A logical approach to the management of object identifiers in non-conventional database management systems

Non-conventional database management systems are used to achieve a better performance when dealing with complex data. One fundamental concept of these systems is object identity (OID), because each object in the database has a unique identifier that is used to access and reference it in relationships to other objects. Two approaches can be used for the implementation of OIDs: physical or logical OIDs. In order to manage complex data, was proposed the Multimedia Data Manager Kernel (NuGeM) that uses a logical technique, named Indirect Mapping. This paper proposes an improvement to the technique used by NuGeM, whose original contribution is management of OIDs with a fewer number of disc accesses and less processing, thus reducing management time from the pages and eliminating the problem with exhaustion of OIDs. Also, the technique presented here can be applied to others OODBMSs. © 2011 IEEE.

Use of Dynamic Technologies for Web-enabled Database Management Systems

In this paper we consider two computer systems and the dynamic Web technologies they are using. Different contemporary dynamic web technologies are described in details and their advantages and disadvantages have been shown. Specific applications are developed, clinic and studying systems, and their programming models are described. Finally we implement these two applications in the students education process: Online studying has been tested in the Technical University – Varna, Web based clinic system has been used for practical education of the students in the Medical College - Sofia, branch V. Tarnovo

Design principles of semantic binary database management systems

The Semantic Binary Data Model (SBM) is a viable alternative to the now-dominant relational data model. SBM would be especially advantageous for applications dealing with complex interrelated networks of objects provided that a robust efficient implementation can be achieved. This dissertation presents an implementation design method for SBM, algorithms, and their analytical and empirical evaluation. Our method allows building a robust and flexible database engine with a wider applicability range and improved performance. ^ Extensions to SBM are introduced and an implementation of these extensions is proposed that allows the database engine to efficiently support applications with a predefined set of queries. A New Record data structure is proposed. Trade-offs of employing Fact, Record and Bitmap Data structures for storing information in a semantic database are analyzed. ^ A clustering ID distribution algorithm and an efficient algorithm for object ID encoding are proposed. Mapping to an XML data model is analyzed and a new XML-based XSDL language facilitating interoperability of the system is defined. Solutions to issues associated with making the database engine multi-platform are presented. An improvement to the atomic update algorithm suitable for certain scenarios of database recovery is proposed. ^ Specific guidelines are devised for implementing a robust and well-performing database engine based on the extended Semantic Data Model. ^

AgroDB - integration of database management systems with crop models.

2016

Improving reporting management with relational database management system

Data management consists of collecting, storing, and processing the data into the format which provides value-adding information for decision-making process. The development of data management has enabled of designing increasingly effective database management systems to support business needs. Therefore as well as advanced systems are designed for reporting purposes, also operational systems allow reporting and data analyzing. The used research method in the theory part is qualitative research and the research type in the empirical part is case study. Objective of this paper is to examine database management system requirements from reporting managements and data managements perspectives. In the theory part these requirements are identified and the appropriateness of the relational data model is evaluated. In addition key performance indicators applied to the operational monitoring of production are studied. The study has revealed that the appropriate operational key performance indicators of production takes into account time, quality, flexibility and cost aspects. Especially manufacturing efficiency has been highlighted. In this paper, reporting management is defined as a continuous monitoring of given performance measures. According to the literature review, the data management tool should cover performance, usability, reliability, scalability, and data privacy aspects in order to fulfill reporting managements demands. A framework is created for the system development phase based on requirements, and is used in the empirical part of the thesis where such a system is designed and created for reporting management purposes for a company which operates in the manufacturing industry. Relational data modeling and database architectures are utilized when the system is built for relational database platform.

The Role of DBMS in Analytical Processes of the Logistic of Stock Reserves

One of main problems of corporate information systems is the precise evaluation of speed of transactions and the speed of making reports. The core of the problem is based on the DBMS that is used. Most DBMS which are oriented for high performance and reliability of transactions do not give fast access to analytical and summarized data and vice versa. It is quite difficult to estimate which class of database to use. The author of the article gives a concise observation of the problem and a possible way to be solved.

How to Use a Desktop Version of a DBMS for Client-Server Applications

DBMS (Data base management systems) still have a very high price for small and middle enterprises in Bulgaria. Desktop versions are free but they cannot function in multi-user environment. We will try to make an application server which will make a Desktop version of a DBMS open to many users. Thus, this approach will be appropriate for client-server applications. The author of the article gives a concise observation of the problem and a possible way of solution.

Endowing NoSQL DBMS with SQL features through standard Call Level Interfaces

To store, update and retrieve data from database management systems (DBMS), software architects use tools, like call-level interfaces (CLI), which provide standard functionalities to interact with DBMS. However, the emerging of NoSQL paradigm, and particularly new NoSQL DBMS providers, lead to situations where some of the standard functionalities provided by CLI are not supported, very often due to their distance from the relational model or due to design constraints. As such, when a system architect needs to evolve, namely from a relational DBMS to a NoSQL DBMS, he must overcome the difficulties conveyed by the features not provided by NoSQL DBMS. Choosing the wrong NoSQL DBMS risks major issues with components requesting non-supported features. This paper focuses on how to deploy features that are not so commonly supported by NoSQL DBMS (like Stored Procedures, Transactions, Save Points and interactions with local memory structures) by implementing them in standard CLI.

Llenguatges de consulta en l'àmbit de la Web Semàntica : Cas d'estudi SPARQL

El projecte es basa en estudiar i avaluar diferents sistemes gestors de bases de dades (SGBD) per desar informació dins del context de la Web Semàntica., tal com es veurà en el capítol 4. La Web Semàntica permet dotar de significat al contingut textual de la web, permetent que sigui interpretable per una màquina.

Paged similarity queries

An important feature of a database management systems (DBMS) is its client/server architecture, where managing shared memory among the clients and the server is always an tough issue. However, similarity queries are specially sensitive to this kind of architecture, since the answer sizes vary widely. Usually, the answers of similarity query are fully processed to be sent in full to the user, who often is interested in just parts of the answer, e.g. just few elements closer or farther to the query reference. Compelling the DBMS to retrieve the full answer, further ignoring its majority is at least a waste of server processing power. Paging the answer is a technique that splits the answer onto several pages, following client requests. Despite the success of paging on traditional queries, little work has been done to support it in similarity queries. In this work, we present a technique that not only provides paging in similarity range or k-nearest neighbor queries, but also supports them in two variations: the forward similarity query and the backward similarity query. They return elements either increasingly farther of increasingly closer to the query reference. The reported experiments show that, depending on the proportion of the interesting part over the full answer, both techniques allow answering queries much faster than it is obtained in the non-paged way. (C) 2010 Elsevier Inc. All rights reserved.

Seamlessly integrating similarity queries in SQL

Modern database applications are increasingly employing database management systems (DBMS) to store multimedia and other complex data. To adequately support the queries required to retrieve these kinds of data, the DBMS need to answer similarity queries. However, the standard structured query language (SQL) does not provide effective support for such queries. This paper proposes an extension to SQL that seamlessly integrates syntactical constructions to express similarity predicates to the existing SQL syntax and describes the implementation of a similarity retrieval engine that allows posing similarity queries using the language extension in a relational DBM. The engine allows the evaluation of every aspect of the proposed extension, including the data definition language and data manipulation language statements, and employs metric access methods to accelerate the queries. Copyright (c) 2008 John Wiley & Sons, Ltd.

Knowledge assisted data management and retrieval in multimedia database systems

With the proliferation of multimedia data and ever-growing requests for multimedia applications, there is an increasing need for efficient and effective indexing, storage and retrieval of multimedia data, such as graphics, images, animation, video, audio and text. Due to the special characteristics of the multimedia data, the Multimedia Database management Systems (MMDBMSs) have emerged and attracted great research attention in recent years. Though much research effort has been devoted to this area, it is still far from maturity and there exist many open issues. In this dissertation, with the focus of addressing three of the essential challenges in developing the MMDBMS, namely, semantic gap, perception subjectivity and data organization, a systematic and integrated framework is proposed with video database and image database serving as the testbed. In particular, the framework addresses these challenges separately yet coherently from three main aspects of a MMDBMS: multimedia data representation, indexing and retrieval. In terms of multimedia data representation, the key to address the semantic gap issue is to intelligently and automatically model the mid-level representation and/or semi-semantic descriptors besides the extraction of the low-level media features. The data organization challenge is mainly addressed by the aspect of media indexing where various levels of indexing are required to support the diverse query requirements. In particular, the focus of this study is to facilitate the high-level video indexing by proposing a multimodal event mining framework associated with temporal knowledge discovery approaches. With respect to the perception subjectivity issue, advanced techniques are proposed to support users' interaction and to effectively model users' perception from the feedback at both the image-level and object-level.

Implementation of an Integrated Activity-Based Costing in a Holistic Database Management System and its Implications for Operations Management

Diplomityössä on tutkittu reaaliaikaisen toimintolaskennan toteuttamista suomalaisen lasersiruja valmistavan PK-yrityksen tietojärjestelmään. Lisäksi on tarkasteltu toimintolaskennan vaikutuksia operatiiviseen toimintaan sekä toimintojen johtamiseen. Työn kirjallisuusosassa on käsitelty kirjallisuuslähteiden perusteella toimintolaskennan teorioita, laskentamenetelmiä sekä teknisessä toteutuksessa käytettyjä teknologioita. Työn toteutusosassa suunniteltiin ja toteutettiin WWW-pohjainen toimintolaskentajärjestelmä case-yrityksen kustannuslaskennan sekä taloushallinnon avuksi. Työkalu integroitiin osaksi yrityksen toiminnanohjaus- sekä valmistuksenohjausjärjestelmää. Perinteisiin toimintolaskentamallien tiedonkeruujärjestelmiin verrattuna case-yrityksessä syötteet toimintolaskentajärjestelmälle tulevat reaaliaikaisesti osana suurempaa tietojärjestelmäintegraatiota.Diplomityö pyrkii luomaan suhteen toimintolaskennan vaatimusten ja tietokantajärjestelmien välille. Toimintolaskentajärjestelmää yritys voi hyödyntää esimerkiksi tuotteiden hinnoittelussa ja kustannuslaskennassa näkemällä tuotteisiin liittyviä kustannuksia eri näkökulmista. Päätelmiä voidaan tehdä tarkkaan kustannusinformaatioon perustuen sekä määrittää järjestelmän tuottaman datan perusteella, onko tietyn projektin, asiakkuuden tai tuotteen kehittäminen taloudellisesti kannattavaa.