Experience in developing a web application for relational databases modeling with a forward engineering function for training students of technical specialties

The article actualizes the need to develop software for modeling relational databases for use in the process of teaching students of technical specialties in disciplines related to databases.The problem is considered from the point of view of assessing modern software used in the process of teaching students database design skills. Based on the shortcomings identified during the software review, a number of requirements for the actual software were determined. Formed key requirements are mobility, accessibility, versatility and openness of the development platform.The article describes the process of solving key problems that arose during the implementation of a project to develop a web application for modeling relational databases in accordance with the generated requirements. The practical implementation of the following functions is sequentially considered: creation of a logical relational data model, creation of a physical data model, direct engineering into relational database software. The main technological solutions used in the development of a web application to ensure the qualities specified in the condition are described.The result of the work is the successful testing of the development results in the process of creating a real web application, both within the framework of laboratory and practical work in the disciplines “Design and administration of databases” and “Data management”, and at the stage of writing graduate works for technical directions of training.

Graphical Notation for Document Database Modeling

Goals and objectives. Graphical models have proven to be a reliable, clear and convenient tool for creating sketch models of databases. Most of the existing notations are designed for the relational data model, the dominant data model for the last thirty years. However, the development of information technologies has led to an increase in the popularity of non-relational data models, primarily the document model. One of the problems of its application in practice is the lack of suitable tools that allow performing graphical modeling of the database, taking into account the features of the document model, at the stage of logical design. The development of appropriate tools is an important and actual task, since their application in practical research makes it possible to identify, classify and analyze typical modeling errors that allow the designer to reduce the risk of their occurrence in the future. The purpose of this article is to develop a graphical notation that, on the one hand, providing convenience for the designer, and on the other hand, taking into account the peculiarities of creating and functioning of the noSQL document storage model.Materials and methods. The materials for the study were numerous publications devoted to the development of graphical notations in problems and their application to database design for various information systems. The selected materials were analyzed and the main graphical notations used to describe the relational data model were identified. Three notations were selected from them, a set of graphic stereotypes, which were most different from each other, the analysis of which allowed us to identify the main image patterns of the components of the relational model.The resulting patterns were applied to the main elements of the document database, which were obtained by analyzing the documentation of the popular MongoDB DBMS.Results. The result of the research was the creation of a new tool for modeling document databases at the logical level, which consists of a set of graphic stereotypes and rules for their application. On the one hand, the development is well known to practitioners who have previously worked with relational data models, since its development took into account many years of experience in using graphical models in the field of relational database design, and on the other hand, it reflects the features of the structure of the document model.Conclusion. The practical application of the developed model has shown the convenience of its use both in the process of designing document databases and in the process of teaching students within this subject area. The use of graphical models constructed in the proposed graphical notation will allow researchers to create and illustrate typical patterns of document databases, which will undoubtedly have a positive impact on the dynamics of the development of promising data storage technologies.

Data modelling and data processing generated by human eye movements

Data modeling and data processing are important activities in any scientific research. This research focuses on the modeling of data and processing of data generated by a saccadometer. The approach used is based on the relational data model, but the processing and storage of the data is done with client datasets. The experiments were performed with 26 randomly selected files from a total of 264 experimental sessions. The data from each experimental session was stored in three different formats, respectively text, binary and extensible markup language (XML) based. The results showed that the text format and the binary format were the most compact. Several actions related to data processing were analyzed. Based on the results obtained, it was found that the two fastest actions are respectively loading data from a binary file and storing data into a binary file. In contrast, the two slowest actions were storing the data in XML format and loading the data from a text file, respectively. Also, one of the time-consuming operations turned out to be the conversion of data from text format to binary format. Moreover, the time required to perform this action does not depend in proportion on the number of records processed.

N-Tier Soft Set Data Model: An Approach to Combine the Logicality of SQL and the Flexibility of NoSQL

To process a huge amount of data, computing resources need to be organized in clusters that can be scaled out easily. Still, traditional SQL databases built on the relational data model are difficult to be put to use in such clusters, which has motivated the movement named NoSQL. However, NoSQL databases have their limits by using their own data models. In this paper, the original soft set theory is extended, and a new theory system called n-tier soft set is brought up. We systematically constructed its concepts, definitions, and operations, establishing it as a novel soft set algebra. And some features of this algebra display its natural advantages as a data model which could combine the logicality of the SQL model (also known as the relational model) and the flexibility of NoSQL models. This data model provides a unified and normative perspective logic for organizing and manipulating data, combines metadata (semantic) and data to form a self-described structure, and combines index and data to realize fast locating and correlating.

Growth of relational model: Interdependence and complementary to big data

A database management system is a constant application of science that provides a platform for the creation, movement, and use of voluminous data. The area has witnessed a series of developments and technological advancements from its conventional structured database to the recent buzzword, bigdata. This paper aims to provide a complete model of a relational database that is still being widely used because of its well known ACID properties namely, atomicity, consistency, integrity and durability. Specifically, the objective of this paper is to highlight the adoption of relational model approaches by bigdata techniques. Towards addressing the reason for this in corporation, this paper qualitatively studied the advancements done over a while on the relational data model. First, the variations in the data storage layout are illustrated based on the needs of the application. Second, quick data retrieval techniques like indexing, query processing and concurrency control methods are revealed. The paper provides vital insights to appraise the efficiency of the structured database in the unstructured environment, particularly when both consistency and scalability become an issue in the working of the hybrid transactional and analytical database management system.

Automated Information System "Distribution of the Teaching Load of the Teacher"

This article discusses the development of an automated information system "Distribution of teaching load of the teacher" based on a relational data model. Existing modern software products for planning the teaching load of a teacher are a commercial product of universities or private organizations. They have many additional functions that are not entirely necessary for a particular university. Therefore, there is a need to create its own automated system for distributing the teaching load of a teacher, which will be easy to use and automatically generates reporting documents in exact accordance with the forms of the university's reporting documentation. The proposed automated information system "Distribution of the teaching load of the teacher" uses a relational data model, since such a model allows information to be represented using interrelated tables in which records are unique. The need to create this system is to save the time of the head of the department, who are responsible for checking the correctness of the distribution of the annual teaching load between teachers. This software product is a logically complete product and ready to use. In the future, it is planned to create a platform for the schedule also for other reporting documents related to the reports of the department and simplifying their preparation. The fact that this system is a separate module allows you to use it in any university. The required data is loaded by the reporting data compiler. All reports are generated in MS Excel format and can be used for further analysis and processing.

Mapping of the descriptive logic into RDF using binary relational data model

This paper is dedicated to the data integration problem. To establish relationships between data models is one of the key tasks in this solution. The descriptive logic and the relational data model are at the heart of a study. They have been used to create a mapping method on the theoretical level. The binary relational data model has been developed as a part of a mapping method. The previous studies are continued in this paper to prove on practice a mapping creation method between the descriptive logic and the binary relational data model. The method uses the binary relational data model as an integrating model. This paper continues the previous research of practical implementation of the mapping creation between the descriptive logic and the binary relational data model. The task to prove the theoretical mapping method on practice was formulated. A question how to map the binary relational data model into RDF-triples was considered. A brief overview of the R2R ML conversion tool was given. Triple maps were created to convert a conceptual information model of descriptive logic into RDF triplets with the help of R2R ML. Also, triples maps are described to convert basic mapping mechanisms into RDF with the help of R2R ML.

PERANCANGAN DESAIN BASIS DATA SISTEM INFORMASI GEOGRAFIS TANAH PENDUDUK DENGAN MENERAPKAN MODEL DATA RELASIONAL ( STUDI KASUS : DESA TUMBANG MANTUHE KABUPATEN GUNUNG MAS PROVINSI KALIMANTAN TENGAH )

Database design is a data design process that is used to support the operational activities and goals of organizations and agencies. The use of databases on the geographic information system of residents' lands makes it possible to store, change, and display all data quickly and easily. One of the factors that become a problem in database design is the point of view of seeing data that varies between designers, programmers, and end-users. Therefore we need a methodology in good database design by applying procedures, techniques, tools, and documentation. The method used in this study used the Research and Development (R&D) method, while the database design method used the Database Life Cycle (DBLC) method. The research variables were database design for the geographic information system of resident land with a relational data model. Research aspects include conceptual design, logical design, and physical design. The final result of this research is to produce 10 types of conceptual entities, produce a relationship diagram of the ten logical entities, and produce a physical design consisting of user_admin, user_pengguna, data_desa, data_kecamatan, data_kabupaten, jenis_tanah, data_penduduk, data_buku_c, data_mutasi, and data_sppt tables.

Storing Hypergraph-Based Data Models in Non-hypergraph Data Storage and Applications for Information Systems

Data structures and especially the relationship among the data entities have changed in the last couple of years. The network-like graph representations of data-model are becoming more and more common nowadays, since they are more suitable to depict these, than the well-established relational data-model. The graphs can describe large and complex networks — like social networks — but also capable of storing rich information about complex data. This was mostly of relational data-model trait before. This also can be achieved with the use of the knowledge representation tool called “hypergraphs”. To utilize the possibilities of this model, we need a practical way to store and process hypergraphs. In this paper, we propose a way by which we can store hypergraphs model in the SAP HANA in-memory database system which has a “Graph Core” engine besides the relational data model. Graph Core has many graph algorithms by default however it is not capable to store or to work with hypergraphs neither are any of these algorithms specifically tailored for hypergraphs either. Hence in this paper, besides the case study of the two information systems, we also propose pseudo-code level algorithms to accommodate hypergraph semantics to process our IS model.

Graph Database Management Systems

Nowadays, the increased amount and complexity of connected data stimulated by the appearance of social networks has shed a new light on the importance of managing such data, especially handling information about the connections. The most natural way of representing connected data is to represent them as nodes connected with relationships forming a graph. The idea of storing data as a set of nodes and edges comprising a graph was implemented in various forms in data models used in the past. The network data model, developed in late 1960s, can be considered as the first data model, which most accurately incorporated this idea. However, it was not long before the relational data model appeared, and took over the entire database market for years, which it dominates even nowadays. Therefore, the objective of this article is to give a timeline overview of developed graph data storage solutions in order to gain insight into past, present and future trends of GDBMSs. Additionally, the most influential factors and reasons for changes in trends in GDBMSs' usage will be analyzed.