Enhancing Agent Mediated Electronic Markets with Ontology Matching Services and Social Network Support

Os Mercados Eletrónicos atingiram uma complexidade e nível de sofisticação tão elevados, que tornaram inadequados os modelos de software convencionais. Estes mercados são caracterizados por serem abertos, dinâmicos e competitivos, e constituídos por várias entidades independentes e heterogéneas. Tais entidades desempenham os seus papéis de forma autónoma, seguindo os seus objetivos, reagindo às ocorrências do ambiente em que se inserem e interagindo umas com as outras. Esta realidade levou a que existisse por parte da comunidade científica um especial interesse no estudo da negociação automática executada por agentes de software [Zhang et al., 2011]. No entanto, a diversidade dos atores envolvidos pode levar à existência de diferentes conceptualizações das suas necessidades e capacidades dando origem a incompatibilidades semânticas, que podem prejudicar a negociação e impedir a ocorrência de transações que satisfaçam as partes envolvidas. Os novos mercados devem, assim, possuir mecanismos que lhes permitam exibir novas capacidades, nomeadamente a capacidade de auxiliar na comunicação entre os diferentes agentes. Pelo que, é defendido neste trabalho que os mercados devem oferecer serviços de ontologias que permitam facilitar a interoperabilidade entre os agentes. No entanto, os humanos tendem a ser relutantes em aceitar a conceptualização de outros, a não ser que sejam convencidos de que poderão conseguir um bom negócio. Neste contexto, a aplicação e exploração de relações capturadas em redes sociais pode resultar no estabelecimento de relações de confiança entre vendedores e consumidores, e ao mesmo tempo, conduzir a um aumento da eficiência da negociação e consequentemente na satisfação das partes envolvidas. O sistema AEMOS é uma plataforma de comércio eletrónico baseada em agentes que inclui serviços de ontologias, mais especificamente, serviços de alinhamento de ontologias, incluindo a recomendação de possíveis alinhamentos entre as ontologias dos parceiros de negociação. Este sistema inclui também uma componente baseada numa rede social, que é construída aplicando técnicas de análise de redes socias sobre informação recolhida pelo mercado, e que permite melhorar a recomendação de alinhamentos e auxiliar os agentes na sua escolha. Neste trabalho são apresentados o desenvolvimento e implementação do sistema AEMOS, mais concretamente: • É proposto um novo modelo para comércio eletrónico baseado em agentes que disponibiliza serviços de ontologias; • Adicionalmente propõem-se o uso de redes sociais emergentes para captar e explorar informação sobre relações entre os diferentes parceiros de negócio; • É definida e implementada uma componente de serviços de ontologias que é capaz de: • o Sugerir alinhamentos entre ontologias para pares de agentes; • o Traduzir mensagens escritas de acordo com uma ontologia em mensagens escritas de acordo com outra, utilizando alinhamentos previamente aprovados; • o Melhorar os seus próprios serviços recorrendo às funcionalidades disponibilizadas pela componente de redes sociais; • É definida e implementada uma componente de redes sociais que: • o É capaz de construir e gerir um grafo de relações de proximidade entre agentes, e de relações de adequação de alinhamentos a agentes, tendo em conta os perfis, comportamento e interação dos agentes, bem como a cobertura e utilização dos alinhamentos; • o Explora e adapta técnicas e algoritmos de análise de redes sociais às várias fases dos processos do mercado eletrónico. A implementação e experimentação do modelo proposto demonstra como a colaboração entre os diferentes agentes pode ser vantajosa na melhoria do desempenho do sistema e como a inclusão e combinação de serviços de ontologias e redes sociais se reflete na eficiência da negociação de transações e na dinâmica do mercado como um todo.In electronic commerce, the diversity of the involved actors can lead to different conceptualizations of their needs and capabilities, giving rise to semantic incompatibilities that might hamper negotiations and the fulfilling of satisfactory transactions. In order to provide help in conversation among different actors, markets must offer ontology services to facilitate interoperability. However, humans tend to be reluctant to accept others’ conceptualizations, except if they become convinced that a good deal can be achieved. In this context, the application and exploitation of relationships captured by social networks can result in the establishment of more accurate trust relationships between businesses and customers, as well as the improvement of the negotiation efficiency and therefore the users’ satisfaction with the electronic commerce system. The AEMOS system is an agent-based electronic commerce platform that provides ontology matching services in order to facilitate the interoperability between agents that use different ontologies. AEMOS also includes a social network component that allows improving the ontology alignment recommendations and supporting the agents’ decisions about which alignments to select based on the information collected throughout the market and by exploring social network analysis techniques. This work presents the development and implementation of the AEMOS system, illustrating how the collaboration between the different agents can be helpful in improving the system’s performance, and how the inclusion and combination of ontology services and social networks reflects in the efficiency of the negotiation process

System learning in complex and emergent environments: A study of how leaders in one education system enabled capacity for learning focused on the enactment of moral purpose

This thesis explores system capacity building, in particular, the purpose of system capacity building and how leaders, in the context of Leading for Learning Project, enabled whole of system capacity building with a focus on sustained engagement with moral purpose. It is argued, however, that the purpose and scope of system capacity building is often conceptually limited because it is understood within the current regulatory and performance focused education reform environment. This thesis, therefore, offers an alternative perspective by engaging with the theoretical underpinnings of complexity theory. As such, this thesis offers a conceptualisation of education systems as complex adaptive systems and system capacity building as a complex and emergent process. The thesis presents a radical reframing of education systems arguing that education systems are better understood as open, dynamic, and emergent systems, constituted of many interdependent relationships throughout the system

Entrepreneurship as nexus of change: the syncretistic production of the future

This paper deals with the issue of how the future is created and the mechanisms through which it is produced and conceived. Key to this process appears to be social interaction and how it is used to bring about change. Examining the entrepreneurial context by qualitative longitudinal research techniques, the study considers the situations of three entrepreneurs. It demonstrates that the web of relationships in which individuals are engaged provide the opportunity to enact the environment in new ways, thus producing organizations for the future. It further provides empirical evidence for a Heideggerian reading of strategy-as-practice, extending this conceptualization to account for the temporal dimension

Knowledge Extraction from Textual Resources through Semantic Web Tools and Advanced Machine Learning Algorithms for Applications in Various Domains

Nowadays there is a tremendous amount of unstructured data, often represented by texts, which is created and stored in variety of forms in many domains such as patients' health records, social networks comments, scientific publications, and so on. This volume of data represents an invaluable source of knowledge, but unfortunately it is challenging its mining for machines. At the same time, novel tools as well as advanced methodologies have been introduced in several domains, improving the efficacy and the efficiency of data-based services. Following this trend, this thesis shows how to parse data from text with Semantic Web based tools, feed data into Machine Learning methodologies, and produce services or resources to facilitate the execution of some tasks. More precisely, the use of Semantic Web technologies powered by Machine Learning algorithms has been investigated in the Healthcare and E-Learning domains through not yet experimented methodologies. Furthermore, this thesis investigates the use of some state-of-the-art tools to move data from texts to graphs for representing the knowledge contained in scientific literature. Finally, the use of a Semantic Web ontology and novel heuristics to detect insights from biological data in form of graph are presented. The thesis contributes to the scientific literature in terms of results and resources. Most of the material presented in this thesis derives from research papers published in international journals or conference proceedings

Exploring leaders\u27 sensemaking of emergent global norms for open science: a mixed methods discourse analysis of UNESCO’s multistakeholder initiative

In November 2021, all 193 United Nations Member States adopted the United Nations Educational, Scientific, and Cultural Organization’s (UNESCO) Recommendation on Open Science (UNESCO, 2021a), which signaled a shared commitment to globally recognized standards for open science. However, as with other normative instruments established by intergovernmental organizations (IGOs) such as UNESCO, the ways in which local, national, and regional leaders will implement the recommendation can and will vary (Finnemore, 1993). Top-down and bottom-up coordination across international stakeholders in the research system is critical for the framework to be effective in driving global policy implementation and enabling sustained research culture change. Such international coordination necessitates an understanding of the complex economic, socio-political, and cultural dimensions that exist among these stakeholders and may influence local implementation efforts and norm-setting (Martinsson, 2011; Nilsson, 2017). This mixed methods study explores leaders’ sensemaking of emergent global norms for open science through public discourse during the development of UNESCO’s recommendation. The central research question is: How did institutional leaders make sense of emergent global norms for open science during UNESCO’s multistakeholder initiative? The study is situated at the intersection of systems thinking, global norms, and sensemaking, using a social constructionist lens. A synthesis of study findings draws two conclusions: That there is evidence in the discourse of accelerating self-organization toward open science among Member States who responded to UNESCO’s call for commentary on the draft recommendation; and that there is also evidence in the discourse of a degree of instability around prospective norm diffusion and internalization of the Recommendation on Open Science (2021a) related directly to matters of implementation. The tension between emergence and instability is well documented throughout the literature across complex systems, global norms, and sensemaking. Therefore, the study supports the ongoing exploration of global norms development and, specifically, the critical progression from norm emergence to norm diffusion. Given the theoretical coherence of complex systems, global norms, and sensemaking as evidenced throughout the findings, the novel integrative analytic frame that was developed during the design of this study may support other global norms development studies

Semantically-enhanced recommendations in cultural heritage

In the Web 2.0 environment, institutes and organizations are starting to open up their previously isolated and heterogeneous collections in order to provide visitors with maximal access. Semantic Web technologies act as instrumental in integrating these rich collections of metadata by defining ontologies which accommodate different representation schemata and inconsistent naming conventions over the various vocabularies. Facing the large amount of metadata with complex semantic structures, it is becoming more and more important to support visitors with a proper selection and presentation of information. In this context, the Dutch Science Foundation (NWO) funded the Cultural Heritage Information Personalization (CHIP) project in early 2005, as part of the Continuous Access to Cultural Heritage (CATCH) program in the Netherlands. It is a collaborative project between the Rijksmuseum Amsterdam, the Eindhoven University of Technology and the Telematica Instituut. The problem statement that guides the research of this thesis is as follows: Can we support visitors with personalized access to semantically-enriched collections? To study this question, we chose cultural heritage (museums) as an application domain, and the semantically rich background knowledge about the museum collection provides a basis to our research. On top of it, we deployed user modeling and recommendation technologies in order to provide personalized services for museum visitors. Our main contributions are: (i) we developed an interactive rating dialog of artworks and art concepts for a quick instantiation of the CHIP user model, which is built as a specialization of FOAF and mapped to an existing event model ontology SEM; (ii) we proposed a hybrid recommendation algorithm, combining both explicit and implicit relations from the semantic structure of the collection. On the presentation level, we developed three tools for end-users: Art Recommender, Tour Wizard and Mobile Tour Guide. Following a user-centered design cycle, we performed a series of evaluations with museum visitors to test the effectiveness of recommendations using the rating dialog, different ways to build an optimal user model and the prediction accuracy of the hybrid algorithm. Chapter 1 introduces the research questions, our approaches and the outline of this thesis. Chapter 2 gives an overview of our work at the first stage. It includes (i) the semantic enrichment of the Rijksmuseum collection, which is mapped to three Getty vocabularies (ULAN, AAT, TGN) and the Iconclass thesaurus; (ii) the minimal user model ontology defined as a specialization of FOAF, which only stores user ratings at that time, (iii) the first implementation of the content-based recommendation algorithm in our first tool, the CHIP Art Recommender. Chapter 3 presents two other tools: Tour Wizard and Mobile Tour Guide. Based on the user's ratings, the Web-based Tour Wizard recommends museum tours consisting of recommended artworks that are currently available for museum exhibitions. The Mobile Tour Guide converts recommended tours to mobile devices (e.g. PDA) that can be used in the physical museum space. To connect users' various interactions with these tools, we made a conversion of the online user model stored in RDF into XML format which the mobile guide can parse, and in this way we keep the online and on-site user models dynamically synchronized. Chapter 4 presents the second generation of the Mobile Tour Guide with a real time routing system on different mobile devices (e.g. iPod). Compared with the first generation, it can adapt museum tours based on the user's ratings artworks and concepts, her/his current location in the physical museum and the coordinates of the artworks and rooms in the museum. In addition, we mapped the CHIP user model to an existing event model ontology SEM. Besides ratings, it can store additional user activities, such as following a tour and viewing artworks. Chapter 5 identifies a number of semantic relations within one vocabulary (e.g. a concept has a broader/narrower concept) and across multiple vocabularies (e.g. an artist is associated to an art style). We applied all these relations as well as the basic artwork features in content-based recommendations and compared all of them in terms of usefulness. This investigation also enables us to look at the combined use of artwork features and semantic relations in sequence and derive user navigation patterns. Chapter 6 defines the task of personalized recommendations and decomposes the task into a number of inference steps for ontology-based recommender systems, from a perspective of knowledge engineering. We proposed a hybrid approach combining both explicit and implicit recommendations. The explicit relations include artworks features and semantic relations with preliminary weights which are derived from the evaluation in Chapter 5. The implicit relations are built between art concepts based on instance-based ontology matching. Chapter 7 gives an example of reusing user interaction data generated by one application into another one for providing cross-application recommendations. In this example, user tagging about cultural events, gathered by iCITY, is used to enrich the user model for generating content-based recommendations in the CHIP Art Recommender. To realize full tagging interoperability, we investigated the problems that arise in mapping user tags to domain ontologies, and proposed additional mechanisms, such as the use of SKOS matching operators to deal with the possible mis-alignment of tags and domain-specific ontologies. We summarized to what extent the problem statement and each of the research questions are answered in Chapter 8. We also discussed a number of limitations in our research and looked ahead at what may follow as future work

A Living Educational Theory of Knowledge Translation: Improving Practice, Influencing Learners, and Contributing to the Professional Knowledge Base

This paper captured our joint journey to create a living educational theory of knowledge translation (KT). The failure to translate research knowledge to practice is identified as a significant issue in the nursing profession. Our research story takes a critical view of KT related to the philosophical inconsistency between what is espoused in the knowledge related to the discipline of nursing and what is done in practice. Our inquiry revealed “us” as “living contradictions” as our practice was not aligned with our values. In this study, we specifically explored our unique personal KT process in order to understand the many challenges and barriers to KT we encountered in our professional practice as nurse educators. Our unique collaborative action research approach involved cycles of action, reflection, and revision which used our values as standards of judgment in an effort to practice authentically. Our data analysis revealed key elements of collaborative reflective dialogue that evoke multiple ways of knowing, inspire authenticity, and improve learning as the basis of improving practice related to KT. We validated our findings through personal and social validation procedures. Our contribution to a culture of inquiry allowed for co-construction of knowledge to reframe our understanding of KT as a holistic, active process which reflects the essence of who we are and what we do

Evaluating Ethical Technology Leadership: Organizational Culture, Leader Behavior, and a Cyberspace Ethic of Business

Evaluating ethical technology leadership at a financial services firm in North Carolina requires discovering interactions amongst organizational culture, leadership approaches, and ethical decision-making practices. This study provides insight into how the participating firm’s organizational culture creates a leadership climate accommodative of an applied cyberspace business ethic. A cyberspace business ethic provides guidance to technology leaders addressing ethical challenges arising from emergent digital technologies. The identification of four key influencers that support ethical decision-making and provide protection against reputational risk exposures create an understanding of the collective nature of core values, relational, reputational, and technological influences on ethical behaviors. Self-determination theory assists in understanding the motivations for ethical leader behavior in the form of competency, autonomy, and relatedness. Coupling this theoretical knowledge with identification of the four influencers of ethical decision-making provides the basis of understanding the participating firm’s applied cyberspace business ethic. Given the rapid pace of emerging digital technology deployment, a dynamic condition of internal environmental complexity and external environmental uncertainty creates the need for leaders to develop a cyberspace business ethic appropriate for the business context. The participating firm’s cyberspace business ethic centers on core values, transparency, and communication clarity, purposefully utilized to mitigate reputational risk. Applying a Christian worldview to study findings adds a theological construct to organizational core values and underlying virtue ethics

Linked democracy : foundations, tools, and applications

Chapter 1Introduction to Linked DataAbstractThis chapter presents Linked Data, a new form of distributed data on theweb which is especially suitable to be manipulated by machines and to shareknowledge. By adopting the linked data publication paradigm, anybody can publishdata on the web, relate it to data resources published by others and run artificialintelligence algorithms in a smooth manner. Open linked data resources maydemocratize the future access to knowledge by the mass of internet users, eitherdirectly or mediated through algorithms. Governments have enthusiasticallyadopted these ideas, which is in harmony with the broader open data movement