Abstract: Relational databases constitute a very vital tool for the effective management and administration of both personal and organizational data. Data access ranges from a single user database management software to a more complex distributed server system. This paper intends to appraise the use a programming language extension like structured query language (SQL) to establish links to a relational database (Microsoft Access 2013) using Visual C++ 9 programming language environment. The methodology used involves the creation of tables to form a database using Microsoft Access 2013, which is Object Linking and Embedding (OLE) database compliant. The SQL command is used to query the tables in the database for easy extraction of expected records inside the visual C++ environment. The findings of this paper reveal that records can easily be accessed and manipulated to filter exactly what the user wants, such as retrieval of records with specified criteria, updating of records, and deletion of part or the whole records in a table.
Abstract: Currently, database management systems have various tools such as backup and maintenance, and also provide statistical information such as resource usage and security. In terms of query performance, this paper covers query optimization, views, indexed tables, pre-computation materialized view, query performance analysis in which query plan alternatives can be created and the least costly one selected to optimize a query. Indexes and views can be created for related table columns. The literature review of this study showed that, in the course of time, despite the growing capabilities of the database management system, only database administrators are aware of the need for dealing with archival and transactional data types differently. These data may be constantly changing data used in everyday life, and also may be from the completed questionnaire whose data input was completed. For both types of data, the database uses its capabilities; but as shown in the findings section, instead of repeating similar heavy calculations which are carrying out same results with the same query over a survey results, using materialized view results can be in a more simple way. In this study, this performance difference was observed quantitatively considering the cost of the query.
Abstract: Currently, the field of data migration is very topical. As the number of applications developed rapidly, the ever-increasing volume of data collected has driven the architectural migration from Relational Database Management System (RDBMS) to NoSQL (Not Only SQL) database. This very recent technology is important enough in the field of database management. The main aim of this paper is to present a methodology for data migration from RDBMS to NoSQL database. To illustrate this methodology, we implement a software prototype using MySQL as a RDBMS and MongoDB as a NoSQL database. Although this is a hard engineering work, our results show that the proposed methodology can successfully accomplish the goal of this study.
Abstract: People, throughout the history, have made estimates
and inferences about the future by using their past experiences.
Developing information technologies and the improvements in the
database management systems make it possible to extract useful
information from knowledge in hand for the strategic decisions.
Therefore, different methods have been developed. Data mining by
association rules learning is one of such methods. Apriori algorithm,
one of the well-known association rules learning algorithms, is not
commonly used in spatio-temporal data sets. However, it is possible
to embed time and space features into the data sets and make Apriori
algorithm a suitable data mining technique for learning spatiotemporal
association rules. Lake Van, the largest lake of Turkey, is a
closed basin. This feature causes the volume of the lake to increase or
decrease as a result of change in water amount it holds. In this study,
evaporation, humidity, lake altitude, amount of rainfall and
temperature parameters recorded in Lake Van region throughout the
years are used by the Apriori algorithm and a spatio-temporal data
mining application is developed to identify overflows and newlyformed
soil regions (underflows) occurring in the coastal parts of
Lake Van. Identifying possible reasons of overflows and underflows
may be used to alert the experts to take precautions and make the
necessary investments.
Abstract: This research is aimed to develop the online-class
scheduling management system and improve as a complex problem
solution, this must take into consideration in various conditions and
factors. In addition to the number of courses, the number of students
and a timetable to study, the physical characteristics of each class
room and regulations used in the class scheduling must also be taken
into consideration. This system is developed to assist management in
the class scheduling for convenience and efficiency. It can provide
several instructors to schedule simultaneously. Both lecturers and
students can check and publish a timetable and other documents
associated with the system online immediately. It is developed in a
web-based application. PHP is used as a developing tool. The
database management system was MySQL. The tool that is used for
efficiency testing of the system is questionnaire. The system was
evaluated by using a Black-Box testing. The sample was composed
of 2 groups: 5 experts and 100 general users. The average and the
standard deviation of results from the experts were 3.50 and 0.67.
The average and the standard deviation of results from the general
users were 3.54 and 0.54. In summary, the results from the research
indicated that the satisfaction of users were in a good level.
Therefore, this system could be implemented in an actual workplace
and satisfy the users’ requirement effectively.
Abstract: For a spatiotemporal database management system,
I/O cost of queries and other operations is an important performance
criterion. In order to optimize this cost, an intense research on
designing robust index structures has been done in the past decade.
With these major considerations, there are still other design issues
that deserve addressing due to their direct impact on the I/O cost.
Having said this, an efficient buffer management strategy plays a key
role on reducing redundant disk access. In this paper, we proposed an
efficient buffer strategy for a spatiotemporal database index
structure, specifically indexing objects moving over a network of
roads. The proposed strategy, namely MONPAR, is based on the data
type (i.e. spatiotemporal data) and the structure of the index
structure. For the purpose of an experimental evaluation, we set up a
simulation environment that counts the number of disk accesses
while executing a number of spatiotemporal range-queries over the
index. We reiterated simulations with query sets with different
distributions, such as uniform query distribution and skewed query
distribution. Based on the comparison of our strategy with wellknown
page-replacement techniques, like LRU-based and Prioritybased
buffers, we conclude that MONPAR behaves better than its
competitors for small and medium size buffers under all used query-distributions.
Abstract: Database management systems that integrate user preferences promise better solution for personalization, greater flexibility and higher quality of query responses. This paper presents a tentative work that studies and investigates approaches to express user preferences in queries. We sketch an extend capabilities of SQLf language that uses the fuzzy set theory in order to define the user preferences. For that, two essential points are considered: the first concerns the expression of user preferences in SQLf by so-called fuzzy commensurable predicates set. The second concerns the bipolar way in which these user preferences are expressed on mandatory and/or optional preferences.
Abstract: The emerging Semantic Web has been attracted many
researchers and developers. New applications have been developed on top of Semantic Web and many supporting tools introduced to improve its software development process. Metadata modeling is one of development process where supporting tools exists. The existing
tools are lack of readability and easiness for a domain knowledge expert to graphically models a problem in semantic model. In this paper, a metadata modeling tool called RDFGraph is proposed. This
tool is meant to solve those problems. RDFGraph is also designed to work with modern database management systems that support RDF and to improve the performance of the query execution process. The
testing result shows that the rules used in RDFGraph follows the W3C standard and the graphical model produced in this tool is properly translated and correct.
Abstract: Modern spatial database management systems require a unique Spatial Access Method (SAM) in order solve complex spatial quires efficiently. In this case the spatial data structure takes a prominent place in the SAM. Inadequate data structure leads forming poor algorithmic choices and forging deficient understandings of algorithm behavior on the spatial database. A key step in developing a better semantic spatial object data structure is to quantify the performance effects of semantic and outlier detections that are not reflected in the previous tree structures (R-Tree and its variants). This paper explores a novel SSRO-Tree on SAM to the Topo-Semantic approach. The paper shows how to identify and handle the semantic spatial objects with outlier objects during page overflow/underflow, using gain/loss metrics. We introduce a new SSRO-Tree algorithm which facilitates the achievement of better performance in practice over algorithms that are superior in the R*-Tree and RO-Tree by considering selection queries.
Abstract: Selecting the data modeling technique for an
information system is determined by the objective of the resultant
data model. Dimensional modeling is the preferred modeling
technique for data destined for data warehouses and data mining,
presenting data models that ease analysis and queries which are in
contrast with entity relationship modeling. The establishment of data
warehouses as components of information system landscapes in
many organizations has subsequently led to the development of
dimensional modeling. This has been significantly more developed
and reported for the commercial database management systems as
compared to the open sources thereby making it less affordable for
those in resource constrained settings. This paper presents
dimensional modeling of HIV patient information using open source
modeling tools. It aims to take advantage of the fact that the most
affected regions by the HIV virus are also heavily resource
constrained (sub-Saharan Africa) whereas having large quantities of
HIV data. Two HIV data source systems were studied to identify
appropriate dimensions and facts these were then modeled using two
open source dimensional modeling tools. Use of open source would
reduce the software costs for dimensional modeling and in turn make
data warehousing and data mining more feasible even for those in
resource constrained settings but with data available.
Abstract: Large-scale systems such as Grids offer
infrastructures for both data distribution and parallel processing. The
use of Grid infrastructures is a more recent issue that is already
impacting the Distributed Database Management System industry. In
DBMS, distributed query processing has emerged as a fundamental
technique for ensuring high performance in distributed databases.
Database placement is particularly important in large-scale systems
because it reduces communication costs and improves resource
usage. In this paper, we propose a dynamic database placement
policy that depends on query patterns and Grid sites capabilities. We
evaluate the performance of the proposed database placement policy
using simulations. The obtained results show that dynamic database
placement can significantly improve the performance of distributed
query processing.
Abstract: This paper presents an algebraic approach to optimize
queries in domain-specific database management system
for protein structure data. The approach involves the introduction of
several protein structure specific algebraic operators to query the
complex data stored in an object-oriented database system. The
Protein Algebra provides an extensible set of high-level Genomic
Data Types and Protein Data Types along with a comprehensive
collection of appropriate genomic and protein functions. The paper
also presents a query translator that converts high-level query
specifications in algebra into low-level query specifications in
Protein-QL, a query language designed to query protein structure
data. The query transformation process uses a Protein Ontology that
serves the purpose of a dictionary.
Abstract: Current tools for data migration between documentoriented
and relational databases have several disadvantages. We
propose a new approach for data migration between documentoriented
and relational databases. During data migration the relational
schema of the target (relational database) is automatically created
from collection of XML documents. Proposed approach is verified on
data migration between document-oriented database IBM Lotus/
Notes Domino and relational database implemented in relational
database management system (RDBMS) MySQL.
Abstract: In present days the area of data migration is very topical. Current tools for data migration in the area of relational database have several disadvantages that are presented in this paper. We propose a methodology for data migration of the database tables and their data between various types of relational database systems (RDBMS). The proposed methodology contains an expert system. The expert system contains a knowledge base that is composed of IFTHEN rules and based on the input data suggests appropriate data types of columns of database tables. The proposed tool, which contains an expert system, also includes the possibility of optimizing the data types in the target RDBMS database tables based on processed data of the source RDBMS database tables. The proposed expert system is shown on data migration of selected database of the source RDBMS to the target RDBMS.
Abstract: The data exchanged on the Web are of different nature
from those treated by the classical database management systems;
these data are called semi-structured data since they do not have a
regular and static structure like data found in a relational database;
their schema is dynamic and may contain missing data or types.
Therefore, the needs for developing further techniques and
algorithms to exploit and integrate such data, and extract relevant
information for the user have been raised. In this paper we present
the system OSIX (Osiris based System for Integration of XML
Sources). This system has a Data Warehouse model designed for the
integration of semi-structured data and more precisely for the
integration of XML documents. The architecture of OSIX relies on
the Osiris system, a DL-based model designed for the representation
and management of databases and knowledge bases. Osiris is a viewbased
data model whose indexing system supports semantic query
optimization. We show that the problem of query processing on a
XML source is optimized by the indexing approach proposed by
Osiris.