The Common NFI Database

We are proposing a keyword-based query interface for knowledge bases - including relational or deductive databases - based on contextual background knowledge such as suitable join conditions or synonyms. Join conditions could be extracted from existing referential integrity (foreign key) constaints of the database schema. They could also be learned from other, previous database queries, if the database schema does not contain foreign key constraints.
\nGiven a textual representation - a word list - of a query to a relational database, one may parse the list into a structured term. The intelligent and cooperative part of our approach is to hypothesize the semantics of the word list and to find suitable links between the concepts mentioned in the query using contextual knowledge, more precisely join conditions between the database tables.
\nWe use a knowledge-based parser based on an extension of Definite Clause Grammars (Dcg) that are interweaved with calls to the database schema to suitably annotate the tokens as table names, table attributes, attribute values or relationships linking tables. Our tool DdQl yields the possible queries in a special domain specific rule language that extends Datalog, from which the user can choose one.

A relational database is a powerful tool for collecting and analyzing the vast amounts of inner-related data associated with the manufacture of composite materials. A relational database contains many individual database tables that store data that are related in some fashion. Manufacturing process variables as well as quality assurance measurements can be collected and stored in database tables indexed according to lot numbers, part type or individual serial numbers. Relationships between manufacturing process and product quality can then be correlated over a wide range of product types and process variations. This paper presents details on how relational databases are used to collect, store, and analyze process variables and quality assurance data associated with the manufacture of advanced composite materials. Important considerations are covered including how the various types of data are organized and how relationships between the data are defined. Employing relational database techniques to establish correlative relationships between process variables and quality assurance measurements is then explored. Finally, the benefits of database techniques such as data warehousing, data mining and web based client/server architectures are discussed in the context of composite material manufacturing.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

A National highway and urban runoff water-quality metadatabase was developed by the U.S. Geological Survey in cooperation with the Federal Highway Administration as part of the National Highway Runoff Water-Quality Data and Methodology Synthesis (NDAMS). The database was designed to catalog available literature and to document results of the synthesis in a format that would facilitate current and future research on highway and urban runoff. This report documents the design and implementation of the NDAMS relational database, which was designed to provide a catalog of available information and the results of an assessment of the available data. All the citations and the metadata collected during the review process are presented in a stratified metadatabase that contains citations for relevant publications, abstracts (or previa), and report-review metadata for a sample of selected reports that document results of runoff quality investigations. The database is referred to as a metadatabase because it contains information about available data sets rather than a record of the original data. The database contains the metadata needed to evaluate and characterize how valid, current, complete, comparable, and technically defensible published and available information may be when evaluated for application to the different data-quality objectives as defined by decision makers. This database is a relational database, in that all information is ultimately linked to a given citation in the catalog of available reports. The main database file contains 86 tables consisting of 29 data tables, 11 association tables, and 46 domain tables. The data tables all link to a particular citation, and each data table is focused on one aspect of the information collected in the literature search and the evaluation of available information. This database is implemented in the Microsoft (MS) Access database software because it is widely used within and outside of government and so, is familiar to many existing and potential customers. The stratified metadatabase design for the NDAMS program is implemented in the MS Access file DBDESIGN.mdb and documented using the NDAMS_DD.mdb file recorded on the CD-ROM. The data dictionary file includes complete documentation of the table names, table descriptions, and information about each of the 419 fields in the database.

We propose an extensible platform for bridging private databases and Web services. Our main idea is to make a Web service and its results be a set of virtual tables in a relational database (RDB) environment. As private data that cannot be disclosed is stored in private RDBs, these virtual tables realize a bridge between private RDBs and Web services.

Standards for Continual Scheduling of Batch Operations

Knowledge of the dependencies and correlations which exist between data units in a relational database is of paramount importance when designing a distributed database since discovering such correlations would be crucial for reaching an optimal data distribution. The knowledge may also be used to improve the performance of a centralized database through a reorganization process. In this paper, we propose a data mining approach for identifying groups of correlated tables in a relational database schema by considering the work profile of the database. We analyze the query history to find sets of tables that are frequently accessed together. The sets of tables that are found overlap in general and we therefore turn each set of tables into a fuzzy set and determine the degree of membership of each table in each of the fuzzy sets. Our approach offers a high degree of flexibility and can be easily customized to produce result with desired amount of detail. The outcome will be highly valuable for guiding a database administrator in producing a better allocation plan. It also guides the database designer in deriving a well optimized fragmentation plan. Our experiment shows the viability and power of our approach. The proposed approach can also be extended to find correlations between smaller data units such as fragments, rows or columns.

Standards for Continual Scheduling of Batch Operations

A relation can be conceptually viewed as a table of data. The table's heading defines the relation's name, the column headings are the attribute names, and each row corresponds to an n-tuple of data values describing a single entity. The set of values which can be used in a column is called a domain. A relational data base is composed of a set of time varying relations inter-related through common domains.

There exist many interrelated information sources on the Internet that can be categorized into structured (database) and semistructured (documents). A key challenge is to integrate, query and analyze such heterogeneous collections of information. In this paper, we defend the idea of building web metadata repositories using relational databases as the main source and central data management technology of structured data, enriched by the semistructured data surrounding it. Our proposal rests on the assumption that heterogeneous relational databases can be integrated (i.e. entity resolution is assumed to work well) and thus can serve as references for external data. That is, we tackle the problem of integrating information in the deep web, departing from databases. We discuss a prototype system that can integrate and query metadata and related documents, based on relational database technology. Metadata includes database ER model elements like database name, table, and column (entity, attribute). Web document data include files, documents and web pages. Links between metadata and external documents are built with SQL queries. Once databases and documents are linked, they are managed and queried with SQL. We discuss an interesting scientific application of our solution with a water pollution database.

У статті проведено порівняльний аналіз трьох основних методів генерації тестових даних для реляційних баз даних: циклічного, на основі Common Table Expressions (CTE) та з використанням тимчасових таблиць. Експериментальне тестування здійснено в середовищі MS SQL Server на прикладі таблиць бази даних торговельної компанії. Проведено порівняння за ключовими метриками ефективності генерації - часу генерації, використання системних ресурсів та масштабованістю об’ємів таблиць тестової бази даних. Результати дослідження обґрунтували ефективність методу рекурсивних CTE для різних обсягів і структур даних. Подано рекомендації щодо вибору методів генерації тестових наборів відповідно до вимог проектів БД, зокрема при використанні сервісів роботи з реляційними БД на хмарних платформах.

Перспективний розвиток галузі розробки програмного забезпечення призвів до появи різноманітних шаблонів та стратегій маніпуляцій з базами даних та, відповідно інструментів, що їх реалізують. Одним з шаблонів проектування, що набуває все більшої популярності є Active Record. Цей шаблон дозволяє інкапсулювати всю логіку роботи з таблицею бази даних у сам клас моделі, завдяки чому зникає необхідність створювати додаткові сервісні класи, які будуть відповідати за CRUD операції. Однією з реалізацій цього підходу є ORM-система ActiveJDBC. ActiveJDBC розвивається як відкрите програмне забезпечення і є популярним варіантом для розробки додатків на Java, які взаємодіють з реляційними базами даних. Метою роботи є представлення процесу покращення користувацького досвіду при роботі з ORM-системою ActiveJDBC. Покращення достягається за рахунок автоматичної генерації коду, що дозволяє маніпулювати з ActiveJDBC об’єктами як з POJO. Методологія рішення представленого завдання складається в розробленні обробника анотацій, що дозволяє автоматично на етапі компіляції згенерувати код, що буде взаємодіяти з об’єктами ORM системи ActiveJDBC. Наукова новизна отриманих результатів полягає у тому, що вперше було розроблено програмне забезпечення, яке полегшує взаємодію з ActiveJDBC компонентами, та дозволяє додавати функціонал, який не був закладений у ActiveJDBC його розробником. Висновки. Досліджені підходи генерації програмного коду у мові програмування Java та розроблено обробник анотацій, що дозволяє автоматично на етапі компіляції згенерувати код, який буде взаємодіяти з об’єктами ORM системи ActiveJDBC. Розроблений інструмент дозволяє: вивільнити робочий час програміста від написання шаблонного коду, та зосередитись на вирішенні поставлених задач, а не на обслуговуванні інструмента взаємодії з базою даних; зменшити обсяг коду, що повинен пройти валідацію при проходженні процесу Code Review; підвищити читабельність отриманого коду, завдяки використанню геттерів та сеттерів, назви яких відповідають специфікації JavaBeans, та використанням патерна Будівельник.

Raw data are presented on orientation studies conducted in crystalline rock areas of the Southeast which were chosen because of published references to uranium mineralization. Preliminary data for four orientation study areas are included. These areas are Lamar County, Georgia; Oconee County, South Carolina; Brush Creek, North Carolina; and North Harper, North Carolina. Sample locality maps, tables of field data, and tables of analytical data are included for each study area. (JGB)

Chapter 2 - Querying

The paper describes recent improvements made to the structural recursion of the Data Funnel Interface. This end user interface organizes the raw data in a database table into a series of nested data lists that guide users to information. The new developments outlined in the article streamline the recursive algorithm and the data files that it produces. The program logic constructs a new SELECT statement on each recursive pass to retrieve a unique subset of attribute data from the table. Next, it transforms the subset's structure into a structure of nested data lists that users can navigate in the interface. The branching data model (BDM) provides the framework for combining these two objectives into a single, recursive algorithm. The data BDM features a detailed description of the data mapping between two table attributes as one-to-many data relationships. The input data for the recursion is a list of table attributes that models the data funnel network. Each new subset of data in the series folds into the former one until it reaches the final subset, a primary key value. The prior algorithm draws on the depth-first tree growing methodology of the OHDS structure to manage these subsets. The paper introduces a new numbering scheme to organize the subsets of data. This improvement assigns a unique list number to each new subset when adding it to the database table. This capability replaces the need for the OHDS in the table. It also simplifies the data funnel software and makes it easier to maintain.

We present a logic, called fuzzy attribute logic (FAL), for reasoning about formulas describing particular attribute dependencies. The formulas are of a form A ⇒ B where A and B are collections of attributes. Our formulas can be interpreted in two ways. First, in data tables with entries containing degrees to which objects (table rows) have attributes (table columns). Second, in database tables where each domain is equipped with a similarity relation assigning a degree of similarity to any pair of domain elements. We assume that the scale of degrees is equipped with fuzzy logical connectives and forms an arbitrary complete residuated lattice. This covers many structures used in fuzzy logic applications as well as structures used in formal systems of fuzzy logic. If the scale contains only two degrees, 0 (falsity) and 1 (truth), two well-known calculi become particular cases of our logic. Namely, with the first interpretation, our logic coincides with attribute logic used in formal concept analysis; with the second interpretation, our logic coincides with Armstrong system for reasoning about functional dependencies. We prove completeness of FAL over arbitrary complete residuated lattices in two versions. First, in the ordinary style, completeness asserts that a formula A ⇒ B is entailed by a collection T of formulas if A ⇒ B is provable from T. Second, in the graded style, completeness asserts that a degree to which A ⇒ B is entailed by a collection T of formulas equals a degree to which A ⇒ B is provable from T.