Policy-based data management enables the creation of community-specific collections. Every collection is created for a purpose. The purpose defines the set of properties that will be associated with the collection. The properties are enforced by management policies that control the execution of procedures that are applied whenever data are ingested or accessed. The procedures generate state information that defines the outcome of enforcing the management policy. The state information can be queried to validate assessment criteria and verify that the required collection properties have been conserved. The integrated Rule-Oriented Data System implements the data management framework required to support policy-based data management. Policies are turned into computer actionable Rules. Procedures are composed from a Micro-service-oriented architecture. The result is a highly extensible and tunable system that can enforce management policies, automate administrative tasks, and periodically validate assessment criteria. Table of Contents: Introduction / Integrated Rule-Oriented Data System / iRODS Architecture / Rule-Oriented Programming / The iRODS Rule System / iRODS Micro-services / Example Rules / Extending iRODS / Appendix A: iRODS Shell Commands / Appendix B: Rulegen Grammar / Appendix C: Exercises / Author Biographies
HPC, Big Data, AI Convergence Towards Exascale provides an updated vision on the most advanced computing, storage, and interconnection technologies, that are at basis of convergence among the HPC, Cloud, Big Data, and artificial intelligence (AI) domains. Through the presentation of the solutions devised within recently founded H2020 European projects, this book provides an insight on challenges faced by integrating such technologies and in achieving performance and energy efficiency targets towards the exascale level. Emphasis is given to innovative ways of provisioning and managing resources, as well as monitoring their usage. Industrial and scientific use cases give to the reader practical examples of the needs for a cross-domain convergence. All the chapters in this book pave the road to new generation of technologies, support their development and, in addition, verify them on real-world problems. The readers will find this book useful because it provides an overview of currently available technologies that fit with the concept of unified Cloud-HPC-Big Data-AI applications and presents examples of their actual use in scientific and industrial applications.
This book constitutes the refereed proceedings of the 7th Metadata and Semantics Research Conference, MTSR 2013, held in Thessaloniki, Greece, in November 2013. The 29 revised papers presented were carefully reviewed and selected from 89 submissions. The papers are organized in several sessions and tracks. The sessions cover the following topics: platforms for research datasets, system architecture and data management; metadata and ontology validation, evaluation, mapping and interoperability; content management. The tracks cover the following topics: big data and digital libraries in health, science and technology; European and national projects and project networking; metadata and semantics for open repositories, research information systems and data infrastructures; metadata and semantics for cultural collections and applications; metadata and semantics for agriculture, food and environment.
A trustworthy repository provides assurance in the form of management documents, event logs, and audit trails that digital objects are being managed correctly. The assurance includes plans for the sustainability of the repository, the accession of digital records, the management of technology evolution, and the mitigation of the risk of data loss. A detailed assessment is provided by the ISO-16363:2012 standard, "Space data and information transfer systems—Audit and certification of trustworthy digital repositories." This book examines whether the ISO specification for trustworthiness can be enforced by computer actionable policies. An implementation of the policies is provided and the policies are sorted into categories for procedures to manage externally generated documents, specify repository parameters, specify preservation metadata attributes, specify audit mechanisms for all preservation actions, specify control of preservation operations, and control preservation properties as technology evolves. An application of the resulting procedures is made to enforce trustworthiness within National Science Foundation data management plans.
This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part "Technologies and Methods" contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part "Processes and Applications" details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems.
This book constitutes the refereed proceedings of the 7th International RuleML Symposium, RuleML 2013, held in Seattle, WA, USA, in July 2013 - collocated with the 27th AAAI 2013. The 22 full papers,12 technical papers in main track, 3 technical papers in human language technology track, and 4 tutorials presented together with 3 invited talks were carefully reviewed and selected from numerous submissions. The accepted papers address topics such as rule-based programming and rule-based systems including production rules systems, logic programming rule engines, and business rules engines/business rules management systems; Semantic Web rule languages and rule standards; rule-based event processing languages (EPLs) and technologies; and research on inference rules, transformation rules, decision rules, production rules, and ECA rules.
This book constitutes the refereed proceedings of the 4th International Conference on Information Technology in Bio- and Medical Informatics, ITBAM 2013, held in Prague, Czech Republic, in August 2013, held in conjunction with DEXA 2013. The 7 revised long papers presented together with 4 short papers were carefully reviewed and selected from numerous submissions. The papers address the following topics: critical health and intelligent systems in medical research, and obstetrics, neonatology and decision systems in cardiology.
The study of people, information and communication technologies and the contexts in which these technologies are designed, implemented and used has long interested scholars in a wide range of disciplines, including the social study of computing, science and technology studies, the sociology of technology, and management information systems. As ICT use has spread from organizations into the larger world, these devices have become routine information appliances in our social lives, researchers have begun to ask deeper and more profound questions about how our lives have become bound up with technologies. A common theme running through this research is that the relationships among people, technology and context are dynamic, complex and critically important to understand. This synthesis lecture explores social informatics (SI), one important and dynamic approach that researchers have used to study these complex relationships. SI is "the interdisciplinary study of the design, uses and consequences of information technology that takes into account their interaction with institutional and cultural contexts" (Kling 1998, p.52; 1999). SI provides flexible frameworks to explore complex and dynamic sociotechnical interactions. As a domain of study related largely by common vocabulary and conclusions, SI critically examines common conceptions of and expectations for technology, by providing contextual evidence. This synthesis describes the evolution of SI research and identifies challenges and opportunities for future research. In what might be seen as an example of sociotechnical "natural selection", SI emerged in six different locations during the 1980s and 1990s: Norway, Slovenia, Japan, the former Soviet Union, the UK and, last, the US. As SI evolved, the version popularized in the US became globally dominant. The evolution of SI is presented in five stages: emergence, foundational, expansion, coherence, and transformation. Thus, we divide SI research into five major periods: an emergence stage, when various forms of SI emerged around the globe, an early period of foundational work which grounds SI (Pre-1990s), a period of expansion (1990s), a robust period of coherence and influence by Rob Kling (2000-2005) , and a period of transformation (2006-Present). Following the description of the five periods we discuss the evolution throughout the periods under five sections: principles, concepts, approaches, topics, and findings. Principles refer to the overarching motivations and labels employed to describe scholarly work. Approaches describe the theories, frameworks, and models employed in analysis, emphasizing the multi-disciplinary and interdisciplinary nature of SI. Concepts include specific processes, entities, themes, and elements of discourse within a given context, revealing a shared SI language surrounding change, complexity, consequences, and social elements of technology. Topics label the issues and general domains studied within social informatics, ranging from scholarly communication to online communities to information systems. Findings from seminal SI works illustrate growing insights over time and demonstrate how repeatable explanations unify SI. In the concluding remarks, we raise questions about the possible futures of SI research.
We are poised at a major turning point in the history of information management via computers. Recent evolutions in computing, communications, and commerce are fundamentally reshaping the ways in which we humans interact with information, and generating enormous volumes of electronic data along the way. As a result of these forces, what will data management technologies, and their supporting software and system architectures, look like in ten years? It is difficult to say, but we can see the future taking shape now in a new generation of information access platforms that combine strategies and structures of two familiar -- and previously quite distinct -- technologies, search engines and databases, and in a new model for software applications, the Search-Based Application (SBA), which offers a pragmatic way to solve both well-known and emerging information management challenges as of now. Search engines are the world's most familiar and widely deployed information access tool, used by hundreds of millions of people every day to locate information on the Web, but few are aware they can now also be used to provide precise, multidimensional information access and analysis that is hard to distinguish from current database applications, yet endowed with the usability and massive scalability of Web search. In this book, we hope to introduce Search Based Applications to a wider audience, using real case studies to show how this flexible technology can be used to intelligently aggregate large volumes of unstructured data (like Web pages) and structured data (like database content), and to make that data available in a highly contextual, quasi real-time manner to a wide base of users for a varied range of purposes. We also hope to shed light on the general convergences underway in search and database disciplines, convergences that make SBAs possible, and which serve as harbingers of information management paradigms and technologies to come. Table of Contents: Search Based Applications / Evolving Business Information Access Needs / Origins and Histories / Data Models and Storage / Data Collection/Population / Data Processing / Data Retrieval / Data Security, Usability, Performance, Cost / Summary Evolutions and Convergences / SBA Platforms / SBA Uses and Preconditions / Anatomy of a Search Based Application / Case Study: GEFCO / Case Study: Urbanizer / Case Study: National Postal Agency / Future Directions
