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How to be FAIR with Your Data
This handbook was written and edited by a group of about 40 collaborators in a series of six book sprints that took place between 1 and 10 June 2021. It aims to support higher education institutions with the practical implementation of content relating to the FAIR principles in their curricula, while also aiding teaching by providing practical material, such as competence profiles, learning outcomes, lesson plans, and supporting information. It incorporates community feedback received during the public consultation which ran from 27 July to 12 September 2021.
Beyond the Flow
In the wake of the so-called digital revolution numerous attempts have been made to rethink and redesign what scholarly publications can or should be. Beyond the Flow examines the technologies as well as narratives driving this unfolding transformation. However, facing challenges such as the serial crisis, knowledge burying or sudoku research the discourses and practices of scholarly publishing today are mainly shaped by confusion, heterogeneity and uncertainty. By critically interrogating the current state of digital publishing in academia the book asks for how a sustainable post-digital publishing ecology can be imagined.
Semantic Web Evaluation Challenge
This book constitutes the thoroughly refereed post conference proceedings of the first edition of the Semantic Web Evaluation Challenge, SemWebEval 2014, co-located with the 11th Extended Semantic Web conference, held in Anissaras, Crete, Greece, in May 2014. This book includes the descriptions of all methods and tools that competed at SemWebEval 2014, together with a detailed description of the tasks, evaluation procedures and datasets. The contributions are grouped in three areas: semantic publishing (sempub), concept-level sentiment analysis (ssa), and linked-data enabled recommender systems (recsys).
Machine Learning and Knowledge Extraction
This book constitutes the refereed proceedings of the IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2017, held in Reggio, Italy, in August/September 2017. The 24 revised full papers presented were carefully reviewed and selected for inclusion in this volume. The papers deal with fundamental questions and theoretical aspects and cover a wide range of topics in the field of machine learning and knowledge extraction. They are organized in the following topical sections: MAKE topology; MAKE smart factory; MAKE privacy; MAKE VIS; MAKE AAL; and MAKE semantics.
Toxicogenomics-Based Cellular Models
Toxicogenomics-Based Cellular Models is a unique and valuable reference for all academic and professional researchers employing toxicogenomic methods with respect to animal testing for chemical safety. This resource offers cutting-edge information on the application of toxicogenomics to developing alternatives to current animal toxicity tests. By illustrating the development of toxicogenomics-based cellular models for critical endpoints of toxicity and providing real-world examples for validation and data analysis, this book provides an assessment of the current state of the field, as well as opportunities and challenges for the future. Written by renowned international toxicological experts...
Interactive Knowledge Discovery and Data Mining in Biomedical Informatics
One of the grand challenges in our digital world are the large, complex and often weakly structured data sets, and massive amounts of unstructured information. This “big data” challenge is most evident in biomedical informatics: the trend towards precision medicine has resulted in an explosion in the amount of generated biomedical data sets. Despite the fact that human experts are very good at pattern recognition in dimensions of = 3; most of the data is high-dimensional, which makes manual analysis often impossible and neither the medical doctor nor the biomedical researcher can memorize all these facts. A synergistic combination of methodologies and approaches of two fields offer ideal...
Model-Driven Organizational and Business Agility
This book constitutes the proceedings of the Second International Workshop on Model-Driven Organizational and Business Agility, MOBA 2022, which took place in Leuven, Belgium, in June 2022. MOBA was launched with the purpose of fetching scientific rigor into the agile practice within an entire enterprise, especially focusing on the role of models and modeling. The 10 papers presented in this volume were carefully reviewed and selected from 22 submissions. They cover topics like business intelligence, agile business rules, agile software development, adaptive domain-specific interfaces, or reconfigurable software architectures.
Advanced Information Systems Engineering Workshops
This book constitutes the thoroughly refereed proceedings of the international workshops associated with the 33rd International Conference on Advanced Information Systems Engineering, CAiSE 2021, which was held during June 28-July 2, 2021. The conference was planned to take place in Melbourne, Australia, but changed to an online format due to the COVID-19 pandemic. The workshops included in this volume are: · BC4IS: 1st International Workshop on Blockchain for Information Systems · EMoBI : 3rd International Workshop on Ethics and Morality in Business Informatics · KET4DF : 3rd International Workshop on Key Enabling Technology for Digital Factories · MOBA: 1st International Workshop on Model-driven Organizational and Business Agility · NeGIS: 2nd International Workshop on Next Generation Information Systems They focus on topics and trends ranging from blockchain technologies to digital factories, ethics, and business agility to the next generation of information systems. The 14 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 33 submissions.
Telehealth Ecosystems in Practice
Telemedicine is a term which covers all remotely-provided health services. It removes the obstacle of distance and can equalize access to care by means of technology. Telemedicine assumed increased importance during the time of pandemic restrictions, but despite increased interest, progress has been slowed by factors such as cost, lack of privacy legislation, the reluctance of elderly patients to use ICT, and a lack of qualified actors. It remains, however, one of the best solutions to the problems of different levels of healthcare provision and health outcomes across regions. This book presents the proceedings of STC2023, a Special Topic Conference (STC) organized by the European Federation...
Machine Learning for Health Informatics
Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds, it is aimed to support human intelligence with machine intelligence. This state-of-the-art survey is an output of the international HCI-KDD expert network and features 22 carefully selected and peer-reviewed chapters on hot topics in machine learning for health informatics; they discuss open problems and future challenges in order to stimulate further research and international progress in this field.
