Database Schema Research Articles

Информационный софт-патронаж пациента после операции эндопротезирования тазобедренного сустава (предварительное сообщение)

Introduction The article considers the situation with modern user’s applications for patients in the post-operative period after surgical interventions, including total hip replacement. The main reasons for the emergence of a multidisciplinary field of a science, in particular between the medical and IT industries, were formulated. The aim of the study was to develop a technology for preventive analysis, control and management of patient actions at the stage of outpatient medical rehabilitation by developing and implementing a universal software platform of an application and a chatbot on a mobile device and PC. Material and methods The study presents a universal software platform on a mobile device and a PC, in which the doctor introduces personalized indications based on existing clinical recommendations that permit to target the patient's behavior in an expert-based vector of preventive measures. The paper presents the database scheme, usage scenarios, interface, and an example of a recommendation for a random patronage day. Results The comparative results in the aspect of complications in the patients who used the software product after discharge from the hospital with those in the patients without software patronage were analysed. The overall percentage of complications and of each specific one among them was significantly more frequent in the comparison group than in the observation group with IT-based support (р < 0.001). Patient satisfaction with the app was studied based on an anonymous survey, and a high satisfaction rate was revealed. Discussion The introduction of the software product into clinical work in comparison with existing analogues provided better patients’ compliance, especially in older persons with cognitive comorbidity, to targeted behavioral information, prevention of non-compliance with the medication dosage regimen and mobile activity, thus improving the long-term treatment results in patients at the stage of the rehabilitation. Conclusion It has been concluded that the results of the study indicate the feasibility and clinical validity of the development and implementation of the application developed and of similar software products.

MobiDB: intrinsically disordered proteins in 2021.

The MobiDB database (URL: https://mobidb.org/) provides predictions and annotations for intrinsically disordered proteins. Here, we report recent developments implemented in MobiDB version 4, regarding the database format, with novel types of annotations and an improved update process. The new website includes a re-designed user interface, a more effective search engine and advanced API for programmatic access. The new database schema gives more flexibility for the users, as well as simplifying the maintenance and updates. In addition, the new entry page provides more visualisation tools including customizable feature viewer and graphs of the residue contact maps. MobiDB v4 annotates the binding modes of disordered proteins, whether they undergo disorder-to-order transitions or remain disordered in the bound state. In addition, disordered regions undergoing liquid-liquid phase separation or post-translational modifications are defined. The integrated information is presented in a simplified interface, which enables faster searches and allows large customized datasets to be downloaded in TSV, Fasta or JSON formats. An alternative advanced interface allows users to drill deeper into features of interest. A new statistics page provides information at database and proteome levels. The new MobiDB version presents state-of-the-art knowledge on disordered proteins and improves data accessibility for both computational and experimental users.

CSI Fingerprinting Localization With Low Human Efforts

Fingerprinting indoor localization systems exploit wireless signal propagation features to estimate the location of wireless devices, where the major challenge in practice is the all-consuming training process: it requires site survey to establish the mapping between the signal feature and the location where the feature is observed. In this paper, we present a Wi-Fi localization scheme based on channel state information (CSI) of wireless signals, which manages to relieve time-consuming site survey. In particular, we first propose how to automatically generate the theoretical fingerprints database based on the signal propagation model and geometric methods. Localization with the theoretical fingerprints database yields accuracy close to existing methods. Second, we improve localization accuracy by parsing the user's trajectory instead of restricting to the single spot, where human movement features introduce more information for localization. Third, we present an automatic update scheme for the theoretical fingerprints database to improve time efficiency for localization, which can save 94 - 98% processing time for utilizing the CSI fingerprints database. We implement a prototype with COTS devices and conduct comprehensive experiments to verify proposed mechanisms. Results show that our design achieves 80% localization errors within 0.3m, which is 3× accuracy compared with the state-of-the-art design leveraging CSI.

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.

DSP: Schema Design for Non-Relational Applications

The way a database schema is designed has a high impact on its performance in relational databases, which are symmetric in nature. While the problem of schema optimization is even more significant for NoSQL (“Not only SQL”) databases, existing modeling tools for relational databases are inadequate for this asymmetric setting. As a result, NoSQL modelers rely on rules of thumb to model schemas that require a high level of competence. Several studies have been conducted to address this problem; however, they are either proprietary, symmetrical, relationally dependent or post-design assessment tools. In this study, a Dynamic Schema Proposition (DSP) model for NoSQL databases is proposed to handle the asymmetric nature of today’s data. This model aims to facilitate database design and improve its performance in relation to data availability. To achieve this, data modeling styles were aggregated and classified. Existing cardinality notations were empirically extended using synthetically generated queries. A binary integer formulation was used to guide the mapping of asymmetric entities from the application’s conceptual data model to a database schema. An experiment was conducted to evaluate the impact of the DSP model on NoSQL schema production and its performance. A profound improvement was observed in read/write query performance and schema production complexities. In this regard, DSP has significant potential to produce schemas that are capable of handling big data efficiently.

Longitudinal study of changes in ecosystem services in a city of lakes, Bhopal, India

Urban landscapes are now the most inhabited places by the majority of global population. The rapid and large-scale land use land cover (LULC) changes induced by urbanization are declining the ecosystem services (ESs) provisioning capacity of natural and semi-natural ecosystems of urban landscapes. The main aim of the study was to assess the ecological changes caused by LULC change in the urbanized capital of the Central India, Bhopal. This study relied on satellite images (from 1988 to 2018) for generation of spatio-temporal LULC database and direct benefit transfer ecosystem service valuation scheme for quantifying the ecosystem service value (ESV). The results showed decline in total ESs by US $ 2.00 million. Though water body covers least area out of 5 LULC types of the city, it remains the top contributor to total ESV in each reference year. The ecosystem service function analysis aided in identifying, regulating and provisioning services as the key contributors. In addition, assessment of ESs under two alternate future urban growth scenarios highlights the importance of conservation of natural ecosystems within the urban area. The results of this study can provide insights to the urban planners in effective decision making about how the ecosystems and their ecosystem service functions can be sustainably managed and strategically developed for the overall well-being of the growing urban population.

Efficient verifiable databases with additional insertion and deletion operations in cloud computing

Verifiable database (VDB) schemes allow the data owner to outsource a large database to the cloud so that any resource-constraint client could later retrieve the database records and check whether the cloud returns valid records or not. Meanwhile, the database can be updated by the data owner. To the best of our knowledge, there is no secure and efficient VDB scheme supporting public verification and all kinds of update operations (i.e., insertion, modification, and deletion) simultaneously. To resolve this problem, we propose an efficient VDB scheme by incorporating vector commitment (VC) with Merkle Interval Hash Tree (MIHT). To enhance the security (i.e., resist the forward automatic update attack), we re-formalize the syntax of VC and present a new construction of VC based on modified Generalized Bilinear Inversion (mGBI) assumption. Our proposed VC scheme is used for guaranteeing the integrity of data. Like the traditional VC schemes, our proposed scheme remains publicly verifiable. MIHT is a new primitive introduced by us, which is mainly used to support all update operations. Security analysis shows that our proposed VDB scheme can achieve real-world security requirements. The detailed performance analyses and simulations show that our proposed schemes are more practical in the real world.

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.

TGenBase - universal database for FAIR experiments

TGenBase is a ROOT-based virtual database which allows to communicate and store data in different underlying database management systems such as PostgreSQL, MySQL, SQLite, based on the configuration. It is primarily used for physics analysis parameter storage. However, it is universally applicable for any data storage task. There are several key features of the TGenBase for the user applications. It is a versioned insert only database, meaning that there is no need to update single entries and the whole history of the entries is available. The historical versions of the data can be queried with for a certain date. Being written as extension of the ROOT framework, it supports saving the ROOT objects such as graphs or histograms as well.We provide the data description interface-a web-based application which allows the end-user to define what and in which form they want the data to be stored and define the relations between different entities. Based on this definition the database schemas, server and client side code is generated from templates and easily deployed. Another feature of this approach is that we are able to generate the full-fledged content management systems with user roles for read and write access. Data query, visualization and modification are available in C++, Python, Web and LabVIEW thin clients.

A Generalization of the Inference Rules for Join Dependencies in Databases

In this paper a generalisation of the inference rules of the join dependencies that are used in the design of database schemas that meets the requirements of the fifth normal form is considered. In the previous works devoted to this problem, attempts to construct systems of the axioms of such dependencies based on inference rules are made. However, while the justification for the consistency (soundness) of the obtained axioms does not cause difficulties, the proof of completeness in general has not been satisfactorily resolved. First of all, this is due to the limitations of the inference rules themselves. This work focuses on two original axiom systems presented in the works of Sciore and Malvestuto. For the inclusion dependencies a system of rules that generalises existing systems and has fewer restrictions has been obtained. The paper presents a proof of the derivability of known systems of axioms from the presented inference rules. In addition, evidence of the consistency (soundness) of these rules is provided. The question of the completeness of the formal system based on the presented rules did not find a positive solution. In conclusion, the theoretical and practical significance of the inference rules for the join dependencies is noted.

Schema design advisor model for RDBMS to NoSQL database migration

Database schema design has a significant importance in software design. There are lots of tools and methods available for schema design in RDBMS but limited attention is given in NoSQL for schema design as it is emerging in database technology. NoSQL requires a different approach in designing efficient schema, such as in the document database which information should be stored as embedded document, or which information should be stored as referenced document. There are certain thumb rules for schema design in NoSQL databases. In reengineering projects, especially in Old RDBMS to new NoSQL system, developing good and efficient database schema is a very difficult task. In this paper, we have proposed a schema design advisor model which uses the existing software’s SQL queries load as an input along with an algorithm for schema design recommendation. Also, we have proposed a cost model for various schemas created by recommendation model. The proposed model is implemented through a prototype for the MongoDB document database in Java. The prototype produces all possible combinations of schemas and calculates cost of each schema. Automated schema design process produces all possible combinations of NoSQL schemas, which is difficult with manual schema design approach.

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.

Querying subjective data

Online users are constantly seeking experiences, such as a hotel with clean rooms and a lively bar, or a restaurant for a romantic rendezvous. However, e-commerce search engines only support queries involving objective attributes such as location, price, and cuisine, and any experiential data is relegated to text reviews. In order to support experiential queries, a database system needs to model subjective data. Users should be able to pose queries that specify subjective experiences using their own words, in addition to conditions on the usual objective attributes. This paper introduces OpineDB, a subjective database system that addresses these challenges. We introduce a data model for subjective databases. We describe how OpineDB translates subjective queries against the subjective database schema, which is done by matching the user query phrases to the underlying schema. We also show how the experiential conditions specified by the user can be combined and the results aggregated and ranked. We demonstrate that subjective databases satisfy user needs more effectively and accurately than alternative techniques through experiments with real data of hotel and restaurant reviews.

Generation of POJOs and DAOs Classes from Metadata Database

Implementing the persistence layer is a task that the Object Relational Mapping (ORMs) tools have standardized through diverse frameworks and Application Programming Interfaces (APIs). However, these ORMs and APIs have some inconveniences related to their configuration process and the time and effort it takes to learn them, amongst others. For example, every time a database is used, a configuration process is realized to map the database to obtain Plain Old Java Objects (POJOs) and Data Access Objects (DAOs). In order to overcome those disadvantages, this work contributes by proposing a reusable and extensible process that supports the automatic generation of POJOs and DAOs from database scheme metadata, through the specification of an Extended Backus-Naur Form (EBNF) grammar. A tool named GenPOJO was developed in order to test the process. Unlike the existing ORMs, the proposed process does not require the configuration steps for each database. In addition, GenPOJO does not require time to learn since the only input it receives is a file in XML (eXtensible Markup Language) format containing the database scheme metadata.

Data Types Diversity Quantitative Indicators in Relational Databases Physical Models

The article compares diversity indices applicability used in ecology to assess data types distribution for physical database schemes. The following dominance measures are used to assess the data type's diversity in the physical database scheme: Simpson's diversity index, Shannon diversity index, Simpson's evenness index, Pielu evenness index. A comparative analysis of the data type's diversity indicators for physical database schemes showed that the values of some indices obey certain rules. It is proposed to use diversity indices for physical database schemes' qualitative assessment. The indices considered in this work can also be used to build new models for assessing database complexity.

Structuring, reuse and analysis of electronic dental data using the Oral Health and Disease Ontology

BackgroundA key challenge for improving the quality of health care is to be able to use a common framework to work with patient information acquired in any of the health and life science disciplines. Patient information collected during dental care exposes many of the challenges that confront a wider scale approach. For example, to improve the quality of dental care, we must be able to collect and analyze data about dental procedures from multiple practices. However, a number of challenges make doing so difficult. First, dental electronic health record (EHR) information is often stored in complex relational databases that are poorly documented. Second, there is not a commonly accepted and implemented database schema for dental EHR systems. Third, integrative work that attempts to bridge dentistry and other settings in healthcare is made difficult by the disconnect between representations of medical information within dental and other disciplines’ EHR systems. As dentistry increasingly concerns itself with the general health of a patient, for example in increased efforts to monitor heart health and systemic disease, the impact of this disconnect becomes more and more severe.To demonstrate how to address these problems, we have developed the open-source Oral Health and Disease Ontology (OHD) and our instance-based representation as a framework for dental and medical health care information. We envision a time when medical record systems use a common data back end that would make interoperating trivial and obviate the need for a dedicated messaging framework to move data between systems.The OHD is not yet complete. It includes enough to be useful and to demonstrate how it is constructed. We demonstrate its utility in an analysis of longevity of dental restorations. Our first narrow use case provides a prototype, and is intended demonstrate a prospective design for a principled data backend that can be used consistently and encompass both dental and medical information in a single framework.ResultsThe OHD contains over 1900 classes and 59 relationships. Most of the classes and relationships were imported from existing OBO Foundry ontologies. Using the LSW2 (LISP Semantic Web) software library, we translated data from a dental practice’s EHR system into a corresponding Web Ontology Language (OWL) representation based on the OHD framework. The OWL representation was then loaded into a triple store, and as a proof of concept, we addressed a question of clinical relevance – a survival analysis of the longevity of resin filling restorations. We provide queries using SPARQL and statistical analysis code in R to demonstrate how to perform clinical research using a framework such as the OHD, and we compare our results with previous studies.ConclusionsThis proof-of-concept project translated data from a single practice. By using dental practice data, we demonstrate that the OHD and the instance-based approach are sufficient to represent data generated in real-world, routine clinical settings. While the OHD is applicable to integration of data from multiple practices with different dental EHR systems, we intend our work to be understood as a prospective design for EHR data storage that would simplify medical informatics. The system has well-understood semantics because of our use of BFO-based realist ontology and its representation in OWL. The data model is a well-defined web standard.

Detection and correction of database schema integrity violation based on initialization scripts

We present a new methodology for detecting and correcting database schema integrity violations. This technique uses initialization scripts, their pre-processing to compare with the current database schema. The result of the work is a prototype of the software product.

Mobile payment and online to offline retail business models

Mobile payments are services that use mobile devices to make payments. When digitalization moves across channel boundaries, online to offline channel retail will expand. Online to offline retailing will become the future retail owner stream and retail operators will move from cross-channel or multi-channel to omni-channel. This study investigates a market survey in Taiwan developing a data mining analytics including clustering analysis and association rules based on a snowflake schema database design. The role of mobile payment is determined in terms of new retail payment mechanism that promotes a better consumer purchase experience in an online to offline business environment.

Publicly Verifiable Shared Dynamic Electronic Health Record Databases With Functional Commitment Supporting Privacy-Preserving Integrity Auditing

Electronic health record (EHR) is a system that collects patients' digital health information and shares it with other healthcare providers in the cloud. Since EHR contains a large amount of significant and sensitive information about patients, it is required that the system ensures response correctness and storage integrity. Meanwhile, with the rise of IoT, more low-performance terminals are deployed for receiving and uploading patient data to the server, which increases the computational and communication burden of the EHR systems. The verifiable database (VDB), where a user outsources his large database to a cloud server and makes queries once he needs certain data, is proposed as an efficient updatable cloud storage model for resource-constrained users. To improve efficiency, most existing VDB schemes utilize proof reuse and proof updating technique to prove correctness of the query results. However, it ignores the “real-time” of proof generation, which results in an overhead that the user has to perform extra process (e.g., auditing schemes) to check storage integrity. In this article, we propose a publicly verifiable shared updatable EHR database scheme that supports privacy-preserving and batch integrity checking with minimum user communication cost. We modify the existing functional commitment (FC) scheme for the VDB design and construct a concrete FC under the computational <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> -BDHE assumption. In addition, the use of an efficient verifier-local revocation group signature scheme makes our scheme support dynamic group member operations, and gives nice features, such as traceability and non-frameability.

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.