Relational Database Structure Research Articles

PRDH and IMPQ 1800–1849 Quebec Historical Family Reconstitution. Content, Design and Biographical Completeness

Since 1966, the Programme de recherche en démographie historique (PRDH) has worked to create comprehensive genealogical data of the Quebec population. The PRDH longitudinal database, the Registre de la population du Québec ancien (RPQA), draws upon the French Catholic parish registers of the St. Lawrence Valley as its main source material. This family reconstitution covers the French Catholic population of Quebec up to 1799, along with deaths after 1800 of persons born before 1750. Subsequent partnerships with l’Institut Généalogique Drouin, FamilySearch and Ancestry as well as collaboration on the 2011–2017 Infrastructure intégrée des microdonnées historiques de la population du Québec (1621–1965) (IMPQ) project enabled the PRDH to continue efforts to reconstitute the French Catholic population up to 1849. Despite these advances, pushing family reconstitution forward to the mid-19th century has forced the PRDH team to reckon with the increasingly mixed and geographically mobile Quebec population of the 19th and early 20th centuries. This article describes the content and design of the RPQA database, detailing the structure of the RPQA relational database and the breadth of variables available for data management and analysis. It then describes features of the IMPQ extension of family reconstitution from 1800 to 1849, including observational protocols necessary to use these data and consideration of data completeness after 1800. At the same time, the article addresses the fundamental question, "what is my population?" as part of a broader reflection upon the target population encompassed by these data.

Simulation of Database Interactions for Early Validation of Digitized Enterprise Processes

Digitized enterprise processes often encompass interaction with relational databases. Describing and simulating large-scale and complex processes on different abstraction levels lead to the use of tools and methods of Model-based Systems Engineering. In practice, current entity-relationship modeling approaches solely enable modeling relational database structure without simulation of database interactions at an early development stage. However, in general, it is known that early validation improves common understanding and communication in the development team and reduces the risk of design flaws. This paper presents an approach for model-based enterprise process digitization and a previously developed and now enhanced broker-based SysML Toolbox for integrating real relational databases into SysML simulations. The approach comprises status quo documentation concerning enterprise processes, development of digitized processes and required relational database structures as well as validation of digitized processes using the SysML Toolbox.

STRUCTURAL MODEL OF THE SYSTEM OF DEVELOPMENT OF METHODOLOGICAL COMPETENCE OF IT-DISCIPLINE TEACHERS ON THE BASIS OF CONTINUING EDUCATION

The article considers the creation of structural model for the system of development of methodological competence of IT-discipline teachers based on continuing education with the description of the structure of microservices subsystems. To implement the proposed conceptual model the paper proposes a software architecture based on the use of classical service-oriented design pattern "Model-View Separation" (separation of model objects from the graphical interface objects with the user) and provides for interaction with the database, the composition of its main packages is detailed. Logical and physical service-oriented models of basic classes of objects of subject area and auxiliary objects (services) have been developed. The article also proposes a relational database structure based on the use of metadata tables, directories, and operational data in a relational database management system environment. Methods and mechanisms for data protection and replication are proposed and justified, considering the specifics of system operation in higher education institutions. The article aims to develop insurgents and mechanisms of creation of information technology improvement of the system of higher education and creation and operation of integrated flexible software tools to support the mixed system of organization of educational process, as well as increasing the effectiveness of the introduction of a mixed system for the organization of the educational process on the basis of the use of the latest technical means of training and documentation, ensuring free access of students to teaching and methodological resources, сontent and criteria for the assessment of knowledge in disciplines and modules, data recording, and partial compensation for the increased workload of teachers and staff through the automation of assessment, registration and assessment processes. A task-oriented model for managing technical problems in the implementation of the information system for the development of teachers' methodological competence is also proposed, and a conceptual framework for managing these problems has been developed from the perspective of considering projects as a set of objects and subjects. Technical problems in projects are shown to be obstacles to moving in the right direction, created by random events, uncertainties, and changes. A mathematical model of the change in resistance value caused by technical problems has been developed and methods to counteract these problems have been proposed.

Networking for Historical Justice: The Application of Graph Database Management Systems to Network Analysis Projects and the Case Study of the Reparation Movement for Japanese Colonial and Wartime Atrocities

Using the reparation movement for Japanese colonial and wartime atrocities as a case study, this paper explores the applicability of graph database management systems to network analysis research and teaching in the field of digital humanities. Since the late 1980s, Asian victims of Japanese colonial and wartime atrocities (such as the infamous “comfort women” system) began to sue the Japanese government and corporations with the help of local and Japanese lawyers and activists. This paper uses the plethora of publicly available court materials produced by the movement to study social networks in this transnational historical justice movement and illustrate how graph database management systems can upgrade traditional network analysis methodologies in digital humanities. By inputting the data about lawsuits and lawyers in the movement into graph database applications like Neo4j and GraphXR, the paper demonstrates the advantages of managing network data in graph database structure in terms of scalability, modifiability, intuitive visibility, query efficiency, and analysis potential over relational database structure, which is the mainstream in network analysis research.

Database Management System in Accounting: Assessing the Role of Internet Service Communication of Accounting System Information

Data management is part of information resource management which includes all activities that ensure that company data resources are accurate, up-to-date, and safe from tampering, and are also available to users and the company. This study aims to find out about the role of concept database management in managing large volumes of company data. The result showed that data management activities include data collection, integrity, and testing, storage, maintenance, security, organization, retrieval. Meanwhile, the database structure includes hierarchical database structure, network database structure, and relational database structure.

Using Blockchain in Cloud Computing to Enhance Relational Database Security

Cloud computing has now become a very standardised concept in our society. However, many modern applications need a better level of security that includes saving data from internal breaches. Thus, cloud databases need effective security mechanisms to keep track of data modifications. This paper will introduce the enhanced structure of cloud relational database (RDB) based on blockchain technology (BC) named BC over cloud-RDB. Through a self-verification mechanism, it enables the client to detect and prevent erroneous RDB manipulation. We proposed two systems to improve cloud-RDB namely, agile BC-based RDB and secure BC-based RDB. Both are distributed among several cloud service providers based on the Byzantine Fault Tolerance consensus. Additionally, both rely on linking records to each other using the SHA-256. At the same time, secure BC-based RDB uses a proof-of-work consensus to make data offensive operation impossible. On the basis of performance of both systems’ and security analysis, the agile BC-based RDB is highly suggested for the high throughput database. On the other hand, the secure BC-based RDB is recommended for RDB that contains sensitive data and low throughput performance. The improved RDB is flexible and can be operated according to the data owner’s specifications.

Data Structure Comparison Between MySql Relational Database and Firebase Database NoSql on Mobile Based Tourist Tracking Application

Tracking application is widely used to help outdoor activities. One of them is used to help tourists who do tourist destinations in group activities. Tourist tracking application requires data on the position of tourists on earth. This coordinate data can be obtained using latitude and longitude data from GPS (Global Positioning System). Coordinate latitude and longitude position of tourists from time to time are stored in a database. Database Selection for media storage will determines the level of speed and ease in accessing data. There are some differences in designing the structure of the MySql and Firebase databases. Relational Database begins with identification of entities involved in the system. One entity with another entity is related and has a cardinality level of the relationship. Relational database implementation in the form of tables in normal forms that are interconnected. Data will be stored in columns and rows. Normalization of tables causes high query computation when calling data that involves many tables. Firebase, which is one of the NoSql databases, in building data structures is stored in JSON objects. JSON tree structures usually consider the display of information that will be presented to users. So that the generated JSON tree has high efficiency and speed in processing data. In this study a comparison between the design of the relational database structure, namely MySql and NoSql Firebase database structure was developed. Firebase is more power full for the development of applications which update data in realtime and and handle a lot of coordinate data such as tourist tracking applications. Applications that do not have complex data relations such as tourist tracking applications are more suitable to use firebase than using MySQL.

The Student Study Experience – Analysing Student Study Choices

As higher education institutions increasingly teach online and offer greater levels of choice to students (over which modules to study, in which order to study, and how long to extend study before qualification) new challenges are introduced. One of these challenges is how to maintain an understanding of the student experience. This understanding is necessary to provide feedback to both students and faculty, and institutionally for the continued enhancement of quality. This paper is the first attempt at providing a narrative describing one approach to this challenge and the experience within a large distance learning University. It demonstrates a new approach to data is key to enabling the analysis of student study pathways. For many years, this University has offered great flexibility of study and as wide a study choice as it is possible to offer with conventional modules. By design, the Institution holds high levels of data for all student study. However, whilst it is possible to create bespoke queries, we found that this has been insufficient to readily enable analysis of the student experience. By moving from a traditional relational database structure to a multi-model database, many of the difficulties are resolved. In this paper, we report on this approach and describe next steps, including the potential to apply machine learning algorithms and test other data theories like that of Markov Chains.

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering.

Science relies on increasingly complex data sets for progress, but common data management methods such as spreadsheet programs are inadequate for the growing scale and complexity of this information. While database management systems have the potential to rectify these issues, they are not commonly utilized outside of business and informatics fields. Yet, many research labs already generate "medium sized", low velocity, multi-dimensional data that could greatly benefit from implementing similar systems. In this article, we provide a conceptual overview explaining how databases function and the advantages they provide in tissue engineering applications. Structural fibroblast data from individuals with a lamin A/C mutation was used to illustrate examples within a specific experimental context. Examples include visualizing multidimensional data, linking tables in a relational database structure, mapping a semi-automated data pipeline to convert raw data into structured formats, and explaining the underlying syntax of a query. Outcomes from analyzing the data were used to create plots of various arrangements and significance was demonstrated in cell organization in aligned environments between the positive control of Hutchinson-Gilford progeria, a well-known laminopathy, and all other experimental groups. In comparison to spreadsheets, database methods were enormously time efficient, simple to use once set up, allowed for immediate access of original file locations, and increased data rigor. In response to the National Institutes of Health (NIH) emphasis on experimental rigor, it is likely that many scientific fields will eventually adopt databases as common practice due to their strong capability to effectively organize complex data.

Building a database for curriculum mapping and analytics

This article was migrated. The article was marked as recommended. Curriculum mapping of an outcomes-based programme using a database was developed using a relational database structure, and it functions as a searchable database by the use of keywords. Factors such as the framework of the programme, the database entity relationship diagram (ERD), benchmarking, terminology and nomenclature, analytics and integration with the learning management system requires careful consideration before implementation. Built into the structure of the curriculum database are the analytics features which identifies the curricula data using defined keywords. This enables staff and students to search through any programme or subject of interest to track a subject or keyword to the point of delivery with the use of the analytics feature. This results in the curricula information being transparent for all stakeholders, ensuring curriculum mapping and blueprinting of assessments are readily available.This paper reports on the implementation of a university-wide curricula database which includes multiple undergraduate and postgraduate programmes, including chronological versions of a programme at an institution with diverse health professions programmes, including medicine, dentistry, pharmacy. Additionally, this paper outlines the steps to design the curricula database, the development of the framework of the database and the analytics, the challenges in implementation, the results that can be obtained from such a database and the lessons learnt.

Building a database for curriculum mapping and analytics

This article was migrated. The article was marked as recommended. Curriculum mapping of an outcomes-based programme using a database was developed using a relational database structure, and it functions as a searchable database by the use of keywords. Factors such as the framework of the programme, the database entity relationship diagram (ERD), benchmarking, terminology and nomenclature, analytics and integration with the learning management system requires careful consideration before implementation. Built into the structure of the curriculum database are the analytics features which identifies the curricula data using defined keywords. This enables staff and students to search through any programme or subject of interest to track a subject or keyword to the point of delivery with the use of the analytics feature. This results in the curricula information being transparent for all stakeholders, ensuring curriculum mapping and blueprinting of assessments are readily available.This paper reports on the implementation of a university-wide curricula database which includes multiple undergraduate and postgraduate programmes, including chronological versions of a programme at an institution with diverse health professions programmes, including medicine, dentistry, pharmacy. Additionally, this paper outlines the steps to design the curricula database, the development of the framework of the database and the analytics, the challenges in implementation, the results that can be obtained from such a database and the lessons learnt.

BACTOME-a reference database to explore the sequence- and gene expression-variation landscape of Pseudomonas aeruginosa clinical isolates.

Extensive use of next-generation sequencing (NGS) for pathogen profiling has the potential to transform our understanding of how genomic plasticity contributes to phenotypic versatility. However, the storage of large amounts of NGS data and visualization tools need to evolve to offer the scientific community fast and convenient access to these data. We introduce BACTOME as a database system that links aligned DNA- and RNA-sequencing reads of clinical Pseudomonas aeruginosa isolates with clinically relevant pathogen phenotypes. The database allows data extraction for any single isolate, gene or phenotype as well as data filtering and phenotypic grouping for specific research questions. With the integration of statistical tools we illustrate the usefulness of a relational database structure for the identification of phenotype–genotype correlations as an essential part of the discovery pipeline in genomic research. Furthermore, the database provides a compilation of DNA sequences and gene expression values of a plethora of clinical isolates to give a consensus DNA sequence and consensus gene expression signature. Deviations from the consensus thereby describe the genomic landscape and the transcriptional plasticity of the species P. aeruginosa. The database is available at https://bactome.helmholtz-hzi.de.

Онтологический метод проверки семантической несогласованности реляционных баз данных и официальных документов

The purpose of this work is to develop a method for applying the description logic formalism to automate the process of identifying semantic conflicts between organization documents and the relational database structure. The ontological method for verifying the consistency of entities and relations data of the subject domain and their relational representation were proposed. It provides rules for describing the structured data of organization's official documents in the form of axioms and statements of the SROIQ (D) description logic. This method allows revealing inconsistencies caused by the difference of data types, permitted values and acceptable values of the same attribute in ontology representations of database and entity and relations data of subject domain. The efficiency of proposed method were evaluated by means of special experimental data, which included a set of conceptual entity-relationship schemas and a set of service tables from documents.

A simplified relational database schema for transformation of BIM data into a query-efficient and spatially enabled database

Abstract With the rising adoption of BIM in the AECO (Architecture, Engineering, Construction and Owner-operator) industry, BIM content is increasingly more complete and valuable. Unfortunately, the data is largely locked inside the respective BIM authoring tool with limited facility for users to perform queries beyond simple queries on objects and their properties. Even with the use of open data exchange format such as IFC (Industry Foundation Classes), getting the data out of BIM is still not an easy task. This research focuses on defining a schema and transformation rules to bring BIM data into a form that is easily queried. The schema is defined using popular relational database structure following an established star schema model that is well-defined within the data warehouse domain. The primary aim of the concept is to allow flexible and efficient queries into the BIM data using standard SQL that removes restrictions on predefined queries, effectively transforming BIM data into an open and queryable database. Another major contribution of this research is the significant potential for supporting spatial queries. This is a critical feature often neglected in the current approach to BIM-based databases. This paper presents the integration of spatial operations into standardized SQL queries making the BIM data accessible for wide ranges of query capabilities. Such feature will allow much better visibility into BIM data for better decision-making processes.

The HITRAN2016 molecular spectroscopic database

This paper describes the contents of the 2016 edition of the HITRAN molecular spectroscopic compilation. The new edition replaces the previous HITRAN edition of 2012 and its updates during the intervening years. The HITRAN molecular absorption compilation is composed of five major components: the traditional line-by-line spectroscopic parameters required for high-resolution radiative-transfer codes, infrared absorption cross-sections for molecules not yet amenable to representation in a line-by-line form, collision-induced absorption data, aerosol indices of refraction, and general tables such as partition sums that apply globally to the data. The new HITRAN is greatly extended in terms of accuracy, spectral coverage, additional absorption phenomena, added line-shape formalisms, and validity. Moreover, molecules, isotopologues, and perturbing gases have been added that address the issues of atmospheres beyond the Earth. Of considerable note, experimental IR cross-sections for almost 300 additional molecules important in different areas of atmospheric science have been added to the database. The compilation can be accessed through www.hitran.org. Most of the HITRAN data have now been cast into an underlying relational database structure that offers many advantages over the long-standing sequential text-based structure. The new structure empowers the user in many ways. It enables the incorporation of an extended set of fundamental parameters per transition, sophisticated line-shape formalisms, easy user-defined output formats, and very convenient searching, filtering, and plotting of data. A powerful application programming interface making use of structured query language (SQL) features for higher-level applications of HITRAN is also provided.

Software Mechanisms for Scientometrical Data Aggregation Based on Ontological Representation of the Relational Database Structure

Software Mechanisms for Scientometrical Data Aggregation Based on Ontological Representation of the Relational Database Structure

English

Proteins are the building blocks of cells of living creatures of all kingdoms. Due to pivotal role of protein structures in understanding evolutionary relationships and inferring their functions, the need to have a publically available databank was recognized and this results in establishment of protein data bank. This is a repository of protein structures in form of text files. Understanding and accessing protein structures in plain text files is very cumbersome job and a little bit difficult to understand the data as well. Several struggles have been made to transform protein structures of protein data bank in relational databases but all available relational databases of protein structures till now either do not provide complete information about the protein structures or they are not convenient to. Relational Protein Databank, presented in this paper, is a repository of all protein structures of protein databank stored in tables. A web interface has been provided to access various elements of protein structures in much more user friendly way. The structure of relational protein database has made data selection, insertion, deletion and editing very easy. RPDB is developed in MySQL which is an open source relational database management system.

Development of Advanced Technologies (AT) in Green Transport Corridors

The paper presents tendency analysis for advanced technologies. Advanced technologies – is an area having different acceptability and local adaptation levels in different countries, thus it is particularly important to be acquainted with its application possibilities and techniques. Contributing to a more efficient use of existing transport infrastructure, AT becomes a powerful tool in improving mobility conditions and optimizing transport activities. The importance of advanced technologies application in different modes of transport is examined. The functionality of advanced technologies application in different modes of transport is indicated and all elements of the transport system are taken into account. Relational database structures are provided; aspects of information and communications, multi-stage transport chains are distinguished. The optimal functionality of road transport and port interaction is particularly important in freight transportation by green transport corridors where transport modes are combined and activities are coordinated. The carried-out analysis of advanced technologies application possibilities in freight transportation by green transport corridors indicated that issues must be explored and solutions are to be suggested. On the basis of these solutions, it is possible to make the efficient use of freight delivery (exportation) by road transport to (from) the seaport. For this purpose, efficiency analysis model of road transport and port interaction while developing freight transportation by green corridors is suggested. The developed model provides an opportunity to evaluate how efficiently road transport is employed in the green corridors, where cargo is transported to/from the seaport.

A System Design for Facilitating Human Resource Decisions in Small and Medium Sized Enterprises in Turkey

Currently, to keep the competitive edge, firms focus on the improvement of the decision making and use different management information systems to leverage the process. In this study, it has been designed an information system which aims to support the management of human resources in the small and medium sized enterprises in Turkey. To do this, a group of human resource key point indicators have been determined for a system design which includes Mysql- and Java-based Hibernate Criteria Api, search algorithm, relational database, JSF(java server faces) Framework and Primefaces structures as methodology. It has been demonstrated by sample user interface snapshots and analysis of the system benefits that the system would serve decision makers in a number of areas including training, performance, efficiency, workforce and working time supported by its user friendly characteristics such as; real time analysis, decision making opportunities and flexibility of accessibility it offers to small and medium sized enterprises.

A Relational Database Structure for Linking Air Pollution Levels with Children’s Respiratory Illnesses

Pollutants' data, meteorological data and medical data feeds the relational database with information from vulnerable urban areas (i.e., Targoviste and Ploiesti), which will help the running of algorithms between air quality, meteorology and health effects and later use of forecasted outputs to forecast health effects. Several computer-based tools were developed to facilitate the population of the database with specific data from various sources. One of these tools allows the automatic capturing of pollutants’ concentrations from web-based official sources. The relational database structure integrates the fields for the required variables in the attributed data tables (PM 2.5 and carried compounds/metals sub-database, meteorological sub-database and medical sub-database). The main criteria in selecting the respiratory illnesses that are linked to atmospheric pollution for children are the wheezing. The medical database contains as main fields: the number of wheezing episodes, number of asthma attacks (with hospitalization), the response to inhalation medication, medication controller, eosinophil count, serum level of E immunoglobins (lgE), and residential address and school/kindergarten address of the children. The presented database structure and adjacent tools are expected to improve the current monitoring methodology of air pollutants, mainly respirable dusts, and their content in various compounds in correlation with children’s health.