligned with the needs and competencies of the individual financial investor in terms of products and services) the management of the private equity and to facilitate the fine-tuned personalised financial advisory services needed. This is achieved by means of a knowledge-based approach, integrating the available information of the investor (e.g. personal profile in terms of financial knowledge and experience) and for an extendable amount of financial service providers with their financial products and demonstrated by a number of exemplary use case scenarios.

Paper Nr: 10
Title:

Towards an Ontology for Representing a Student’s Profile in Adaptive Gamified Learning System

Authors:

Siwar Missaoui, Souha Bennani and Ahmed Maalel

Abstract: Learner and learning content are the key factors contributing towards the success of any adaptive learning system. Each learner searches for an adequate environment to his needs which offers personalized and adaptive content that provides a learning experience to be more successful and more useful to him. Moreover, he likes to study in a fun and entertaining environment that gives them a sense of engagement and motivation. Education research shows that considering student profile is effective in adapting courses and profile modeling is an important process that aims to give as complete representation as possible of all the aspects related to the user's features. With regard to motivation, some studies have approved that gamification is a good solution to enhance student engagement and that there is a strong link between it and motivation. Therefore, this article presents our contribution through a SPOnto ontology for representation of students profile, by combining the two concepts “adaptive learning” and “gamification” to provide a personalized gamified experience. We propose a student profile ontology, to benefit from semantic web technologies, which presents a global model of the student based on many important characteristics in order to help decision-making in the different academic contexts and to motivate him to achieve his learning goals.

Paper Nr: 12
Title:

Tracing the Evolution of Approaches to Semantic Similarity Analysis

Authors:

Weronika T. Adrian, Sebastian Skoczeń, Szymon Majkut, Krzysztof Kluza and Antoni Ligęza

Abstract: Capturing the essence of semantic similarity of words or concepts in order to quantify it and measure has been an inspiring challenge for the last decades. From corpus-based statistics to metrics based on structured knowledge bases, a plethora of methods has been proposed in several branches of Artificial Intelligence. Recently, with the advent of knowledge graphs, a renewed interest in similarity metrics can be observed. Choosing appropriate metrics that will work best in a given situation is not a trivial task. To help navigate through the semantic similarity algorithms and understand the characteristics of them, we have analyzed the fundamental proposals in this domain and the evolution of them over the years. In this paper, we present a review of the approaches to measuring semantic similarity of entities in knowledge bases. We organize the findings into a taxonomy and analyze the relations between and within the identified categories. To complement the research with a practical solution, we present a new tool that supports the literature review process with graph-based and temporal visualizations.

Paper Nr: 18
Title:

An Ontological View of the RAMI4.0 Asset Administration Shell

Authors:

Andreas W. Müller, Irlán Grangel-González and Christoph Lange

Abstract: Information interoperability is of paramount importance to Industry 4.0 (I4.0). To this end, the Reference Architecture Model for I4.0 (RAMI4.0) defines the Asset Administration Shell (AS) concept as a core element for interoperable descriptions of assets. Assets, such as Cyber-Physical Systems, are building blocks that need to be interchangeable between various industrial systems but are heterogeneously modeled. In order to achieve the required interoperability between these systems, semantics is key. Typically, two types of systems occur in I4.0 scenarios: legacy systems not considering explicit semantics, and a new generation of ontology-based systems. However, existing approaches for modeling the AS do not explicitly address this situation of interoperability between systems of such different types. In this article, we develop an ontological view of the AS concept to bridge the gap between these types of systems. This results in an ontology that is intended to be likewise realizable with both ontology-based and non-ontology-based systems. We present this ontology together with a suggested two-phase engineering process for its application.

Paper Nr: 22
Title:

Consistency and Interoperability on Dublin Core Element Values in Collections Harvested using the Open Archive Initiative Protocol for Metadata Harvesting

Authors:

Sarantos Kapidakis

Abstract: When resource descriptions use the exact same value for an entity, this value is easier parsed, identified and utilized by automatic procedures. The use of controlled values, even when it is common and very useful, it is usually not enforced during the data entry. In this paper we study the use of the controlled values in many harvested collections and we study all Dublin Core elements and also their similarity. We mainly focus in the element language, as there is a lot of standardization on how to denote language values, followed by other elements that normally use controlled values. We discovered values that are repeated many times and in many collections and many more values that are used only once! The lack of coordination among collections during their creation results to many variations for each value, even when the value is used consistently and many times inside a collection. The study uses dendrogram to reveal the current usage of the Dublin Core elements inside and among active collections by clustering the collections with similar values and helps adopting better guidelines, designing better tools and improving the effectiveness of the collections.

Paper Nr: 27
Title:

Intensional Model for Data Integration System in Open Environment

Authors:

Islam Ali and Kenneth McIsaac

Abstract: Open environment allows agents to associate and/or dissociate with the environment without affecting the overall functionality of the system. There are several challenges to modeling data integration systems (DIS) in open environment. This is because of the distributed, dynamic, heterogeneous, and loosely coupled nature of open environment. It is also important to note that information systems are intensional in nature. This is because the belief of an agent and the knowledge of an information system are intensional contexts. Open environments are also intensional in nature. This is because, the dynamic nature of open environment imposes no constrains on the set of participating agents or the number information systems plugged into the system. We propose the use of Mediated P2P architecture for the architecture of data integration systems in open environment. The DIS is formulated using Intensional Epistemic Logic (IEL). We also present an interface and query answering semantics that are based on the IEL. The proposed model accounts for the intensional, distributed, dynamic, and loosely-coupled characteristics of open environment.

Paper Nr: 30
Title:

Knowledge Discovery from ISAD, Digital Archive Data, into ArchOnto, a CIDOC-CRM based Linked Model

Authors:

Dora Melo, Irene P. Rodrigues and Inês Koch

Abstract: This paper presents an automatic semantic migration prototype based on Knowledge Discovery from Digital Archive Data for ontology population in the domain of Archives metadata, ISAD(G). Natural Language Processing (NLP) techniques are used for language processing and Semantic Web techniques for querying and updating the Ontology ArchOnto, a CIDOC-CRM (Conceptual Reference Model) extension. This work is done in the context of project EPISA (Entity and Property Inference for Semantic Archives) where the Portuguese National Archives, Torre do Tombo (ANTT) is one of the partners. The data model and description vocabularies we adopted are built upon the CIDOC-CRM standard, an ontology, developed for museums by the International Committee for Documentation (CIDOC) of the International Council of Museums (ICOM). A detailed example of a baptism document metadata migration is presented to highlight the challenges on the natural language interpretation and the ontology representation.

Paper Nr: 33
Title:

Driving Context Detection and Validation using Knowledge-based Reasoning

Authors:

Abderraouf Khezaz, Manolo D. Hina, Hongyu Guan and Amar Ramdane-Cherif

Abstract: The intensive research on artificial intelligence and internet of things is speeding up the rise of smart cities and autonomous vehicles. In order to ensure the safety of the drivers and pedestrians, the transportation network needs to be connected to its surroundings and consider every valuable piece of information it can gather. Knowledge bases have proven themselves to be efficient in the storage and processing of structured data, making them interesting solutions for the management of transportation networks. This study focuses on the building of a driving simulator allowing the gathering of practical data that can be processed by an ontology and a set of rules, and can quickly and continuously infer a result to suggest the driver on an optimal choice to make. The accuracy results are encouraging, yet giving us extra room for improvement.

Paper Nr: 34
Title:

A Distributed Approach for Parsing Large-scale OWL Datasets

Authors:

Heba Mohamed, Said Fathalla, Jens Lehmann and Hajira Jabeen

Abstract: Ontologies are widely used in many diverse disciplines, including but not limited to biology, geology, medicine, geography and scholarly communications. In order to understand the axiomatic structure of the ontologies in OWL/XML syntax, an OWL/XML parser is needed. Several research efforts offer such parsers; however, these parsers usually show severe limitations as the dataset size increases beyond a single machine’s capabilities. To meet increasing data requirements, we present a novel approach, i.e., DistOWL, for parsing large-scale OWL/XML datasets in a cost-effective and scalable manner. DistOWL is implemented using an in-memory and distributed framework, i.e., Apache Spark. While the application of the parser is rather generic, two use cases are presented for the usage of DistOWL. The Lehigh University Benchmark (LUBM) has been used for the evaluation of DistOWL. The preliminary results show that DistOWL provides a linear scale-up compared to prior centralized approaches.

Paper Nr: 37
Title:

Semantic Knowledge-Based-Engineering: The Codex Framework

Authors:

J. Zamboni, A. Zamfir and E. Moerland

Abstract: The development of complex systems within multi-domain environments requires an effective way of capturing, sharing and integrating knowledge of the involved experts. Modern Knowledge-Based Engineering (KBE) systems fulfill this function, making formalized knowledge executable by using highly specialized environments and languages. However, the dedication of these environments to their domain of application poses limitations on the cross-domain integration of KBE applications. The use of Semantic Web Technologies (SWT) delivers a domain-neutral way of knowledge formalization and data integration which promises to drastically reduce the effort required to integrate knowledge of multiple domains in a single representation. Especially within the complex field of aeronautical vehicle design the authors are working in, characterized by several individual disciplines having to be considered simultaneously, the combined usage of KBE and SWT technologies seems an attractive approach for the continued digitalization of the design process. In this paper, the COllaborative DEsign and eXploration (Codex) framework is presented which aims at merging these two technologies into a single framework that can be used to create domain-specific knowledge-bases and integrate these into a single model of the overall product. Formalizing and executing this model will lead to a more transparent and integrated view on complex product design.

Paper Nr: 38
Title:

Ontology Metrics as a Service (OMaaS)

Authors:

Achim Reiz, Henrik Dibowski, Kurt Sandkuhl and Birger Lantow

Abstract: The use of automatically calculated metrics for the evaluation of ontologies can provide impartial support for knowledge engineers. However, even though the use of ontological representations is unabated – in opposite expected to rise through the increasing use of AI technologies – most ontology evaluation tools today are no longer available or outdated. At the same time, due to the growth of the computational cloud, service-driven architectures are on the rise, and enterprises tend to prefer to consume services in a platform- or software as a service model. In this paper, we argue that the change of the IT-landscape also requires a change in how we offer and consume ontology metrics. This hypothesis is backed by an industrial use-case of Robert Bosch GmbH and their application of ontologies, as well as their need and requirements for ontology evaluation. It motivated the extension of the tool OntoMetrics with a REST-interface, offering a public endpoint for ontology metrics on the Internet.

Paper Nr: 40
Title:

On IT Risk Management Ontology using DEMO

Authors:

Mariana Rosa, Sérgio Guerreiro and Rúben Pereira

Abstract: Nowadays, organisations use and rely on Information Technology (IT) solutions. However, despite their benefits, IT solutions induct risks. Consequently, organisations implement Risk Management (RM), more specifically Information Technology Risk Management (IT RM), in order to maximize the effectiveness of IT usage while dealing with IT risks. Nevertheless, IT RM’s implementation is not easy, since numerous standards and frameworks propose multiple RM processes to deal with IT risks. Moreover, these processes are composed of different activities causing confusion. In the end, organisations are not capable of managing risks successfully due to IT RM’s complexity. To overcome IT RM diversity, a Systematic Literature Review (SLR) was conducted. The goal is to identify which are the most essential IT RM activities. The SLR results were then integrated with ISO 31000 and PMBOK standards in the form of an ontology using Design and Engineering Methodology Ontology (DEMO). The contributions of this study are: the aggregate analysis of IT RM activities through the SLR; the identification of reasons and benefits of using DEMO; a description of an IT RM’s essential model designed as an ontology; and a critical view of the benefits of the ontological model proposed.

Paper Nr: 42
Title:

Topic-OPA: A Topic Ontology for Modeling Topics of Old Press Articles

Authors:

Mirna El Ghosh, Cecilia Zanni-Merk, Nicolas Delestre, Jean-Philippe Kotowicz and Habib Abdulrab

Abstract: Topic ontologies are recently gaining much importance in several domains. Their purpose is to identify the themes necessary to describe the knowledge structure of an application domain. Meanwhile, their development from scratch is hard and time consuming task. This paper discusses the development a topic-specific ontology, named Topic-OPA, for modeling topics of old press articles. Topic-OPA is extracted from the open knowledge graph Wikidata by the application of a SPARQL-based fully automatic approach. The development process of Topic-OPA depends mainly on a set of disambiguated named entities representing the articles. Each named entity is unambiguously identified by a Wikidata URI. In contrast to existent topic ontologies, which are limited to taxonomies, the structure of Topic-OPA is composed of hierarchical and non-hierarchical schemes. The domain application of this work is the old french newspaper Le Matin. Finally, an evaluation process is performed to assess the structure quality of Topic-OPA.

Paper Nr: 45
Title:

Semantic Search for Biomedical Texts using Predicate-Argument Structure

Authors:

Mohammed Alliheedi and Robert E. Mercer

Abstract: In this position paper we argue that using semantic roles in addition to using biologically-oriented ontologies and databases (or knowledge bases) will further enhance the generation of RDF triples that can be collected from biomedical text. RDF triples have been used to enhance semantic search beyond the simple use of linguistically oriented additions such as synonyms. We wish to focus on drug-virus interactions.

Paper Nr: 47
Title:

Method of Semantic Refinement for Enterprise Search

Authors:

Alexey Pismak, Serge Klimenkov, Eugeny Tsopa, Alexandr Yarkeev, Vladimir Nikolaev and Anton Gavrilov

Abstract: In this paper, we propose an approach of using the semantic refinement of the input search query for the enterprise search systems. The problem of enterprise search is actual because of the amount of processed data. Even with a good organization of documents, the process of searching for specific documents or specific data in these documents is very laborious. But even more significant problem is that the required content may have the matching meaning, but expressed with different words in the different languages, which prevents it from appearing in the search result. The proposed approach uses semantic refinement of the search query. First, the concepts are extracted from the semantic network based on translingual lexemes of the user query string, allowing to perform the search based on the senses rather than word forms. In addition, several rules are applied to the query in order to include or exclude senses which can affect the relevance and the pertinence of the search result.

Paper Nr: 48
Title:

Some Techniques for Intelligent Searching on Ontology-based Knowledge Domain in e-Learning

Authors:

Nhon V. Do, Hien D. Nguyen and Long N. Hoang

Abstract: E-learning is the modern way to learn by using electronic media and information and communication technologies in education. Ontology is a useful method to organize knowledge bases for intelligent educational systems. In this paper, a method for intelligent searching on ontology-based knowledge domain in e-learning is presented. This method includes an ontology representing educational knowledge domains, called Search-Onto. The foundation of this ontology is concepts, relations between concepts, operators, and rules combining the structures of problems and their solving methods. Beside the ontology organizing the knowledge base, the proposed method also studies some techniques for intelligent searching, such as searching for the knowledge content, searching on the knowledge classification, and searching the related knowledge. The method for intelligent searching based on a knowledge base has been applied to construct a search engine for the knowledge of high-school mathematics. This engine can do searching works and retrieve required information in mathematics for high-school students to support their learning.

Paper Nr: 20
Title:

Extended Knowledge Graphs: A Conceptual Study

Authors:

Weronika T. Adrian, Marek Adrian, Krzysztof Kluza, Bernadetta Stachura-Terlecka and Antoni Ligęza

Abstract: The amount and variety of data that we produce every day pose a constant challenge for meaningful information processing. While knowledge graphs have gained a considerable attention in the recent years, due to their flexible and universal knowledge representation, they lack the mechanisms facilitating knowledge processing. In this paper, we propose an information system called extended knowledge graphs (EKG) that augments the concept of knowledge graphs with procedural attachments. We put forward the requirements and assumption of the EKG structure and present a categorisation of supported reasoning tasks.

Paper Nr: 31
Title:

On Specifying and Analysing Domain Ontologies for Workflows in “Binary Model of Knowledge"

Authors:

Gerald S. Plesniewicz and Valery B. Tarasov

Abstract: The main purpose of the present paper is to show how concept languages of the system “Binary Model of Knowledge” can be used for specifying workflow ontologies. The system is under development in the Applied Mathematics and Artificial Intelligence Department of National Research University MPEI (Moscow). In particular, the system includes the language LTS of temporal specification. The language includes the sentences matching the sentences of the Boolean and metric extensions of Allen’s interval logic. For the extended logics we present the complete systems of inference rules (in style of analytic tableaux).

Paper Nr: 32
Title:

Annotating Arguments in a Parliamentary Corpus: An Experience

Authors:

Mare Koit

Abstract: Estonian parliamentary corpus includes verbatim records of sessions held in the Parliament of Estonia (Riigikogu) in 1995-2001. An important task of the Riigikogu is the passing of acts and resolutions. A bill initiated in the Riigikogu will pass three readings, during which it is refined and amended. Negotiation is an important part of parliamentary discussions. Arguments for and against of the bill and its amendments are presented by the members of the Parliament in negotiation. In the paper, arguments used in negotiation are considered. Every argument consists of one or more premises, and a claim (or conclusion). The arguments and the relations between them (rebuttal, attack, and support) are determined with the aim to create a corpus where arguments are annotated. Some problems are discussed in relation with annotation. Our further aim is the automatic recognition of arguments and inter-argument relations in Estonian political texts.

Paper Nr: 36
Title:

Analysis of Data Anonymization Techniques

Authors:

Joana F. Marques and Jorge Bernardino

Abstract: The privacy of personal data is a very important issue these days. How to process the data and use it for analysis without compromising the individual’s identity is a critical task and must be done in order to ensure the anonymity of this data. To try to unanimously unify this anonymity, laws and regulations such as GDPR were created. In this paper, GDPR will be described and the concepts of anonymization and pseudonymization will be explained. We present some of the main anonymization techniques and efficient software to support the application of these techniques. The main objective is to understand which techniques offer a higher level of anonymization, the strengths and weakness of each one and the advantages in its use.

Paper Nr: 41
Title:

Creating Core Ontology for Social Sciences Empirical Data Integration

Authors:

Dmitry Kudryavtsev, Tatiana Gavrilova and Alena Begler

Abstract: There exist several dozens of metadata standards for empirical research data, making it difficult for users to choose and apply such standards. Consequently, the integration of datasets from similar empirical studies for further knowledge acquisition is highly constrained. To resolve this problem, an ontology for social science research data integration (Empirion-core) has been developed. The ontology reuses existing data integration schemas: DDI-RDF Discovery Vocabulary, Generic Statistical Information Model, Core Ontology for Scientific Research Activities, Data Catalog Vocabulary, and DCMI Metadata Terms. It consists of five subontologies that provide concepts for empirical datasets description: Information resource ontology, Research activity ontology, Research coverage ontology, Measurement ontology, and Sampling ontology.

Paper Nr: 43
Title:

Automated DEMO Action Model Implementation using Blockchain Smart Contracts

Authors:

Marta Aparício, Sérgio Guerreiro and Pedro Sousa

Abstract: Enterprise Ontology theory describes a well-founded method to model the essence of an organization in a coherent, comprehensive, consistent, and concise way. Enterprise Ontology can offer advantages in understanding the essence of an organization and in using organization models as a starting point for building software supporting organizations. The availability of ontological models that express the essence of an organization becomes the fundamental element to support the correct implementation of Smart Contracts in the Blockchain of that same organization. In this context, it is intended to automatically extract from the DEMO Action Model the knowledge necessary to produce Smart Contracts in Blockchain. The advantage to be obtained is the reuse of the modeling done ontologically in line with a correct implementation of the Smart Contracts. This research feasibility is demonstrated through the well-known Rent-A-Car case.

Paper Nr: 44
Title:

AI-T: Software Testing Ontology for AI-based Systems

Authors:

J. I. Olszewska

Abstract: Software testing is an expanding area which presents an increasing complexity. Indeed, on one hand, there is the development of technologies such as Software Testing as a Service (TaaS), and on the other hand, there is a growing number of Artificial Intelligence (AI)-based softwares. Hence, this work is about the development of an ontological framework for AI-softwares’ Testing (AI-T), which domain covers both software testing and explainable artificial intelligence; the goal being to produce an ontology which guides the testing of AI softwares, in an effective and interoperable way. For this purpose, AI-T ontology includes temporal interval logic modelling of the software testing process as well as ethical principle formalization and has been built using the Enterprise Ontology (EO) methodology. Our resulting AI-T ontology proposes both conceptual and implementation models and contains 708 terms and 706 axioms.