Visualization for biomedical ontologies alignment

Tese de mestrado, Bioinformática e Biologia Computacional (Bioinformática), Universidade de Lisboa, Faculdade de Ciências, 2016Desde o início do século, a investigação biomédica e a prática clínica levaram a uma acumulação de grandes quantidades de informação, por exemplo, os dados resultantes da sequenciação genómica ou os registos médicos. As ontologias fornecem um modelo estruturado com o intuito de representar o conhecimento e têm sido bem sucedidas no domínio biomédico na melhoria da interoperabilidade e partilha. O desenvolvimento desconectado das ontologias biomédicas levou à criação de modelos que apresentam domínios idênticos ou sobrepostos. As técnicas de emparelhamento de ontologias foram desenvolvidas afim de estabelecer ligações significativas entre as classes das ontologias, por outras palavras, para criar alinhamentos. Para alcançar um alinhamento ótimo é, não só importante melhorar as técnicas de emparelhamentos mas também criar as ferramentas necessárias para que possa existir intervenção humana, particularmente na visualização. Apesar da importância da intervenção de utilizadores e da visualização no emparelhamento de ontologias, poucos sistemas o suportam, sobretudo para grandes e complexas ontologias como as do domínio biomédico, concretamente no contexto da revisão de alinhamentos e interpretação de incoerências lógicas. O objetivo central desta tese consistiu na investigação dos principais paradigmas de visualização de ontologias, no contexto do alinhamento de ontologias biomédicas, e desenvolver abordagens de visualização e interação que vão de encontro a estes desafios. O trabalho desenvolvido levou, então, à criação de um novo módulo de visualização para um sistema de emparelhamento do state of the art que suporta a revisão de alinhamentos, e à construção de uma ferramenta online que visa ajudar o utilizador a compreender os conflitos encontrados nos alinhamentos, ambos baseados numa abordagem de visualização de subgrafos. Ambas as contribuições foram avaliadas em pequena escala, por testes a utilizadores que revelaram a relevância da visualização de subgrafos contra a visualização em árvore, mais comum no domínio biomédico.Since the begin of the century, biomedical research and clinical practice have resulted in the accumulation of very large amounts of information, e.g. data from genomic sequencing or medical records. Ontologies provide a structured model to represent knowledge and have been quite successful in the biomedical domain at improving interoperability and sharing. The disconnected development of biomedical ontologies has led to the creation of models that have overlapping or even equal domains. Ontology matching techniques were developed to establish meaningful connections between classes of the ontologies, in other words to create alignments. In order to achieve an optimal alignment, it is not only important to improve the matching techniques but also to create the necessary tools for human intervention, namely in visualization. Despite the importance of user intervention and visualization in ontology matching, few systems support these, especially for large and complex ontologies such as those in the biomedical domain, specifically in the context of the alignment revision and logical incoherence explanation. The central objective of this thesis was to investigate the main ontology visualization paradigms, in the context of biomedical ontology matching, and to develop visualization and interaction approaches addressing those challenges. The work developed lead to the creation of a new visualization module for a state of the art ontology matching system, that supports the alignment review, and to the construction of an online tool that aims to help the user understand the conflicts found in the alignments both based on a subgraph visualization approach. Both contributions were evaluated, in a small-scale, by user tests that revealed the relevance of subgraph visualization versus the more common tree visualization for the biomedical domain

Helping scientists integrate and interact with biomedical data

Tese de mestrado, Bioinformática e Biologia Computacional , 2021, Universidade de Lisboa, Faculdade de CiênciasFor the past decades, the amount and complexity of biomedical data available have increased and far exceeded the human capacity to process it. To support this, knowledge graphs and ontologies have been increasingly used, allowing semantic integration of heterogeneous data within and across domains. However, the independent development of biomedical ontologies has created heterogeneity problems, with the design of ontologies with overlapping domains or significant differences. Automated ontology alignment techniques have been developed to tackle the semantic heterogeneity problem, by establishing meaningful correspondences between entities of two ontologies. However, their performance is limited, and the alignments they produce can contain erroneous, incoherent, or missing mappings. Therefore, manual validation of automated ontology alignments remains essential to ensure their quality. Given the complexity of the ontology matching process, is important to provide visualization and a user interface with the necessary features to support the exploration, validation, and edition of alignments. However, these aspects are often overlooked, as few alignment systems feature user interfaces enabling alignment visualization, fewer allow editing alignments, and fewer provide the functionalities needed to make the task seamless for users. This dissertation developed VOWLMap — an extension for the standalone web application, WebVOWL — for visualizing, editing, and validating biomedical ontology alignments. This work extended the Visual Notation for OWL Ontologies (VOWL), which defines a visual representation for most language constructs of OWL, to support graphical representations of alignments and restructured WebVOWL to load and visualize alignments. VOWLMap employs modularization techniques to facilitate the visualization of large alignments, while maintaining the context of each mapping, and offers a dynamic visualization that supports interaction mechanisms, including direct interaction with and editing of graph representations. A user study was conducted to evaluate the usability and performance of VOWLMap, having obtained positive feedback with an excellent score in a standard usability questionnaire

Visual exploration of semantic-web-based knowledge structures

Humans have a curious nature and seek a better understanding of the world. Data, in- formation, and knowledge became assets of our modern society through the information technology revolution in the form of the internet. However, with the growing size of accumulated data, new challenges emerge, such as searching and navigating in these large collections of data, information, and knowledge. The current developments in academic and industrial contexts target the corresponding challenges using Semantic Web techno- logies. The Semantic Web is an extension of the Web and provides machine-readable representations of knowledge for various domains. These machine-readable representations allow intelligent machine agents to understand the meaning of the data and information; and enable additional inference of new knowledge. Generally, the Semantic Web is designed for information exchange and its processing and does not focus on presenting such semantically enriched data to humans. Visualizations support exploration, navigation, and understanding of data by exploiting humans’ ability to comprehend complex data through visual representations. In the context of Semantic- Web-Based knowledge structures, various visualization methods and tools are available, and new ones are being developed every year. However, suitable visualizations are highly dependent on individual use cases and targeted user groups. In this thesis, we investigate visual exploration techniques for Semantic-Web-Based knowledge structures by addressing the following challenges: i) how to engage various user groups in modeling such semantic representations; ii) how to facilitate understanding using customizable visual representations; and iii) how to ease the creation of visualizations for various data sources and different use cases. The achieved results indicate that visual modeling techniques facilitate the engagement of various user groups in ontology modeling. Customizable visualizations enable users to adjust visualizations to the current needs and provide different views on the data. Additionally, customizable visualization pipelines enable rapid visualization generation for various use cases, data sources, and user group

Towards a uniform user interface for editing data shapes

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Visual analysis of anatomy ontologies and related genomic information

Challenges in scientific research include the difficulty in obtaining overviews of the large amount of data required for analysis, and in resolving the differences in terminology used to store and interpret information in multiple, independently created data sets. Ontologies provide one solution for analysis involving multiple data sources, improving cross-referencing and data integration. This thesis looks at harnessing advanced human perception to reduce the cognitive load in the analysis of the multiple, complex data sets the bioinformatics user group studied use in research, taking advantage also of users’ domain knowledge, to build mental models of data that map to its underlying structure. Guided by a user-centred approach, prototypes were developed to provide a visual method for exploring users’ information requirements and to identify solutions for these requirements. 2D and 3D node-link graphs were built to visualise the hierarchically structured ontology data, to improve analysis of individual and comparison of multiple data sets, by providing overviews of the data, followed by techniques for detailed analysis of regions of interest. Iterative, heuristic and structured user evaluations were used to assess and refine the options developed for the presentation and analysis of the ontology data. The evaluation results confirmed the advantages that visualisation provides over text-based analysis, and also highlighted the advantages of each of 2D and 3D for visual data analysis.Overseas Research Students Awards SchemeJames Watt Scholarshi

On the Mental Workload Assessment of Uplift Mapping Representations in Linked Data

Self-reporting procedures have been largely employed in literature to measure the mental workload experienced by users when executing a specific task. This research proposes the adoption of these mental workload assessment techniques to the task of creating uplift mappings in Linked Data. A user study has been performed to compare the mental workload of “manually” creating such mappings, using a formal mapping language and a text editor, to the use of a visual representation, based on the block metaphor, that generate these mappings. Two subjective mental workload instruments, namely the NASA Task Load Index and the Workload Profile, were applied in this study. Preliminary results show the reliability of these instruments in measuring the perceived mental workload for the task of creating uplift mappings. Results also indicate that participants using the visual representation achieved smaller and more consistent scores of mental workload

Time-Sensitive Ontology Evolution Visualization

With the integration of IoT in the industry, interest has risen regarding predictive approaches to maintenance, in hopes of predicting equipment or system anomalies before they take place. Ontologies, a crucial part of the semantic web, have found a use in these industries, as a way to semantically describe the data related to these equipments and systems. The ontology maintenance process, however, relies heavily on understanding the evolution of knowledge of the domain, over time. Visual representations of these ontologies and their evolution are very useful to ontology engineers (particularly in time-sensitive scenarios), even if tools that offer a service of this kind are fairly limited. Considering this, this dissertation presents a state of the art review of the existing ontology evolution visualization methods and tools, in the context of in time-sensitive scenarios, ending up by choosing to develop the solution using the WebVOWL viewer, React and Fuseki. It then describes the analysis of the requirements for the project, as well as a design proposal for a solution, taking into consideration the need to integrate with an already existing Java back-end application, and that the application must allow for the creation, loading and visualization of an ontology’s evolution. The solution is described in detail, before concluding that it fulfills the requirements proposed at the beginning of the project, and successfully allows for the visualization of the evolutionary process of ontologies.Com a integração da IoT na indústria, o interesse relacionado com manutenção preditiva subiu, com a intenção de prever anomalias em equipamentos ou sistemas antes que estas ocorram. Ontologias, um componente crucial da web semântica, encontraram um uso nestas indústrias, como uma forma de representar semanticamente os dados relacionados com estes equipamentos ou sistemas. Contudo, o processo de manutenção de ontologias depende muito do entendimento da evolução do conhecimento do domínio, ao longo do tempo. A representação visual destas ontologias e da sua evolução são muito úteis para engenheiros de ontologias (especialmente em cenários sensíveis ao tempo), embora ferramentas que ofereçam serviços deste género sejam um pouco limitadas. Considerando isso, esta dissertação apresenta uma análise do estado da arte dos métodos e ferramentas existentes para a visualização da evolução de ontologias, no contexto de cenários sensíveis ao tempo, acabando por selecionar para o desenvolvimento da solução o visualizador WebVOWL, React e Fuseki. Depois, descreve a análise dos requisitos do projeto, bem como a proposta de arquitetura para uma solução, considerando a necessidade de integrar uma aplicação back-end Java já existente, e que a aplicação tem que permitir a criação, carrega mento e visualização da evolução de uma ontologia. A solução é descrita em detalhe, antes de concluir que a mesma cumpre os requisitos propostos na definição do projeto, e é bem sucedido em permitir a visualização do processo evolutivo de ontologias

Supporting Tools for Automated Generation and Visual Editing of Relational-to-Ontology Mappings

La integració de dades amb formats heterogenis i de diversos dominis mitjançant tecnologies de la web semàntica permet solucionar la seva disparitat estructural i semàntica. L'accés a dades basat en ontologies (OBDA, en anglès) és una solució integral que es basa en l'ús d'ontologies com esquemes mediadors i el mapatge entre les dades i les ontologies per facilitar la consulta de les fonts de dades. No obstant això, una de les principals barreres que pot dificultar més l'adopció de OBDA és la manca d'eines per donar suport a la creació de mapatges entre dades i ontologies. L'objectiu d'aquesta investigació ha estat desenvolupar noves eines que permetin als experts sense coneixements d'ontologies la creació de mapatges entre dades i ontologies. Amb aquesta finalitat, s'han dut a terme dues línies de treball: la generació automàtica de mapatges entre dades relacionals i ontologies i l'edició dels mapatges a través de la seva representació visual. Les eines actualment disponibles per automatitzar la generació de mapatges estan lluny de proporcionar una solució completa, ja que es basen en els esquemes relacionals i amb prou feines tenen en compte els continguts de la font de dades relacional i les característiques de l'ontologia. No obstant això, les dades poden contenir relacions ocultes que poden ajudar a la generació de mapatges. Per superar aquesta limitació, hem desenvolupat AutoMap4OBDA, un sistema que genera automàticament mapatges R2RML a partir de l'anàlisi dels continguts de la font relacional i tenint en compte les característiques de l'ontologia. El sistema fa servir una tècnica d'aprenentatge d'ontologies per inferir jerarquies de classes, selecciona les mètriques de similitud de cadenes en base a les etiquetes de les ontologies i analitza les estructures de grafs per generar els mapatges a partir de l'estructura de l'ontologia. La representació visual per mitjà d'interfícies intuïtives pot ajudar els usuaris sense coneixements tècnics a establir mapatges entre una font relacional i una ontologia. No obstant això, les eines existents per a l'edició visual de mapatges mostren algunes limitacions. En particular, la representació visual de mapatges no contempla les estructures de la font relacional i de l'ontologia de forma conjunta. Per superar aquest inconvenient, hem desenvolupat Map-On, un entorn visual web per a l'edició manual de mapatges. AutoMap4OBDA ha demostrat que supera les prestacions de les solucions existents per a la generació de mapatges. Map-On s'ha aplicat en projectes d'investigació per verificar la seva eficàcia en la gestió de mapatges.La integración de datos con formatos heterogéneos y de diversos dominios mediante tecnologías de la Web Semántica permite solventar su disparidad estructural y semántica. El acceso a datos basado en ontologías (OBDA, en inglés) es una solución integral que se basa en el uso de ontologías como esquemas mediadores y mapeos entre los datos y las ontologías para facilitar la consulta de las fuentes de datos. Sin embargo, una de las principales barreras que puede dificultar más la adopción de OBDA es la falta de herramientas para apoyar la creación de mapeos entre datos y ontologías. El objetivo de esta investigación ha sido desarrollar nuevas herramientas que permitan a expertos sin conocimientos de ontologías la creación de mapeos entre datos y ontologías. Con este fin, se han llevado a cabo dos líneas de trabajo: la generación automática de mapeos entre datos relacionales y ontologías y la edición de los mapeos a través de su representación visual. Las herramientas actualmente disponibles para automatizar la generación de mapeos están lejos de proporcionar una solución completa, ya que se basan en los esquemas relacionales y apenas tienen en cuenta los contenidos de la fuente de datos relacional y las características de la ontología. Sin embargo, los datos pueden contener relaciones ocultas que pueden ayudar a la generación de mapeos. Para superar esta limitación, hemos desarrollado AutoMap4OBDA, un sistema que genera automáticamente mapeos R2RML a partir del análisis de los contenidos de la fuente relacional y teniendo en cuenta las características de la ontología. El sistema emplea una técnica de aprendizaje de ontologías para inferir jerarquías de clases, selecciona las métricas de similitud de cadenas en base a las etiquetas de las ontologías y analiza las estructuras de grafos para generar los mapeos a partir de la estructura de la ontología. La representación visual por medio de interfaces intuitivas puede ayudar a los usuarios sin conocimientos técnicos a establecer mapeos entre una fuente relacional y una ontología. Sin embargo, las herramientas existentes para la edición visual de mapeos muestran algunas limitaciones. En particular, la representación de mapeos no contempla las estructuras de la fuente relacional y de la ontología de forma conjunta. Para superar este inconveniente, hemos desarrollado Map-On, un entorno visual web para la edición manual de mapeos. AutoMap4OBDA ha demostrado que supera las prestaciones de las soluciones existentes para la generación de mapeos. Map-On se ha aplicado en proyectos de investigación para verificar su eficacia en la gestión de mapeos.Integration of data from heterogeneous formats and domains based on Semantic Web technologies enables us to solve their structural and semantic heterogeneity. Ontology-based data access (OBDA) is a comprehensive solution which relies on the use of ontologies as mediator schemas and relational-to-ontology mappings to facilitate data source querying. However, one of the greatest obstacles in the adoption of OBDA is the lack of tools to support the creation of mappings between physically stored data and ontologies. The objective of this research has been to develop new tools that allow non-ontology experts to create relational-to-ontology mappings. For this purpose, two lines of work have been carried out: the automated generation of relational-to-ontology mappings, and visual support for mapping editing. The tools currently available to automate the generation of mappings are far from providing a complete solution, since they rely on relational schemas and barely take into account the contents of the relational data source and features of the ontology. However, the data may contain hidden relationships that can help in the process of mapping generation. To overcome this limitation, we have developed AutoMap4OBDA, a system that automatically generates R2RML mappings from the analysis of the contents of the relational source and takes into account the characteristics of ontology. The system employs an ontology learning technique to infer class hierarchies, selects the string similarity metric based on the labels of ontologies, and analyses the graph structures to generate the mappings from the structure of the ontology. The visual representation through intuitive interfaces can help non-technical users to establish mappings between a relational source and an ontology. However, existing tools for visual editing of mappings show somewhat limitations. In particular, the visual representation of mapping does not embrace the structure of the relational source and the ontology at the same time. To overcome this problem, we have developed Map-On, a visual web environment for the manual editing of mappings. AutoMap4OBDA has been shown to outperform existing solutions in the generation of mappings. Map-On has been applied in research projects to verify its effectiveness in managing mappings

Exploring the motivation behind cybersecurity insider threat and proposed research agenda

Cyber exploitation and malicious activities have become more sophisticated. Insider threat is one of the most significant cyber security threat vector, while posing a great concern to corporations and governments. An overview of the fundamental motivating forces and motivation theory are discussed. Such overview is provided to identify motivations that lead trusted employees to become insider threats in the context of cyber security. A research agenda with two sequential experimental research studies are outlined to address the challenge of insider threat mitigation by a prototype development. The first proposed study will classify data intake feeds, as recognized and weighted by cyber security experts, in an effort to establish predictive analytics of novel correlations of activities that may lead to cyber security incidents. It will also develop approach to identify how user activities can be compared against an established baseline, the user’s network cyber security pulse, with visualization of simulated users’ activities. Additionally, the second study will explain the process of assessing the usability of a developed visualization prototype that intends to present correlated suspicious activities requiring immediate action. Successfully developing the proposed prototype via feeds aggregation and an advanced visualization from the proposed research could assist in the mitigation of malicious insider threat