The Structured Query Language (SQL) is widely used and challenging to master. Within the context of lab exercises in an introductory database course, this thesis analyzes the student learning process and seeks to answer the question: ``Which SQL concepts, or concept combinations, trouble students the most?'' We provide comprehensive taxonomies of SQL concepts and errors, identify common areas of student misunderstanding, and investigate the student problem-solving process. We present an interactive web application used by students to complete SQL lab exercises. In addition, we analyze data collected by this application and we offer suggestions for improvement to database lab activities.

This report describes the purpose, design, development and analysis of SQLTips, an online instructional delivery framework and set of instructional modules relating to advanced features and performance tuning of Oracle's Structured Query Language (SQL). SQLTips was developed using Wiki, server-side software that allows users to edit web pages with almost any browser. The report includes a literature review of existing SQL instructional materials and a review of instructional theory. The report also includes a description of the formative evaluation process and results. These results show that SQLTips is easy and enjoyable to use. Based on a scale of 1 to 7 with 7 being the most positive, the 10 modules comprising SQLTips averaged a 6.1 for ease of use and a 6.2 for enjoyability. Posttest results also showed an average increase of 46% upon completion of the instruction. The report also contains a critique of the project.

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<p>A problem in modern command and control situations is that much data is available from different sensors. Several sensor data sources also require that the user has knowledge about the specific sensor types to be able to interpret the data.</p><p>To alleviate the working situation for a commander, we have designed and constructed a system that will take input from several different sensors and subsequently present the relevant combined information to the user. The users specify what kind of information is of interest at the moment by means of a query language. The main issues when designing this query language have been that (a) the users should not have to have any knowledge about sensors or sensor data analysis, and (b) that the query language should be powerful and flexible, yet easy to use. The solution has been to (a) use sensor data independence and (b) have a visual query language.</p><p>A visual query language was developed with a two-step interface. First, the users pose a “rough”, simple query that is evaluated by the underlying knowledge system. The system returns the relevant information that can be found in the sensor data. Then, the users have the possibility to refine the result by setting conditions for this. These conditions are formulated by specifying attributes of objects or relations between objects.</p><p>The problem of uncertainty in spatial data; (i.e. location, area) has been considered. The question of how to represent potential uncertainties is dealt with. An investigation has been carried out to find which relations are practically useful when dealing with uncertain spatial data.</p><p>The query language has been evaluated by means of a scenario. The scenario was inspired by real events and was developed in cooperation with a military officer to assure that it was fairly realistic. The scenario was simulated using several tools where the query language was one of the more central ones. It proved that the query language can be of use in realistic situations.</p> / Report code: LiU-Tek-Lic-2007:42.

A problem in modern command and control situations is that much data is available from different sensors. Several sensor data sources also require that the user has knowledge about the specific sensor types to be able to interpret the data. To alleviate the working situation for a commander, we have designed and constructed a system that will take input from several different sensors and subsequently present the relevant combined information to the user. The users specify what kind of information is of interest at the moment by means of a query language. The main issues when designing this query language have been that (a) the users should not have to have any knowledge about sensors or sensor data analysis, and (b) that the query language should be powerful and flexible, yet easy to use. The solution has been to (a) use sensor data independence and (b) have a visual query language. A visual query language was developed with a two-step interface. First, the users pose a “rough”, simple query that is evaluated by the underlying knowledge system. The system returns the relevant information that can be found in the sensor data. Then, the users have the possibility to refine the result by setting conditions for this. These conditions are formulated by specifying attributes of objects or relations between objects. The problem of uncertainty in spatial data; (i.e. location, area) has been considered. The question of how to represent potential uncertainties is dealt with. An investigation has been carried out to find which relations are practically useful when dealing with uncertain spatial data. The query language has been evaluated by means of a scenario. The scenario was inspired by real events and was developed in cooperation with a military officer to assure that it was fairly realistic. The scenario was simulated using several tools where the query language was one of the more central ones. It proved that the query language can be of use in realistic situations. / <p>Report code: LiU-Tek-Lic-2007:42.</p>

Apesar de muito trabalho ter sido dispendido sobre linguagens de consulta a Sistemas de Gerenciamento de Bancos de Dados Relacionais, existem somente dois paradigmas básicos para essas linguagens, que são representados pela Structured Query Language – SQL e pela Query by Example – QBE. Apesar dessas linguagens de consultas serem computacionalmente completas, elas tem a desvantagem de não permitir ao usuário nenhuma interação gráfica com a informação contida na base de dados. Um dos principais desenvolvimentos na área de base de dados diz respeito às ferramentas que proveêm aos usuários um entendimento simples da base de dados e uma extração amigável da informação. A linguagem descrita neste trabalho possibilita que usuários criem consultas graficamente por meio de diagramas de fluxo de dados. Além da linguagem de consulta gráfica, este trabalho mostra também a ferramenta de apoio Data Flow Query Language - DFQL, que é um editor/executor de consultas construído para suportar essa linguagem, através de um conjunto de operadores representados graficamente, e a execução desses diagramas, analisando a rede e gerando os comandos correspondentes em SQL para realização da consulta. Esses comandos são submetidos ao sistema de gerenciamento de banco de dados e o resultado é mostrado/gravado conforme a consulta feita. / In spite of many works done on query languages, all existing languages are direct extensions of Structured Query Language – SQL and query-By-Example – QBE. These two languages were developed in the beginning of the Relational Database Management Systems – RDBMS development. Althoug these languages are computationally complete, they take the disadvantage of not supporting graphical interaction with data. One of the the main developments in the database area concerns tools to provide users a simple understand of database content, and friendly extraction of the information. The language described in this work enables users to create graphical queries using data flow diagrams. Besides the graphical query language, this work also shows the Data Flow Query Language - DFQL tool. This tool is a query editor/executer that supports this language, using a set of operators represented graphicaly, and the diagram execution is done by analising the network and producing the respective commands in SQL to realize the query. This commands are sent to the DBMS and the result is shown/recorded according to the query.

<p>Science is changing. Computers, fast communication, and  new technologies have created new ways of conducting research.  For  instance, researchers from different disciplines are processing and  analyzing scientific data that is increasing at an exponential rate.  This kind of research requires that the scientists have access to  tools that can handle huge amounts of data, enable access to vast  computational resources, and support the collaboration of large  teams of scientists. This thesis focuses on tools that help support  scientific collaboration.</p><p>Workflows and provenance are two concepts that have proven useful in  supporting scientific collaboration.  Workflows provide a formal  specification of scientific experiments, and provenance offers a  model for documenting data and process dependencies.  Together, they  enable the creation of tools that can support collaboration through  the whole scientific life-cycle, from specification of experiments  to validation of results.  However, existing models for workflows  and provenance are often specific to particular tasks and tools.  This makes it hard to analyze the history of data that has been  generated over several application areas by different tools.  Moreover, workflow design is a time-consuming process and often  requires extensive knowledge of the tools involved and collaboration  with researchers with different expertise. This thesis addresses  these problems.</p><p>Our first contribution is a study of the differences between two  approaches to interoperability between provenance models: direct  data conversion, and mediation. We perform a case study where we  integrate three different provenance models using the mediation  approach, and show the advantages compared to data conversion.  Our  second contribution serves to support workflow design by allowing  multiple users to concurrently design workflows. Current workflow  tools lack the ability for users to work simultaneously on the same  workflow.  We propose a method that uses the provenance of workflow  evolution to enable real-time collaborative design of workflows.  Our third contribution considers supporting workflow design by  reusing existing workflows. Workflow collections for reuse are  available, but more efficient methods for generating summaries of  search results are still needed. We explore new summarization  strategies that considers the workflow structure.</p><p><img src="data:image/png;base64,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%3D" /></p>

Databases are used in many applications, spanning virtually the entire range of data processing services industry. The data in many database applications can be most naturally represented in the form of a graph structure consisting of various types of nodes and edges with several properties. These graph data can be classified into four categories: social networks describing the relationships between individual person and/or groups of people (e.g. genealogy, network of coauthorship among academics, etc); information networks in which the structure of the network reflects the structure of the information stored in the nodes (e.g. citation network among academic papers, etc); geographic networks, providing geographic information about public transport systems, airline routes, etc; and biological networks (e.g. biochemical networks, neuron network, etc). In order to analyze such networks and obtain desired information that users are interested in, some typical queries must be conducted. It can be seen that many of the query patterns are across multiple categories described above, such as finding nodes with certain properties in a path or graph, finding the distance between nodes, finding sub-graphs, paths enumeration, etc. However, the classical query languages like SQL, OQL are inept dealing with these types of queries needed to be performed in the above applications. Therefore, a data model that can effectively represent the graph objects and their properties, and a query language which empowers users to answer queries across multiple categories are needed. In this research work, a graph data model and a query language are proposed to resolve the issues existing in the current database applications. The proposed graph data model is an object-oriented graph data model which aims to represent the graph objects and their properties for various applications. The graph query language empowers users to query graph objects and their properties in a graph with specified conditions. The capability to specify the relationships among the entities composing the queried sub-graph makes the language more flexible than others.

An increasing amount of data is published as semistructured documents formatted with presentational markup. Examples include data objects such as mathematical expressions encoded with MathML or web pages encoded with XHTML. Our intention is to improve the state of the art in retrieving, manipulating, or mining such data. We focus first on mathematics retrieval, which is appealing in various domains, such as education, digital libraries, engineering, patent documents, and medical sciences. Capturing the similarity of mathematical expressions also greatly enhances document classification in such domains. Unlike text retrieval, where keywords carry enough semantics to distinguish text documents and rank them, math symbols do not contain much semantic information on their own. Unfortunately, considering the structure of mathematical expressions to calculate relevance scores of documents results in ranking algorithms that are computationally more expensive than the typical ranking algorithms employed for text documents. As a result, current math retrieval systems either limit themselves to exact matches, or they ignore the structure completely; they sacrifice either recall or precision for efficiency. We propose instead an efficient end-to-end math retrieval system based on a structural similarity ranking algorithm. We describe novel optimization techniques to reduce the index size and the query processing time. Thus, with the proposed optimizations, mathematical contents can be fully exploited to rank documents in response to mathematical queries. We demonstrate the effectiveness and the efficiency of our solution experimentally, using a special-purpose testbed that we developed for evaluating math retrieval systems. We finally extend our retrieval system to accommodate rich queries that consist of combinations of math expressions and textual keywords. As a second focal point, we address the problem of recognizing structural repetitions in typical web documents. Most web pages use presentational markup standards, in which the tags control the formatting of documents rather than semantically describing their contents. Hence, their structures typically contain more irregularities than descriptive (data-oriented) markup languages. Even though applications would greatly benefit from a grammar inference algorithm that captures structure to make it explicit, the existing algorithms for XML schema inference, which target data-oriented markup, are ineffective in inferring grammars for web documents with presentational markup. There is currently no general-purpose grammar inference framework that can handle irregularities commonly found in web documents and that can operate with only a few examples. Although inferring grammars for individual web pages has been partially addressed by data extraction tools, the existing solutions rely on simplifying assumptions that limit their application. Hence, we describe a principled approach to the problem by defining a class of grammars that can be inferred from very small sample sets and can capture the structure of most web documents. The effectiveness of this approach, together with a comparison against various classes of grammars including DTDs and XSDs, is demonstrated through extensive experiments on web documents. We finally use the proposed grammar inference framework to extend our math retrieval system and to optimize it further.

No description available.