Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Bibliographic Control in the Digital Ecosystem

With the contributions of international experts, the book aims to explore the new boundaries of universal bibliographic control. Bibliographic control is radically changing because the bibliographic universe is radically changing: resources, agents, technologies, standards and practices. Among the main topics addressed: library cooperation networks; legal deposit; national bibliographies; new tools and standards (IFLA LRM, RDA, BIBFRAME); authority control and new alliances (Wikidata, Wikibase, Identifiers); new ways of indexing resources (artificial intelligence); institutional repositories; new book supply chain; “discoverability” in the IIIF digital ecosystem; role of thesauri and ontologies in the digital ecosystem; bibliographic control and search engines

Construindo grafos de conhecimento utilizando documentos textuais para análise de literatura científica

Orientador: Julio Cesar dos ReisDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: O número de publicações científicas que pesquisadores tem que ler vem aumento nos últimos anos. Consequentemente, dentre várias opções, é difícil para eles identificarem documentos relevantes relacionados aos seus estudos. Ademais, para entender como um campo científico é organizado, e para estudar o seu estado da arte, pesquisadores geralmente se baseiam em artigos de revisão de uma área. Estes artigos podem estar indisponíveis ou desatualizados dependendo do tema estudado. Usualmente, pesquisadores têm que realizar esta árdua tarefa de pesquisa fundamental manualmente. Pesquisas recentes vêm desenvolvendo mecanismos para auxiliar outros pesquisadores a entender como campos científicos são estruturados. Entretanto, estes mecanismos são focados exclusivamente em recomendar artigos relevantes para os pesquisadores ou os auxiliar em entender como um ramo da ciência é organizado ao nível de publicação. Desta forma, estes métodos limitam o entendimento sobre o ramo estudado, não permitindo que interessados estudem os conceitos e relações abstratas que compõe um ramo da ciência e as suas subáreas. Esta dissertação de mestrado propõe um framework para estruturar, analisar, e rastrear a evolução de um campo científico no nível dos seus conceitos. Ela primeiramente estrutura o campo científico como um grafo-de-conhecimento utilizando os seus conceitos como vértices. A seguir, ela automaticamente identifica as principais subáreas do campo estudado, extrai as suas frases-chave, e estuda as suas relações. Nosso framework representa o campo científico em diferentes períodos do tempo. Esta dissertação compara estas representações, e identifica como as subáreas do campo estudado evoluiram no decorrer dos anos. Avaliamos cada etapa do nosso framework representando e analisando dados científicos provenientes de diferentes áreas de conhecimento em casos de uso. Nossas descobertas indicam o sucesso em detectar resultados similares em diferentes casos de uso, indicando que nossa abordagem é aplicável à diferentes domínios da ciência. Esta pesquisa também contribui com uma aplicação com interface web para auxiliar pesquisadores a utilizarem nosso framework de forma gráfica. Ao utilizar nossa aplicação, pesquisadores podem ter uma análise geral de como um campo científico é estruturado e como ele evoluiAbstract: The amount of publications a researcher must absorb has been increasing over the last years. Consequently, among so many options, it is hard for them to identify interesting documents to read related to their studies. Researchers usually search for review articles to understand how a scientific field is organized and to study its state of the art. This option can be unavailable or outdated depending on the studied area. Usually, they have to do such laborious task of background research manually. Recent researches have developed mechanisms to assist researchers in understanding the structure of scientific fields. However, those mechanisms focus on recommending relevant articles to researchers or supporting them in understanding how a scientific field is organized considering documents that belong to it. These methods limit the field understanding, not allowing researchers to study the underlying concepts and relations that compose a scientific field and its sub-areas. This Ms.c. thesis proposes a framework to structure, analyze, and track the evolution of a scientific field at a concept level. Given a set of textual documents as research papers, it first structures a scientific field as a knowledge graph using its detected concepts as vertices. Then, it automatically identifies the field's main sub-areas, extracts their keyphrases, and studies their relations. Our framework enables to represent the scientific field in distinct time-periods. It allows to compare its representations and identify how the field's areas changed over time. We evaluate each step of our framework representing and analyzing scientific data from distinct fields of knowledge in case studies. Our findings indicate the success in detecting the sub-areas based on the generated graph from natural language documents. We observe similar outcomes in the different case studies by indicating our approach applicable to distinct domains. This research also contributes with a web-based software tool that allows researchers to use the proposed framework graphically. By using our application, researchers can have an overview analysis of how a scientific field is structured and how it evolvedMestradoCiência da ComputaçãoMestre em Ciência da Computação2013/08293-7 ; 2017/02325-5FAPESPCAPE

Information and Communication Technologies in Tourism 2021

This open access book is the proceedings of the International Federation for IT and Travel & Tourism (IFITT)’s 28th Annual International eTourism Conference, which assembles the latest research presented at the ENTER21@yourplace virtual conference January 19–22, 2021. This book advances the current knowledge base of information and communication technologies and tourism in the areas of social media and sharing economy, technology including AI-driven technologies, research related to destination management and innovations, COVID-19 repercussions, and others. Readers will find a wealth of state-of-the-art insights, ideas, and case studies on how information and communication technologies can be applied in travel and tourism as we encounter new opportunities and challenges in an unpredictable world

Machine Learning Algorithm for the Scansion of Old Saxon Poetry

Several scholars designed tools to perform the automatic scansion of poetry in many languages, but none of these tools deal with Old Saxon or Old English. This project aims to be a first attempt to create a tool for these languages. We implemented a Bidirectional Long Short-Term Memory (BiLSTM) model to perform the automatic scansion of Old Saxon and Old English poems. Since this model uses supervised learning, we manually annotated the Heliand manuscript, and we used the resulting corpus as labeled dataset to train the model. The evaluation of the performance of the algorithm reached a 97% for the accuracy and a 99% of weighted average for precision, recall and F1 Score. In addition, we tested the model with some verses from the Old Saxon Genesis and some from The Battle of Brunanburh, and we observed that the model predicted almost all Old Saxon metrical patterns correctly misclassified the majority of the Old English input verses

LIPIcs, Volume 277, GIScience 2023, Complete Volume

LIPIcs, Volume 277, GIScience 2023, Complete Volum

Information knowledge and technology for Development in Africa

Information, knowledge, and technology occupy significant space in the information and knowledge society and ongoing debates on development such as sustainable development goals (SDGs) agenda 2030 and the fourth industrial revolution (4IR). Disruptive technologies and cyber-physical systems, obscuring the lines between the physical, digital and biological, escalated by the COVID-19 pandemic, present a ‘new normal’ that profoundly affects the nature and magnitude of responses required to sustain and benefit from the new developments. Africa, known for late adoption of new technologies and innovations, is leapfrogging development stages in several enviable ways. This book, Information knowledge and technology for development in Africa’, written by eminent African scholars, comprises chapters that satisfactorily address information access, artificial intelligence, information ethics, e-learning, library and information science education (LISE) in the 4IR, data literacy and e-scholarship, and knowledge management, which are increasingly essential for information access, services, and LISE in Africa. We expect the book to support research, teaching and learning in African higher education and worldwide for comparative scholarship