Ontologies tend to be found everywhere. They are viewed as the silver bullet for many applications, such as database integration, peer-to-peer systems, e-commerce, semantic web services, or social networks. However, in open or evolving systems, such as the semantic web, different parties would, in general, adopt different ontologies. Thus, merely using ontologies, like using XML, does not reduce heterogeneity: it just raises heterogeneity problems to a higher level. Euzenat and Shvaikos book is devoted to ontology matching as a solution to the semantic heterogeneity problem faced by computer systems. Ontology matching aims at finding correspondences between semantically related entities of different ontologies. These correspondences may stand for equivalence as well as other relations, such as consequence, subsumption, or disjointness, between ontology entities. Many different matching solutions have been proposed so far from various viewpoints, e.g., databases, information systems, and artificial intelligence. The second edition of Ontology Matching has been thoroughly revised and updated to reflect the most recent advances in this quickly developing area, which resulted in more than 150 pages of new content. In particular, the book includes a new chapter dedicated to the methodology for performing ontology matching. It also covers emerging topics, such as data interlinking, ontology partitioning and pruning, context-based matching, matcher tuning, alignment debugging, and user involvement in matching, to mention a few. More than 100 state-of-the-art matching systems and frameworks were reviewed. With Ontology Matching, researchers and practitioners will find a reference book that presents currently available work in a uniform framework. In particular, the work and the techniques presented in this book can be equally applied to database schema matching, catalog integration, XML schema matching and other related problems. The objectives of the book include presenting (i) the state of the art and (ii) the latest research results in ontology matching by providing a systematic and detailed account of matching techniques and matching systems from theoretical, practical and application perspectives.

Ontology Matching

Understanding, management and modelling of urban hydrology and its consequences for receiving waters: A state of the art

This paper introduces a framework for using Game Theory tournaments as a base to implement Competition-based Learning (CnBL), together with other classical learning techniques, to motivate the students and increase their learning performance. The paper also presents a description of the learning activities performed along the past ten years of a course where, in five of them, Competition-based Learning has been used. Finally, the experience gained is described together with an analysis of the feedback obtained from the students' surveys. The good survey results, and their similarity along the years, suggest that the combination of game theory with the use of friendly competitions provides a strong motivation for students; helping to increase their performance.

Using game theory and Competition-based Learning to stimulate student motivation and performance

Bandit Problems, Sequential Allocation of Experiments

(1997). Multiple Comparisons: Theory and Methods. Journal of Quality Technology: Vol. 29, No. 3, pp. 359-359.

Multiple Comparisons: Theory and Methods

A motivated student is more likely to be a successful learner. Interesting assignments encourage student learning by actively engaging them in the material. Active student learning is especially important in an introductory data structures course where students learn the fundamentals of programming. In this paper, the author describes a project for a data structures course based on the idea of competitive programming. Competitive programming motivates student learning by allowing students to evaluate and improve their programs throughout an assignment by competing their code against instructor-defined code and the code of other students in a tournament environment. Pedagogical results indicate that the combination of game development and friendly student competition is a significant motivator for increased student performance.

/pdf/teaching-data-structures-using-competitive-games-sqveleoeef.pdf

Teaching data structures using competitive games

NoSQL databases are growing in popularity for Big Data applications in web analytics and supporting large web sites due to their high availability and scalability. Since each NoSQL system has its own API and does not typically support standards such as SQL and JDBC, integrating these systems with other enterprise and reporting software requires extra effort. In this work, we present a generic standards-based architecture that allows NoSQL systems, with specific focus on MongoDB, to be queried using SQL and seamlessly interact with any software supporting JDBC. A virtualization system is built on top of the NoSQL sources that translates SQL queries into the source-specific APIs. The virtualization architecture allows users to query and join data from both NoSQL and relational SQL systems in a single SQL query. Experimental results demonstrate that the virtualization layer adds minimal overhead in translating SQL to NoSQL APIs, and the virtualization system can efficiently perform joins across sources.

/pdf/integration-and-virtualization-of-relational-sql-and-nosql-4u1lhyuj3k.pdf

Integration and Virtualization of Relational SQL and NoSQL Systems Including MySQL and MongoDB

Adaptive and sequential experiment design is a well-studied area in numerous domains. We survey and synthesize the work of the online statistical learning paradigm referred to as multi-armed bandits integrating the existing research as a resource for a certain class of online experiments. We first explore the traditional stochastic model of a multi-armed bandit, then explore a taxonomic scheme of complications to that model, for each complication relating it to a specific requirement or consideration of the experiment design context. Finally, at the end of the paper, we present a table of known upper-bounds of regret for all studied algorithms providing both perspectives for future theoretical work and a decision-making tool for practitioners looking for theoretical guarantees.

A Survey of Online Experiment Design with the Stochastic Multi-Armed Bandit

With a very modest investment in computer hardware and the open-source local data manager (LDM) software from University Corporation for Atmospheric Research (UCAR) Unidata Program Center, a researcher can receive a variety of NEXRAD Level III rainfall products and the unprocessed Level II data in real-time from most NEXRAD radars in the USA. Alternatively, one can receive such data from the National Climatic Data Center in Ashville, NC. Still, significant obstacles remain in order to unlock the full potential of the data. One set of obstacles is related to effective management of multi-terabyte datasets. A second set of obstacles, for hydrologists and hydrometeorologists in particular, is that the NEXRAD Level III products are not well suited for applications in hydrology. There is a strong need for the generation of high-quality products directly from the Level II data with well-documented steps that include quality control, removal of false echoes, rainfall estimation algorithms, coordinate conversion, georeferencing and integration with GIS. For hydrologists it is imperative that these procedures are basin-centered as opposed to radar-centered. The authors describe the Hydro-NEXRAD system that addresses the above challenges. With support from the National Science Foundation through its ITR program, the authors have developed a basin-centered framework for addressing all these issues in a comprehensive manner, tailored specifically for use of NEXRAD data in hydrology and hydrometeorology.

/pdf/towards-better-utilization-of-nexrad-data-in-hydrology-an-4ti2kz4emo.pdf

Towards better utilization of NEXRAD data in hydrology: an overview of Hydro-NEXRAD

Schema integration requires the resolution of naming, structural, and semantic conflicts Currently, automatic schema integration is not possible We propose that integration can be increasingly automated by capturing data semantics using a standardized dictionary Our integration architecture constructs an integrated view by automatically combining local views defined by independently expressing database semantics in XML documents using only a pre-defined dictionary as a binding between integration sites The dictionary eliminates naming conflicts and reduces semantic conflicts Structural conflicts are resolved at query-time by a query processor which translates from the semantic integrated view to structural queries Thus, the system provides both logical and physical access transparency by mapping user queries on high-level concepts to schema elements in the underlying data sources The architecture automatically integrates and transparently queries relational data sources, and its application of standardization to the integration problem is unique

https://people.ok.ubc.ca/rlawrenc/research/Papers/schint.pdf

Ramon Lawrence

Papers

Teaching data structures using competitive games

Integration and Virtualization of Relational SQL and NoSQL Systems Including MySQL and MongoDB

A Survey of Online Experiment Design with the Stochastic Multi-Armed Bandit

Towards better utilization of NEXRAD data in hydrology: an overview of Hydro-NEXRAD

Integrating relational database schemas using a standardized dictionary