Relational Database Schema Research Articles

Enhancing Healthcare Informatics: Integrating Category Theory Reasoning into OMOP-CDM Ontology Model.

The task of managing diverse electronic health records requires the consolidation of data from different sources to facilitate clinical research and decision-making support, with the emergence of the Observational Medical Outcomes Partnership - Common Data Model (OMOP-CDM) as a standard relational database schema for structuring health records from different sources. Working with ontologies is strongly associated with reasoners. Implementing them over expansive and intricate Ontologies can pose computational challenges, potentially resulting in slow performance. In this paper, we propose the implementation of a new reasoner based on categorical logic over a translation of OMOP-CDM into an ontology model. This enables enhancements to the efficiency and scalability of implementing such models.

APPOINTMENT MAKER USING COMPUTERIZED VOICE

The Appointment Maker Using Computerized Voice is a novel system designed to streamline the process of scheduling appointments in healthcare settings through the integration of voice recognition and natural language processing technologies. By leveraging speech-to-text and text-to-speech capabilities, the system enables users to interact with the appointment booking interface using spoken commands, eliminating the need for manual input and enhancing accessibility for individuals with diverse technological proficiencies. This intuitive interface simplifies the appointment scheduling process, allowing users to book, reschedule, or cancel appointments with ease. Furthermore, the Appointment Maker employs machine learning models to understand and interpret user queries, providing accurate responses and assistance in real-time. By leveraging pre-trained language models and fine-tuning them on domain-specific data, the system demonstrates robust performance in understanding diverse user inputs and generating contextually relevant responses. This capability enhances user experience by providing personalized and timely assistance, akin to interacting with a human receptionist.The Appointment Maker features a backend database for storing and managing appointment and user information, ensuring data integrity, security, and efficient resource utilization. The relational database schema facilitates seamless coordination between users, healthcare providers, and administrative staff, enabling efficient scheduling and management of appointments. Overall, the Appointment Maker Using Computerized Voice represents a significant advancement in healthcare administration, offering a user-friendly and efficient solution for appointment scheduling while improving accessibility and patient experience. Key Words: Computerized Voice ,Natural Language Understanding (NLU), Speech to Text, Text to Speech.

An empirical hybrid strategy for NoSQL database distribution

A case study of a pharmaceutical distribution company with a relational database that is migrated to a document-oriented NoSQL database for which a hybrid distribution strategy based on fragmentation and replication is implemented. The legacy relational database schema was thoroughly analyzed and evaluated to determine the collections and documents needed to move all the data and leverage the capabilities of the document-based database. In addition, a hybrid data distribution strategy was designed to effectively balance the performance, scalability, and fault tolerance of the system. Finally, integrated operational tests were performed on the distributed system nodes to verify that they function properly and ensure their availability for the company's operations.

A Unified Data Architecture for Assessing Motor Symptoms in Parkinson's Disease.

The diagnosis and treatment of Parkinson's disease depend on the assessment of motor symptoms. Wearables and machine learning algorithms have emerged to collect large amounts of data and potentially support clinicians in clinical and ambulant settings. However, a systematical and reusable data architecture for storage, processing, and analysis of inertial sensor data is not available. Consequently, datasets vary significantly between studies and prevent comparability. To simplify research on the neurodegenerative disorder, we propose an efficient and real-time-optimized architecture compatible with HL7 FHIR backed by a relational database schema. We can verify the adequate performance of the system on an experimental benchmark and in a clinical experiment. However, existing standards need to be further optimized to be fully sufficient for data with high temporal resolution.

Method of generating ORM models software code based on relational database schemes

Abstract. Problem. Databases and data stores are an important part of any system, regardless of the field of application. It is at this level that all system information is stored, such as a list of online store products, user personal data, system configuration parameters, etc. In addition, they allow to structure information in the desired format. Although the use of databases is associated with obvious advantages, it has some disadvantages, in particular the process of designing them and integrating their software code is labor-intensive and time-consuming. This problem is usually attempted to be circumvented by using ORM libraries, which provide a convenient programming interface for performing basic queries. But the process of setting up an ORM library including developing ORM models still takes a lot of time. Goal. The purpose of the work is to develop an algorithm for the automatic generation of software code for ORM models based on the selected ORM library and the data scheme presented in the form of a configuration file. To achieve the goal, it is necessary to establish the optimal representation of the data scheme in text format, to determine the structure of the data configuration scheme and to describe all stages of the generation of software code for ORM models. Methodology. System approach, analysis of existing methods of visual design, formats of text representation of configuration data and methods of configuration data storing. Results. The developed method for software code generation for the selected ORM library based on the scheme of the relational database provides the user with the opportunity to obtain a qualitatively designed software code with minimal time expenditure. Originality. The developed method implements a unique approach which allows to create program code for various ORM libraries, supports the syntax and features of a specific programming language, and provides work with data schemas from various relational databases. Practical value. Developed generation algorithm can be used as part of the software in which the automated process of preparing the data schema in the appropriate text formatted form will be implemented. As a result, such a web-application will represent a platform for working with the data layer for IT professionals.

On the Complexity of Binary Polynomial Optimization Over Acyclic Hypergraphs

In this work, we advance the understanding of the fundamental limits of computation for binary polynomial optimization (BPO), which is the problem of maximizing a given polynomial function over all binary points. In our main result we provide a novel class of BPO that can be solved efficiently both from a theoretical and computational perspective. In fact, we give a strongly polynomial-time algorithm for instances whose corresponding hypergraph is beta -acyclic. We note that the beta -acyclicity assumption is natural in several applications including relational database schemes and the lifted multicut problem on trees. Due to the novelty of our proving technique, we obtain an algorithm which is interesting also from a practical viewpoint. This is because our algorithm is very simple to implement and the running time is a polynomial of very low degree in the number of nodes and edges of the hypergraph. Our result completely settles the computational complexity of BPO over acyclic hypergraphs, since the problem is NP-hard on alpha -acyclic instances. Our algorithm can also be applied to any general BPO problem that contains beta -cycles. For these problems, the algorithm returns a smaller instance together with a rule to extend any optimal solution of the smaller instance to an optimal solution of the original instance.

Translating the Observational Medical Outcomes Partnership - Common Data Model (OMOP-CDM) Electronic Health Records to an OWL Ontology.

The heterogeneity of electronic health records model is a major problem: it is necessary to gather data from various models for clinical research, but also for clinical decision support. The Observational Medical Outcomes Partnership - Common Data Model (OMOP-CDM) has emerged as a standard model for structuring health records populated from various other sources. This model is proposed as a relational database schema. However, in the field of decision support, formal ontologies are commonly used. In this paper, we propose a translation of OMOP-CDM into an ontology, and we explore the utility of the semantic web for structuring EHR in a clinical decision support perspective, and the use of the SPARQL language for querying health records. The resulting ontology is available online.

Transforming OpenAPI Specification 3.0 documents into RDF-based semantic web services

Web services are provided with documents that at the very least specify the endpoint, input parameters, and output or response of each operation to expose their capabilities. This should be considered through an understandable format for humans and/or machines. In the Representational State Transfer (REST) architectural style, the OpenAPI Specification (OAS) is used as a reference to create web service descriptions. However, it only supports syntactic interoperability, leading to the incapability of supporting the automated selection process. To overcome this, OAS documents must be enhanced by including semantics to each resource to provide “understandable” services. Therefore, this study aims to develop a system capable of transforming resources in OAS documents into RDF-based semantic web services. To begin, a relational database schema based on the OAS structure is created to store all objects in the OAS document. The published open-linked vocabulary was then used to create the ontology, which maps resources and their relationships on the RDF data model. To build RDF-based semantic web services, R2RML was used to generate the relational database model into triple RDF. The proposed system was also tested through prototyping and using a dataset of 106 OAS documents, which were downloaded from APIs.guru between 5–10 May 2021. The number of triple RDFs generated per document varied with resource rate. An OAS document generates 36 to 16,505 triple RDF in a dataset. The end product was a triple RDF knowledge base maintained by a graph management database. It is now possible to find service operations, input and output parameters, and service composition requirements utilizing the repository semantic web services using SPARQL. On the other hand, the use of relational databases to store OAS resources increased reuse efficiency by approximately 48%, owing to service developers designing interoperability between uniform parameter services, which were then used as input and output.

ABSTRACT MODEL OF INFLUENCE OF MALICIOUS OF SOFTWARE AND METHOD OF ENSURING THE FAILURE RESISTANCE OF SPECIALIZED INFORMATION TECHNOLOGIES

The proposed abstract model of the effects of malicious software (SDR) allows us to consider the objects of the computer system that may be affected by SDR and computer attacks. Therefore, it was used as a basis for a new method of ensuring the resilience of specialized IT in the face of SDR and computer attacks. As a result, the application of the developed method is carried out in a system that has mechanisms for restructuring and uses redundancies. A feature of the main steps of the developed method according to the parametric control of program file integrity is the possibility of its application to a group of program files that do not have a fixed checksum and thus it expands the possibilities of the known method of detecting. Compared with the known application of this method, in previous work, this method could not be used to control the integrity of a certain group of executable files that have a heterogeneous internal structure. This group includes files of type mde, which are obtained when compiling programs written in MS Access. Their feature is the fact that they have a complex internal structure, which includes, in addition to program code, structures that are elements of the database, such as tables, indexes, relational database schema and others. This step of the method is designed for application in IP with increased fault tolerance and enhanced protection against RAM and computer attacks, namely in the second, local security loop integrated into specialized IT software. This is dictated by the fact that its implementation requires specific information about the parameters of the program file, which is unknown at the system level, but known locally, as it is information obtained in the design and implementation of this part of specialized IT as a whole. Therefore, the scope of the SCR detection method based on checksum calculation for files with volatile checksums as a step of the IT fault tolerance method has been expanded. As a result, the application of the developed method is carried out in a system that has mechanisms for rebuilding and uses redundancies. To study the developed method, a method of evaluating its effectiveness in terms of redundancy and redundancy has been developed. Experimental studies and evaluation calculations confirm the effectiveness of the developed method of ensuring the resilience of IT in the face of SDR and computer attacks.

For fuzzy classification of databases with FCQL

Business information systems have extensive databases that are mainly managed in relational databases. What is often missing are automated procedures to analyze these inventories without major restructuring. Therefore, we extend the relational database schema with a context model for fuzzy classification. Based on this, we develop the fuzzy classification query language, FCQL, which allows fuzzy queries to the extended database schema using linguistic variables and converts them into SQL calls to the database. With this we give the user a data mining tool so that he can start extended queries on his databases based on a predefined fuzzy classification and obtain an improved basis for decision-making.

Организация хранения «открытых» наборов атрибутов сущностей в реляционных базах данных

Relations are practically implemented by database management systems in the form of two-dimensional tables. In this regard, certain difficulties arise in the development of relational database schemas, in which it is necessary to represent objects with an alterable (open) set of attributes. The article proposes a solution to this problem by including special relations in the scheme - relations of properties directory. Properties directory allow replenishing the sets of object attributes without changing the structure of the database. Examples of the practical use of properties directory in the development of database schemas of two information systems are presented.

An entity-relationship model of the flow of waste and resources in city-regions: Improving knowledge management for the circular economy

Waste and resources management is one of the domains where urban and regional planning can transition towards a Circular Economy, thus slowing environmental degradation. Improving waste and resources management in cities requires an adequate understanding of multiple systems and how they interact. New technologies contribute to improve waste management and resource efficiency, but knowledge silos hinder the possibility of delivering sound holistic solutions. Furthermore, lack of compatibility between data formats and diverse definitions of the same concept reduces information exchange across different urban domains. This paper addresses the challenge of organising and standardising information about waste and resources management in city regions.Given the amount and variety of data constantly captured, data models and standards are a crucial element of Industry 4.0. The paper proposes an Entity-Relationship Model to harmonise definitions and integrate information on waste and resources management. Furthermore, it helps to formalise the components of the system and their relationships. Semi-structured interviews with government officials, mobile app developers and academics provided insights into the specific system and endorsed the model. Finally, the paper illustrates the translation of the ERM into a relational database schema and instantiates Waste Management and industrial Symbiosis cases in Buenos Aires (ARG) and Helsingborg (SWE) to validate its general applicability. The data model for the Circular Flow of Waste and Resources presented here enhances traditional waste management perspectives by introducing Circular Economy strategies and spatial variables in the model. Thus, this research represents a step towards unlocking the true potential of Industry 4.0.

A PostgreSQL Tripal solution for large-scale genotypic and phenotypic data.

Researchers are seeking cost-effective solutions for management and analysis of large-scale genotypic and phenotypic data. Open-source software is uniquely positioned to fill this need through user-focused, crowd-sourced development. Tripal, an open-source toolkit for developing biological data web portals, uses the GMOD Chado database schema to achieve flexible, ontology-driven storage in PostgreSQL. Tripal also aids research-focused web portals in providing data according to findable, accessible, interoperable, reusable (FAIR) principles. We describe here a fully relational PostgreSQL solution to handle large-scale genotypic and phenotypic data that is implemented as a collection of freely available, open-source modules. These Tripal extension modules provide a holistic approach for importing, storage, display and analysis within a relational database schema. Furthermore, they embody the Tripal approach to FAIR data by providing multiple search tools and ensuring metadata is fully described and interoperable. Our solution focuses on data integrity, as well as optimizing performance to provide a fully functional system that is currently being used in the production of Tripal portals for crop species. We fully describe the implementation of our solution and discuss why a PostgreSQL-powered web portal provides an efficient environment for researcher-driven genotypic and phenotypic data analysis.

High density genotype storage for plant breeding in the Chado schema of Breedbase.

Modern breeding programs routinely use genome-wide information for selecting individuals to advance. The large volumes of genotypic information required present a challenge for data storage and query efficiency. Major use cases require genotyping data to be linked with trait phenotyping data. In contrast to phenotyping data that are often stored in relational database schemas, next-generation genotyping data are traditionally stored in non-relational storage systems due to their extremely large scope. This study presents a novel data model implemented in Breedbase (https://breedbase.org/) for uniting relational phenotyping data and non-relational genotyping data within the open-source PostgreSQL database engine. Breedbase is an open-source, web-database designed to manage all of a breeder’s informatics needs: management of field experiments, phenotypic and genotypic data collection and storage, and statistical analyses. The genotyping data is stored in a PostgreSQL data-type known as binary JavaScript Object Notation (JSONb), where the JSON structures closely follow the Variant Call Format (VCF) data model. The Breedbase genotyping data model can handle different ploidy levels, structural variants, and any genotype encoded in VCF. JSONb is both compressed and indexed, resulting in a space and time efficient system. Furthermore, file caching maximizes data retrieval performance. Integration of all breeding data within the Chado database schema retains referential integrity that may be lost when genotyping and phenotyping data are stored in separate systems. Benchmarking demonstrates that the system is fast enough for computation of a genomic relationship matrix (GRM) and genome wide association study (GWAS) for datasets involving 1,325 diploid Zea mays, 314 triploid Musa acuminata, and 924 diploid Manihot esculenta samples genotyped with 955,690, 142,119, and 287,952 genotype-by-sequencing (GBS) markers, respectively.

Cloud computing and semantic web technologies for ubiquitous management of smart cities-related competences

One of the biggest challenges in building sustainable smart cities of the future is skill management and development. Developing the digital skills of the municipalities’ workforce is crucial for all occupational profiles and specifically for those that are actively involved in the development and operation of digital services for a smart city. In this context, the current paper presents a semantically enhanced cloud-based IT approach which integrates learning pathways with competence management of personnel working as management and technical employees in a smart city municipality. The proposed approach combines a rule-based expert system with a semantically rich infrastructure in order to map skill gap diagnosis to required learning objects and, thus, to contribute in developing appropriate competences of smart city professionals. The semantic infrastructure of the learning platform consists of an ontology which encapsulates the appropriate knowledge and a rule-base for modeling the steps of an employee training process. In order to achieve efficiency in competence management the semantic model has been transformed into a relational database schema, which is further utilized by the system for the execution of useful queries. The paper presents the key modeling artifacts of the proposed approach and the architecture of the implemented CMUTE system.

Machado: Open source genomics data integration framework.

BackgroundGenome projects and multiomics experiments generate huge volumes of data that must be stored, mined, and transformed into useful knowledge. All this information is supposed to be accessible and, if possible, browsable afterwards. Computational biologists have been dealing with this scenario for more than a decade and have been implementing software and databases to meet this challenge. The GMOD's (Generic Model Organism Database) biological relational database schema, known as Chado, is one of the few successful open source initiatives; it is widely adopted and many software packages are able to connect to it.FindingsWe have been developing an open source software package named Machado, a genomics data integration framework implemented in Python, to enable research groups to both store and visualize genomics data. The framework relies on the Chado database schema and, therefore, should be very intuitive for current developers to adopt it or have it running on top of already existing databases. It has several data-loading tools for genomics and transcriptomics data and also for annotation results from tools such as BLAST, InterproScan, OrthoMCL, and LSTrAP. There is an API to connect to JBrowse, and a web visualization tool is implemented using Django Views and Templates. The Haystack library integrated with the ElasticSearch engine was used to implement a Google-like search, i.e., single auto-complete search box that provides fast results and filters.ConclusionMachado aims to be a modern object-relational framework that uses the latest Python libraries to produce an effective open source resource for genomics research.

THE INDEPENDENCE OF THE AXIOMATIC SYSTEM OF MULTIVALUED DEPENDENCIES IN RELATION (TABLE) DATABASES

Context. The complexity of understanding the concept of multivalued dependencies (when setting out their theoretical foundations, an axiomatic approach is used) in relational (table) databases leads to problems of their modeling, which in turn can cause a violation of data integrity. A partial solution to these issues is facilitated by the search for equivalent axiomatic systems of multivalued dependencies that are minimal in terms of the number and power of their components. This, in turn, requires establishing the equivalence of these axiomatic systems and proving the independence of their elements. The object of the study is the axiomatisations of multivalued dependencies.The purpose of the work is to establish the equivalence of two axiomatic systems of multivalued dependencies, one of which is minimal in terms of the number and power of components, and to prove the independence of specified axiomatics. Method. Set-theoretic and logical-algebraic methods are used in the construction of proofs. The equivalence of two axiomatic systems of multivalued dependencies is established classically: the relation of syntactic inference is considered and sequences of multivalued dependencies are constructed that are proofs of the rules of each axiomatics from the components of the other. To build proof of independence of the axiomatic system, models of relational schemes are proposed, such that for an axiom or rule whose independence is being proved, it is impossible to construct proof from set of other axioms or rules.Results. Equivalence of the axiomatisation of multivalued dependencies proposed by a group of scientists Beeri, Fagin and Howard and the Biskup’s axiomatisation of multivalued dependencies has been established. The independence of the Biskup’s axiomatic system is proved in the sense that without loss of completeness it is impossible to remove neither the only axiom nor none of the inference rules.Conclusions. The independence of the Biskup’s axiomatisation of multivalued dependencies, which has no more in number and power of components than other axiomatic systems of multivalued dependencies, is proved. Using such axiomatic system has advantages in the development of CASE-tools (Computer-Aided Software Engineering Tools), which include the implementation of reducing the relational database schema to the fourth normal form, and also, when manually designing a logical model of a relational database.

ПОРІВНЯННЯ SQL І NOSQL БАЗ ДАНИХ НА ПРИКЛАДІ ПРОЕКТУВАННЯ АФФІЛЕЙТ РЕПОРТ СИСТЕМ

Nowadays, due to the rapid development of social networks and the blogger culture, there is a tendency to use affiliate systems to promote their product. The Affiliate Reporting Service is a service offered to customers who want to analyze the affiliate systems' performance data. These systems are used by business executives and business owners to analyze ecommerce data and convert it into profit/expense data to adjust their business path further. This type of service includes data storage for all affiliates, data archive management, conversion of advertising campaigns, trend tracking, and more. These systems are based on large data sets that need to be stored correctly and safely stored and processed using database management systems. There are two major direction: SQL and NoSQL, relational and non-relational databases. The differences between them are how they are designed, what types of data they support, how they store information, how they support information security. A rigid relational database schema helps maintain the security and integrity of data when stored and modified. The lack of a rigid database schema and the need to change the entire structure of the table with a minimal change in the storage concept, make it easier to work with non-relational databases and subsequently support them, but it also has its disadvantages. It is important to understand that the tasks are different and the methods for solving them are also different; Choosing a database and database management system is a complex multi-parameter task and is one of the most important steps in developing such applications. Properly selected database will reduce the monetary and time costs associated with the development of the software, as well as facilitate system support in the future. The purpose of the article is to compare relational and non-relational databases by different metrics used in Affiliate Reporting Systems Design. In particular, a performance analysis was conducted on the performance of various operations, on the basis of which conclusions were drawn about the use of a particular database.

ER Model Partitioning: Towards Trustworthy Automated Systems Development

In database development, a conceptual model is created, in the form of an Entity-relationship (ER) model, and transformed to a relational database schema (RDS) to create the database. However, some important information represented on the ER model may not be transformed and represented on the RDS. This situation causes a loss of information during the transformation process. With a view to preserving information, in our previous study, we standardized the transformation process as a one-to-one and onto mapping from the ER model to the RDS. For this purpose, we modified the ER model and the transformation algorithm resolving some deficiencies existed in them. Since the mapping was established using a few real-world cases as a basis and for verification purposes, a formal-proof is necessary to validate the work. Thus, the ongoing research aiming to create a proof will show how a given ER model can be partitioned into a unique set of segments and use it to represent the ER model itself. How the findings can be used to complete the proof in the future will also be explained. Significance of the research on automating database development, teaching conceptual modeling, and using formal methods will also be discussed.

ER Model Partitioning: Towards Trustworthy Automated Systems Development

In database development, a conceptual model is created, in the form of an Entity-relationship(ER) model, and transformed to a relational database schema (RDS) to create the database. However, some important information represented on the ER model may not be transformed and represented on the RDS. This situation causes a loss of information during the transformation process. With a view to preserving information, in our previous study, we standardized the transformation process as a one-to-one and onto mapping from the ER model to the RDS. For this purpose, we modified the ER model and the transformation algorithm resolving some deficiencies existed in them. Since the mapping was established using a few real-world cases as a basis and for verification purposes, a formal-proof is necessary to validate the work. Thus, the ongoing research aiming to create a proof will show how a given ER model can be partitioned into a unique set of segments and use it to represent the ER model itself. How the findings can be used to complete the proof in the future will also be explained. Significance of the research on automating database development, teaching conceptual modeling, and using formal methods will also be discussed.