Big Data Analytics for Earth Sciences: the EarthServer approach

Big Data Analytics is an emerging field since massive storage and computing capabilities have been made available by advanced e-infrastructures. Earth and Environmental sciences are likely to benefit from Big Data Analytics techniques supporting the processing of the large number of Earth Observation datasets currently acquired and generated through observations and simulations. However, Earth Science data and applications present specificities in terms of relevance of the geospatial information, wide heterogeneity of data models and formats, and complexity of processing. Therefore, Big Earth Data Analytics requires specifically tailored techniques and tools. The EarthServer Big Earth Data Analytics engine offers a solution for coverage-type datasets, built around a high performance array database technology, and the adoption and enhancement of standards for service interaction (OGC WCS and WCPS). The EarthServer solution, led by the collection of requirements from scientific communities and international initiatives, provides a holistic approach that ranges from query languages and scalability up to mobile access and visualization. The result is demonstrated and validated through the development of lighthouse applications in the Marine, Geology, Atmospheric, Planetary and Cryospheric science domains.

Gestengestützte Schema- und Datenexploration

Der Zugang zu Datenbanken über die universelle Abfragesprache SQL stellt für Nicht-Spezialisten eine große Herausforderung dar. Als eine benutzerfreundliche Alternative wurden daher seit den 1970er-Jahren unterschiedliche visuelle Abfragesprachen (Visual Query Languages, kurz VQLs) für klassische PCs erforscht. Ziel der vorliegenden Arbeit ist es, eine generische VQL zu entwickeln und zu erproben, die eine gestenbasierte Exploration von Datenbanken auf Schema- und Instanzdatenebene für mobile Endgeräte, insbesondere Tablets, ermöglicht. Dafür werden verschiedene Darstellungsformen, Abfragestrategien und visuelle Hints für Fremdschlüsselbeziehungen untersucht, die den Benutzer bei der Navigation durch die Daten unterstützen. Im Rahmen einer Anforderungsanalyse erwies sich die Visualisierung der Daten und Beziehungen mittels einer platzsparenden geschachtelten NF2-Darstellung als besonders vorteilhaft. Zur Steuerung der Datenbankexploration wird eine geeignete Gestensprache, bestehend aus Stroke-, Multitouch- und Mid-Air-Gesten, vorgestellt. Das Gesamtkonzept aus Darstellung und Gestensteuerung wurde anhand des im Rahmen dieser Arbeit entwickelten GBXT-Prototyps auf seine reale Umsetzbarkeit hin, als plattformunabhängige Single-Page-Application für verschiedene mobile Endgeräte mittels JavaScript und HTML5/CSS3 untersucht.

Data mining languages for business intelligence

Doctoral Thesis in Information Systems and Technologies Area of Engineering and Manag ement Information Systems

Comparació entre els llenguatges XQuery del W3C i X-Query de Tamino

Aquest treball de final de carrera vol fer un estudi comparatiu entre el llenguatge XQuery del W3C i el llenguatge X-Query de Tamino, amb una valoració de les possibilitats que ofereix aquest sistema nadiu en el treball amb XML amb relació al llenguatge de consultes sobre XML definit pel W3C.

Applications of graph transformation in tools for domain-specific modeling languages

The use of domain-specific languages (DSLs) has been proposed as an approach to cost-e ectively develop families of software systems in a restricted application domain. Domain-specific languages in combination with the accumulated knowledge and experience of previous implementations, can in turn be used to generate new applications with unique sets of requirements. For this reason, DSLs are considered to be an important approach for software reuse. However, the toolset supporting a particular domain-specific language is also domain-specific and is per definition not reusable. Therefore, creating and maintaining a DSL requires additional resources that could be even larger than the savings associated with using them. As a solution, di erent tool frameworks have been proposed to simplify and reduce the cost of developments of DSLs. Developers of tool support for DSLs need to instantiate, customize or configure the framework for a particular DSL. There are di erent approaches for this. An approach is to use an application programming interface (API) and to extend the basic framework using an imperative programming language. An example of a tools which is based on this approach is Eclipse GEF. Another approach is to configure the framework using declarative languages that are independent of the underlying framework implementation. We believe this second approach can bring important benefits as this brings focus to specifying what should the tool be like instead of writing a program specifying how the tool achieves this functionality. In this thesis we explore this second approach. We use graph transformation as the basic approach to customize a domain-specific modeling (DSM) tool framework. The contributions of this thesis includes a comparison of di erent approaches for defining, representing and interchanging software modeling languages and models and a tool architecture for an open domain-specific modeling framework that e ciently integrates several model transformation components and visual editors. We also present several specific algorithms and tool components for DSM framework. These include an approach for graph query based on region operators and the star operator and an approach for reconciling models and diagrams after executing model transformation programs. We exemplify our approach with two case studies MICAS and EFCO. In these studies we show how our experimental modeling tool framework has been used to define tool environments for domain-specific languages.

A Multilingual Query Processing System using Software Agents

The goal of this work was developing a query processing system using software agents. Open Agent Architecture framework is used for system development. The system supports queries in both Hindi and Malayalam; two prominent regional languages of India. Natural language processing techniques are used for meaning extraction from the plain query and information from database is given back to the user in his native language. The system architecture is designed in a structured way that it can be adapted to other regional languages of India. . This system can be effectively used in application areas like e-governance, agriculture, rural health, education, national resource planning, disaster management, information kiosks etc where people from all walks of life are involved.

Analyzing Query Success and User Context

This paper describes the participation of DAEDALUS at the LogCLEF lab in CLEF 2011. This year, the objectives of our participation are twofold. The first topic is to analyze if there is any measurable effect on the success of the search queries if the native language and the interface language chosen by the user are different. The idea is to determine if this difference may condition the way in which the user interacts with the search application. The second topic is to analyze the user context and his/her interaction with the system in the case of successful queries, to discover out any relation among the user native language, the language of the resource involved and the interaction strategy adopted by the user to find out such resource. Only 6.89% of queries are successful out of the 628,607 queries in the 320,001 sessions with at least one search query in the log. The main conclusion that can be drawn is that, in general for all languages, whether the native language matches the interface language or not does not seem to affect the success rate of the search queries. On the other hand, the analysis of the strategy adopted by users when looking for a particular resource shows that people tend to use the simple search tool, frequently first running short queries build up of just one specific term and then browsing through the results to locate the expected resource

Enabling query technologies for the semantic sensor web

Sensor networks are increasingly being deployed in the environment for many different purposes. The observations that they produce are made available with heterogeneous schemas, vocabularies and data formats, making it difficult to share and reuse this data, for other purposes than those for which they were originally set up. The authors propose an ontology-based approach for providing data access and query capabilities to streaming data sources, allowing users to express their needs at a conceptual level, independent of implementation and language-specific details. In this article, the authors describe the theoretical foundations and technologies that enable exposing semantically enriched sensor metadata, and querying sensor observations through SPARQL extensions, using query rewriting and data translation techniques according to mapping languages, and managing both pull and push delivery modes.

Towards a systematic benchmarking of ontology-based query rewriting systems

Query rewriting is one of the fundamental steps in ontologybased data access (OBDA) approaches. It takes as inputs an ontology and a query written according to that ontology, and produces as an output a set of queries that should be evaluated to account for the inferences that should be considered for that query and ontology. Different query rewriting systems give support to different ontology languages with varying expressiveness, and the rewritten queries obtained as an output do also vary in expressiveness. This heterogeneity has traditionally made it difficult to compare different approaches, and the area lacks in general commonly agreed benchmarks that could be used not only for such comparisons but also for improving OBDA support. In this paper we compile data, dimensions and measurements that have been used to evaluate some of the most recent systems, we analyse and characterise these assets, and provide a unified set of them that could be used as a starting point towards a more systematic benchmarking process for such systems. Finally, we apply this initial benchmark with some of the most relevant OBDA approaches in the state of the art.

Towards a Systematic benchmarking of ontology-based query rewriting systems

Query rewriting is one of the fundamental steps in ontologybased data access (OBDA) approaches. It takes as inputs an ontology and a query written according to that ontology, and produces as an output a set of queries that should be evaluated to account for the inferences that should be considered for that query and ontology. Different query rewriting systems give support to different ontology languages with varying expressiveness, and the rewritten queries obtained as an output do also vary in expressiveness. This heterogeneity has traditionally made it difficult to compare different approaches, and the area lacks in general commonly agreed benchmarks that could be used not only for such comparisons but also for improving OBDA support. In this paper we compile data, dimensions and measurements that have been used to evaluate some of the most recent systems, we analyse and characterise these assets, and provide a unified set of them that could be used as a starting point towards a more systematic benchmarking process for such systems. Finally, we apply this initial benchmark with some of the most relevant OBDA approaches in the state of the art.

Extending the expressiveness of fuzzy logic languages

En el trabajo que aquí presentamos se incluye la base teórica (sintaxis y semántica) y una implementación de un framework para codificar el razonamiento de la representación difusa o borrosa del mundo (tal y como nosotros, seres humanos, entendemos éste). El interés en la realización de éste trabajo parte de dos fuentes: eliminar la complejidad existente cuando se realiza una implementación con un lenguaje de programación de los llamados de propósito general y proporcionar una herramienta lo suficientemente inteligente para dar respuestas de forma constructiva a consultas difusas o borrosas. El framework, RFuzzy, permite codificar reglas y consultas en una sintaxis muy cercana al lenguaje natural usado por los seres humanos para expresar sus pensamientos, pero es bastante más que eso. Permite representar conceptos muy interesantes, como fuzzificaciones (funciones usadas para convertir conceptos no difusos en difusos), valores por defecto (que se usan para devolver resultados un poco menos válidos que los que devolveríamos si tuviésemos la información necesaria para calcular los más válidos), similaridad entre atributos (característica que utilizamos para buscar aquellos individuos en la base de datos con una característica similar a la buscada), sinónimos o antónimos y, además, nos permite extender el numero de conectivas y modificadores (incluyendo modificadores de negación) que podemos usar en las reglas y consultas. La personalización de la definición de conceptos difusos (muy útil para lidiar con el carácter subjetivo de los conceptos borrosos, donde nos encontramos con que cualificar a alguien de “alto” depende de la altura de la persona que cualifica) es otra de las facilidades incluida. Además, RFuzzy implementa la semántica multi-adjunta. El interés en esta reside en que introduce la posibilidad de obtener la credibilidad de una regla a partir de un conjunto de datos y una regla dada y no solo el grado de satisfacción de una regla a partir de el universo modelado en nuestro programa. De esa forma podemos obtener automáticamente la credibilidad de una regla para una determinada situación. Aún cuando la contribución teórica de la tesis es interesante en si misma, especialmente la inclusión del modificador de negacion, sus multiples usos practicos lo son también. Entre los diferentes usos que se han dado al framework destacamos el reconocimiento de emociones, el control de robots, el control granular en computacion paralela/distribuída y las busquedas difusas o borrosas en bases de datos. ABSTRACT In this work we provide a theoretical basis (syntax and semantics) and a practical implementation of a framework for encoding the reasoning and the fuzzy representation of the world (as human beings understand it). The interest for this work comes from two sources: removing the existing complexity when doing it with a general purpose programming language (one developed without focusing in providing special constructions for representing fuzzy information) and providing a tool intelligent enough to answer, in a constructive way, expressive queries over conventional data. The framework, RFuzzy, allows to encode rules and queries in a syntax very close to the natural language used by human beings to express their thoughts, but it is more than that. It allows to encode very interesting concepts, as fuzzifications (functions to easily fuzzify crisp concepts), default values (used for providing results less adequate but still valid when the information needed to provide results is missing), similarity between attributes (used to search for individuals with a characteristic similar to the one we are looking for), synonyms or antonyms and it allows to extend the number of connectives and modifiers (even negation) we can use in the rules. The personalization of the definition of fuzzy concepts (very useful for dealing with the subjective character of fuzziness, in which a concept like tall depends on the height of the person performing the query) is another of the facilities included. Besides, RFuzzy implements the multi-adjoint semantics. The interest in them is that in addition to obtaining the grade of satisfaction of a consequent from a rule, its credibility and the grade of satisfaction of the antecedents we can determine from a set of data how much credibility we must assign to a rule to model the behaviour of the set of data. So, we can determine automatically the credibility of a rule for a particular situation. Although the theoretical contribution is interesting by itself, specially the inclusion of the negation modifier, the practical usage of it is equally important. Between the different uses given to the framework we highlight emotion recognition, robocup control, granularity control in parallel/distributed computing and flexible searches in databases.

Improving cross language information retrieval using corpus based query suggestion approach

Users seeking information may not find relevant information pertaining to their information need in a specific language. But information may be available in a language different from their own, but users may not know that language. Thus users may experience difficulty in accessing the information present in different languages. Since the retrieval process depends on the translation of the user query, there are many issues in getting the right translation of the user query. For a pair of languages chosen by a user, resources, like incomplete dictionary, inaccurate machine translation system may exist. These resources may be insufficient to map the query terms in one language to its equivalent terms in another language. Also for a given query, there might exist multiple correct translations. The underlying corpus evidence may suggest a clue to select a probable set of translations that could eventually perform a better information retrieval. In this paper, we present a cross language information retrieval approach to effectively retrieve information present in a language other than the language of the user query using the corpus driven query suggestion approach. The idea is to utilize the corpus based evidence of one language to improve the retrieval and re-ranking of news documents in the other language. We use FIRE corpora - Tamil and English news collections in our experiments and illustrate the effectiveness of the proposed cross language information retrieval approach.

The user's view level of the GOQL graphical query language

The paper addresses issues related to the design of a graphical query mechanism that can act as an interface to any object-oriented database system (OODBS), in general, and the object model of ODMG 2.0, in particular. In the paper a brief literature survey of related work is given, and an analysis methodology that allows the evaluation of such languages is proposed. Moreover, the user's view level of a new graphical query language, namely GOQL (Graphical Object Query Language), for ODMG 2.0 is presented. The user's view level provides a graphical schema that does not contain any of the perplexing details of an object-oriented database schema, and it also provides a foundation for a graphical interface that can support ad-hoc queries for object-oriented database applications. We illustrate, using an example, the user's view level of GOQL

The impact of spatial data redundancy on SOLAP query performance

Geographic Data Warehouses (GDW) are one of the main technologies used in decision-making processes and spatial analysis, and the literature proposes several conceptual and logical data models for GDW. However, little effort has been focused on studying how spatial data redundancy affects SOLAP (Spatial On-Line Analytical Processing) query performance over GDW. In this paper, we investigate this issue. Firstly, we compare redundant and non-redundant GDW schemas and conclude that redundancy is related to high performance losses. We also analyze the issue of indexing, aiming at improving SOLAP query performance on a redundant GDW. Comparisons of the SB-index approach, the star-join aided by R-tree and the star-join aided by GiST indicate that the SB-index significantly improves the elapsed time in query processing from 25% up to 99% with regard to SOLAP queries defined over the spatial predicates of intersection, enclosure and containment and applied to roll-up and drill-down operations. We also investigate the impact of the increase in data volume on the performance. The increase did not impair the performance of the SB-index, which highly improved the elapsed time in query processing. Performance tests also show that the SB-index is far more compact than the star-join, requiring only a small fraction of at most 0.20% of the volume. Moreover, we propose a specific enhancement of the SB-index to deal with spatial data redundancy. This enhancement improved performance from 80 to 91% for redundant GDW schemas.

A Procedure for Semantic Querying in the Adaptive Formalism

This paper contains a new proposal for the definition of the fundamental operation of query under the Adaptive Formalism, one capable of locating functional nuclei from descriptions of their semantics. To demonstrate the method`s applicability, an implementation of the query procedure constrained to a specific class of devices is shown, and its asymptotic computational complexity is discussed.