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In the last decade, healthcare systems have played an effective role in improving medical services by monitoring and diagnosing patients' health remotely. These systems, either in hospitals or in other health centers, have experienced significant growth with emerging technologies. They are becoming of great interest to many countries worldwide nowadays. Portable healthcare monitoring systems (HMS) depend on internet of things (IoT) technology due to its effectiveness and reliability in several sectors, as well as in the sector of telemedicine. This paper proposes a portable healthcare system in an IoT environment controllable via a smartphone application that aims to facilitate utilization. This proposed system can track physiological indicators of a patient's body as well as the environmental conditions where the patient lives in real-time and auto-manage databases. Moreover, this paper touched on a comparison between three servers, concerning data transfer speeds from the proposed system into the servers.

En qualsevol sistema d'informació existeix un conjunt de regles de negoci que les dades han de complir per constituir un estat vàlid. L'estàndard SQL defineix les assercions com una manera d'expressar aquestes regles directament a la base de dades, tanmateix, els Sistemes Gestors de Bases de Dades Relacionals moderns no donen suport a les assercions a causa de la baixa eficiència en temps d'execució. La validació d'integritat es pot fer de forma incremental, assumint que la base de dades és consistent i només tenint en compte el conjunt de modificacions de dades al avaluar si provocarien la violació d'una asserció. En aplicacions reals, es gestionen múltiples connexions d'usuaris simultàniament, i per tant es generen molts conjunts de modificacions de dades que s'han de comprovar. Aquesta tesi de final de grau parteix d'un mètode incremental capaç de comprovar, eficientment, els efectes d'una sola transacció, i l'amplia per introduir la capacitat de comprovar concurrentment si múltiples transaccions poden provocar una violació per si soles o conjuntament. Això s'aconsegueix proposant un algorisme que transforma regles que es comproven de forma serial en regles que poden ser comprovades de forma concurrent. A la segona part del treball, s'implementa l'algorisme suggerit en una eina que, donat un conjunt d'assercions en SQL estàndard i un esquema de base de dades, compila automàticament la infraestructura necessària dins la base de dades i genera una sèrie de vistes SQL que poden comprovar, eficientment, la integritat de conjunts de modificacions de dades provinents de múltiples transaccions concurrents. L'eina també permet als seus usuaris modificar assercions existents o introduir-ne de noves, per tant, es tracta d'una eina per a gestionar la comprovació d'integritat incremental concurrent d'assercions en SQL. Any information system has a defined set of business rules that the data must satisfy to constitute a valid state. The SQL standard defines assertions as a way to express these rules directly into the database, however, modern Relational Database Management Systems do not support assertions due to lack of efficiency in execution time. Integrity checking can be performed in an incremental manner, where the database is assumed to be consistent and only the set of data modifications are considered when evaluating if they would produce an assertion violation. In real world applications, multiple user connections are handled simultaneously, generating many sets of data modifications that need to be checked. This thesis extends an incremental approach that was capable of efficiently checking the effects of a single transaction, and introduces the capability of concurrently checking if multiple transactions can produce a violation by themselves or combined. This is achieved by proposing an algorithm that transforms the serially-checked constraints of the previous method into concurrently-checked ones. In the second part of the thesis such algorithm is implemented into a tool that can receive a set of standard SQL assertions and a target database schema as an input, and automatically compile the necessary infrastructure into the database and generate a series of SQL views that efficiently check the integrity of data modifications from multiple concurrent transactions. The tool also enables its users to modify any existing assertions or introduce new ones, which makes it a management tool for concurrent incremental integrity checking of SQL assertions.

A partir d'un treball anterior realitzat per Aniol Carbó, es vol continuar aquest extenent-lo i aplicant-ho a exemples i situacions més complexes. Es tracta d'un desenvolupament realista d'un exemple "benchmark" de referència, combinant la tecnologia "Blockchain" amb les clàsiques bases de dades relacionals, remodelant i extenent les anàlisis, comparatives i desenvolupament de programari per a cobrir utilitats com les perseguides pels Models Conceptuals Deductius proposats pel professor Antoni Olivé.

Relational databases are ubiquitous. Such monolithic databases accumulate large amounts of data, yet applications typically only work on small portions of the data at a time. A subset of the database defined as a computation on the underlying tables is called a view. Querying views is helpful, but it is also desirable to update them and have these changes be applied to the underlying database. This view update problem has been the subject of much previous work before, but support by database servers is limited and only rarely available. Lenses are a popular approach to bidirectional transformations, a generalization of the view update problem in databases to arbitrary data. However, perhaps surprisingly, lenses have seldom actually been used to implement updatable views in databases. Bohannon, Pierce and Vaughan propose an approach to updatable views called relational lenses. However, to the best of our knowledge this proposal has not been implemented or evaluated prior to the work reported in this thesis. This thesis proposes programming language support for relational lenses. Language integrated relational lenses support expressive and efficient view updates, without relying on updatable view support from the database server. By integrating relational lenses into the programming language, application development becomes easier and less error-prone, avoiding the impedance mismatch of having two programming languages. Integrating relational lenses into the language poses additional challenges. As defined by Bohannon et al. relational lenses completely recompute the database, making them inefficient as the database scales. The other challenge is that some parts of the well-formedness conditions are too general for implementation. Bohannon et al. specify predicates using possibly infinite abstract sets and define the type checking rules using relational algebra. Incremental relational lenses equip relational lenses with change-propagating semantics that map small changes to the view into (potentially) small changes to the source tables. We prove that our incremental semantics are functionally equivalent to the non-incremental semantics, and our experimental results show orders of magnitude improvement over the non-incremental approach. This thesis introduces a concrete predicate syntax and shows how the required checks are performed on these predicates and show that they satisfy the abstract predicate specifications. We discuss trade-offs between static predicates that are fully known at compile time vs dynamic predicates that are only known during execution and introduce hybrid predicates taking inspiration from both approaches. This thesis adapts the typing rules for relational lenses from sequential composition to a functional style of sub-expressions. We prove that any well-typed functional relational lens expression can derive a well-typed sequential lens. We use these additions to relational lenses as the foundation for two practical implementations: an extension of the Links functional language and a library written in Haskell. The second implementation demonstrates how type-level computation can be used to implement relational lenses without changes to the compiler. These two implementations attest to the possibility of turning relational lenses into a practical language feature.

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.

Det finns en stor mängd databaser som används inom många olika sorters användningsområden. Bland dessa finns det sådana som har funktion för att behandla spatiala data. Problemet som detta medför är att välja en databas som kan hantera en viss tänkt typ av spatiala data med bäst prestanda. Denna rapport presenterar en utredning för detta utifrån ett dataset som erhållits från Norconsult Digital. Bland de databaser som valts finns tre SQL databaser (PostgreSQL, MySQL och SQLite) och en NoSQL databas (MongoDB). Dessa databaser genomgick fem likvärdiga operationer/tester som resulterade i att PostgreSQL med dess GiST/SP-GiST index och MongoDB presterade på en nivå långt över resterande databaser som testades. Utifrån detta arbete kan det konstateras att fler utförliga prestandatester bör utföras, där större och mer komplexa dataset, samt fler alternativ till databaser och spatiala index bör finnas med. Detta för att ge en bättre bild över vilka databaser, med stöd för spatiala data, som presterar bättre. There are a large number of databases that are used in many different areas. Among these, some have a function for processing spatial data. The problem that this entails is the choice of a database that can handle a certain type of spatial data with the best possible performance. This report presents an analysis of this based on a dataset obtained from Norconsult Digital. Among the chosen databases are three SQL databases (PostgreSQL, MySQL and SQLite) and one NoSQL database (MongoDB). These databases underwent five identical operations/tests resulting in PostgreSQL with its GiST/SP-GiST index and MongoDB performing at a level well above the rest of the databases tested. Based on this work, it can be concluded that more detailed performance tests should be carried out, where larger and more complex datasets, as well as more alternatives to databases and spatial indexes, should be included. This is to give a better picture of which databases, with support for spatial data, perform better.

To cope with the increased complexity of systems, models are used to capture what is considered the essence of a system. Such models are typically represented as a graph, which is queried to gain insight into the modelled system. Often, the results of these queries need to be adjusted according to updated requirements and are therefore a subject of maintenance activities. It is thus necessary to support writing model queries with adequate languages. However, in order to stay meaningful, the analysis results need to be refreshed as soon as the underlying models change. Therefore, a good execution speed is mandatory in order to cope with frequent model changes. In this paper, we propose a benchmark to assess model query technologies in the presence of model change sequences in the domain of social media. We present solutions to this benchmark in a variety of 11 different tools and compare them with respect to explicitness of incrementalization, asymptotic complexity and performance.

Dissertação de mestrado integrado em Engenharia Informática, As bases de dados relacionais não foram desenhadas para tratar de dados interligados, em oposição às tecnologias de grafos. A modelação de Recursos Humanos trabalha com estruturas altamente relacionadas entre si, pelo que a substituição de bases de dados relacionais por bases de dados de grafos neste contexto poderia melhorar a robustez e desempenho das aplicações. Na presente dissertação, pretendeu-se comparar as tecnologias existentes (relacionais, não relacionais e grafos) e, dentro da tecnologia de grafos, avaliar qual a mais adequada em contexto de Recursos Humanos. A revisão de literatura revelou que as bases de dados de grafos são mais eficientes para dados interligados do que as bases de dados relacionais e não relacionais. De todos os modelos de grafos analisados, o Neo4j foi o sistema de gestão de bases de dados que reuniu, num âmbito geral, as melhores características e, por este motivo, foi utilizado como prova de conceito. Foram realizadas três interrogações (duas com obtenção de dados de diferentes relações e uma com obtenção de dados de uma única relação), tendo-se obtido tempos de resposta de 41.48, 18.58 e 62.14ms vs. 804.68, 103.08 e 318.42ms entre bases de dados de grafos e relacionais, respetivamente. Os resultados obtidos revelaram melhor desempenho do Neo4j na maioria das situações avaliadas. Em situações sem junções entre diferentes relações num ambiente relacional, o desempenho do SQL foi superior ao do Neo4j. Adicionalmente, verificou-se quebra significativa de desempenho do Neo4j quando foi analisado mais de metade do grafo. As bases de dados de grafos apresentaram um melhor desempenho no tratamento de bases de dados altamente relacionadas., Relational databases were not designed to handle linked data, as opposed to graph technologies. Human Resource Modelling works with highly interrelated structures. Therefore, replacing relational databases with graph databases in this context could improve applications' robustness and performance. The aim of this dissertation was to 1) compare existing technologies (relational, non-relational and graphs) and 2) evaluate which is the most appropriate graph technology in a Human Resources context. The literature review showed that graph databases are more efficient for interconnected data than relational and non-relational databases. Of all graph models analysed, Neo4j was the database management system that gathered, overall, the best features and therefore was used as proof of concept. Three queries were performed two with data obtained from different relations and one with data obtained from a single relation), having obtained response times of 41.48, 18.58 and 62,14rns vs. 804.68, 103.08 and 318,42ms between graph and relational databases, respectively. Results showed better performance of Neo4j in most of the evaluated situations. In a relational environment without joins between different relations, SQL outperformed Nleo4i. Additionally, there was a significant drop in Neo4cs performance when more than half of the graph was analysed, In conclusion, graph databases performed better in processing highly related databases.

With the rise of big data, the use of data science has become critically important to extract insights from a huge amount of data. In recent years, several categories of databases have been used in data science to efficiently store, manage and analyze huge amounts of data. In particular, NoSQL (Not Only SQL) databases have emerged as an alternative to relational databases. In this thesis, we are interested in the graph-oriented category of NoSQL databases that replaces expensive relational joins with graph traversals. We use graph databases to address two data science issues of concern that are our main contributions: Implementing data warehouses capable of responding quickly to complex analytical queries and constructing descriptors to be used to predict missing values on the edges of a protein-protein interaction network.; Avec l’essor du big data, le recours à la science des données est devenu crucial pour extraire les connaissances à partir des données massives. Ces dernières années, plusieurs catégories de bases de données ont été utilisées en science des données pour stocker, gérer et analyser efficacement les mégadonnées. En particulier, les bases de données NoSQL (Not Only SQL) ont émergé comme une alternative aux bases de données relationnelles. Dans cette thèse, nous nous intéressons à la catégorie orientée graphes des bases de données NoSQL qui remplace les jointures relationnelles coûteuses par des parcours du graphe. Nous les utilisons pour répondre à deux problématiques en science des données et qui constituent nos principales contributions : implanter des entrepôts de données capables de répondre rapidement à des requêtes analytiques complexes et construire des descripteurs afin de les utiliser pour prédire les valeurs manquantes sur les arcs d’un réseau d’interaction protéine-protéine.

Today, recent rapid advancements and developments in information and communication technologies have enabled the number of connected devices to increase gradually. Thus, a significant amount of data from many sources has been produced as a result of the increase in connected devices. It is now more crucial than ever to access and draw conclusions from the data kept in relational database management systems. Ontology-Based Data Access (OBDA) is a hugely important paradigm for leveraging Semantic Web technologies to access data stored in relational databases. Users access data via a conceptual layer in the OBDA paradigm. Data is stored in relational databases and is represented by the conceptual layer as an RDF(S) or OWL ontology. In this paper, a demonstration for the integration of a relational database and an ontology is presented in order to provide an ontology-based data access. The goal of the presented demonstration is to serve as a roadmap for further research studies. For this purpose, a data set stored in MySQL relational database management system is accessed using the OBDA model. Further, the Ontop Framework that is compatible with the Protégé ontology development environment is used to provide the integration between the ontology and the relational database. Moreover, the Ontop queries are executed over SPARQL.

Computer systems are a part of today’s most common activities and, more often than not, involve some type of interaction with a database. In this scheme, databases play a big role, where even small operational delays could cost millions to big tech companies. It is then, of utmost importance that such systems are responsive and adapt automatically to different types of workload. To this date, Relational Database Management System remain the most popular database type, which allows the executing of concurrent transactions with Atomicity, Consistency, Isolation and Durability guarantees. Enforcing such properties requires strict control over the execution of transactions. However, maintaining such properties and controlling the transactions’ concurrency may hamper performance of the system, being this specially the case when database contention is high. Motivated by such behavior, we propose the lazy evaluation of database SQL queries — using Futures/Promises and Java Database Connectivity (JDBC) — by empowering a relational database with Lazy State Determination (LSD). This novel Application Programming Interface (API) allows delaying operations to the commit time, which in the end reduces the transaction window where conflicts may occur. We observed that, by introducing our implementation of a JDBC-LSD driver, in high contention scenarios the throughput increased by 50% and latency reduced by 40%. Os sistemas informáticos são parte das atividades mais comuns na atualidade e, na maioria das vezes, envolvem algum tipo de interação com uma base de dados. Neste cenário, as bases de dados têm um grande papel, sendo que pequenos atrasos operacionais podem custar milhões às grandes empresas tecnológicas. Até os dias de hoje, os Sistemas de Gestão de Bases de Dados Relacionais continuam a ser o tipo de bases de dados mais popular, permitindo a execução concorrente de transações garantindo as propriedades de Atomicidade, Consistência, Isolamento e Durabilidade. A aplicação de tais propriedades requer um controlo rigoroso sobre a execução de transações. No entanto, manter tais propriedades e controlar a concorrência das transacções pode diminuir o desempenho do sistema, sendo especialmente o caso em bases onde a contenção é elevada. Assim, propomos o atraso na execução de queries SQL na base de dados através da introdução do protocolo de controlo de concorrência Lazy State Determination (LSD), com a utilização de Futuros/Promessas e Java Database Connectivity (JDBC). Esta nova Interface de Programação de Aplicações (API) permite adiar as operações para o momento do commit, o que acaba por reduzir a janela da transação onde conflitos podem ocorrer. Observamos que, ao utilizar LSD em um cliente JDBC, nós conseguimos aumentar a taxa de execução de transações em 50% e reduzir a latência em 40% num ambiente de contenção elevada.

U ovom radu su promatrane prednosti i nedostaci dokumentno orijentiranih baza podataka na način da su se testirala prosječna vremena izvođenja različitih jednostavnih i često korištenih upita. Na početku rada dana je teorijska podloga o različitim tipovima baza koje se danas koriste za rukovanje podacima. Ukratko je objašnjen način funkcioniranja relacijskih baza podataka te su dani primjeri i načini njihovog korištenja. Potom su pogledani tipove podataka i neke osnovne upite za rukovanje podacima unutar dokumentno orijentiranih ili NoSQL baza podataka te su objašnjene neke karakteristike koje ih opisuju. U poglavlju praktičnog rada konfigurirana sa dva različita tipa baza korištenjem softvera MongoDB i MsSQL i nad njima su se radili jednostavne i često korištene operacije te uspoređivali vremenski rezultati njihovog izvođenja. Rad je zaključen sa prednostima i nedostacima dokumentno orijentiranih baza podataka prema rezultatima koje su dobiveni iz njihovog testiranja i uspoređivanja sa relacijskim bazama podataka. Topic of this paper is “Advantages and disadvantages of document-oriented databases”. In the beginning of this paper the reader is given a theoretical background on different database types most commonly used nowadays for data handling. Function of such databases is briefly explained, along with examples of their usage. Furthermore, data types and some of the basic queries for handling data in document oriented or NoSQL databases were analysed, as well as interpreted characteristics which describe them. In the chapter which focuses on practical work using MongoDB and MsSQL, two different types of databases were configured. Afterwards they were used to conduct frequently used operation and compared the results of their performance. The paper is concluded with advantages and disadvantages of document oriented databases based on acquired results from performed tests and their comparison with relational databases.

PurposeThe technical feasibility of using Benford's law to assist internal auditors in reviewing the integrity of high-volume data sets is analysed. This study explores whether Benford's distribution applies to the set of numbers represented by the quantity of records (size) that comprise the different tables that make up a state-owned enterprise's (SOE) enterprise resource planning (ERP) relational database. The use of Benford's law streamlines the search for possible abnormalities within the ERP system's data set, increasing the ability of the internal audit functions (IAFs) to detect anomalies within the database. In the SOEs of emerging economies, where groups compete for power and resources, internal auditors are better off employing analytical tests to discharge their duties without getting involved in power struggles.Design/methodology/approachRecords of eight databases of an SOE in Argentina are used to analyse the number of records of each table in periods of three to 12 years. The case develops step-by-step Benford's law application to test each ERP module records using Chi-squared (χ²) and mean absolute deviation (MAD) goodness-of-fit tests.FindingsBenford's law is an adequate tool for performing integrity tests of high-volume databases. A minimum of 350 tables within each database are required for the MAD test to be effective; this threshold is higher than the 67 reported by earlier researches. Robust results are obtained for the complete ERP system and for large modules; modules with less than 350 tables show low conformity with Benford's law.Research limitations/implicationsThis study is not about detecting fraud; it aims to help internal auditors red flag databases that will need further attention, making the most out of available limited resources in SOEs. The contribution is a simple, cheap and useful quantitative tool that can be employed by internal auditors in emerging economies to perform the first scan of the data contained in relational databases.Practical implicationsThis paper provides a tool to test whether large amounts of data behave as expected, and if not, they can be pinpointed for future investigation. It offers tests and explanations on the tool's application so that internal auditors of SOEs in emerging economies can use it, particularly those that face divergent expectations from antagonist powerful interest groups.Originality/valueThis study demonstrates that even in the context of limited information technology tools available for internal auditors, there are simple and inexpensive tests to review the integrity of high-volume databases. It also extends the literature on high-volume database integrity tests and our knowledge of the IAF in Civil law countries, particularly emerging economies in Latin America.

An increasing amount of data is stored and managed in today's information systems. For this purpose, relational databases are used very often. Fast access to data is becoming increasingly important and great emphasis is placed on its improvement. The data access time can be significantly improved by creating partitions and index structures, or their combinations. From the point of view of efficiency, it is not appropriate or necessary to access all data. They can be divided into smaller parts, which will facilitate the execution of certain operations and bring efficiency, whether in terms of time or performance. As far as indexing is concerned, there is also an opportunity to access only the data sought, thus avoiding the Table Access Full method. This paper deals with the effect of partitioning and indexing on data access time, which is compared in seven different scenarios of different combinations of partitions created over tables and indexes.

In recent years, several bacterial strains have acquired significant antibiotic resistance and can, therefore, become difficult to contain. To counteract such trends, relational databases can be a powerful tool for supporting the decision-making process. The case of Klebsiella pneumoniae diffusion in a central region of Italy was analyzed as a case study. A specific relational database is shown to provide very detailed and timely information about the spatial–temporal diffusion of the contagion, together with a clear assessment of the multidrug resistance of the strains. The analysis is particularized for both internal and external patients. Tools such as the one proposed can, therefore, be considered important elements in the identification of infection hotspots, a key ingredient of any strategy to reduce the diffusion of an infectious disease at the community level and in hospitals. These types of tools are also very valuable in the decision-making process related to antibiotic prescription and to the management of stockpiles. The application of this processing technology to viral diseases such as COVID-19 is under investigation.

The aim of this thesis was to compare the performance of two relational database management systems PostgreSQL and MySQL. For the purpose of the study a relational database was designed and a piece of software was implemented to connect desktop application with the database system. This software shall also create entities and relations between them in desired empty schemes on servers for databases. There has also been implemented a desktop application in Java programming language, that allows browsing data stored in database and performing the tests of database performance. Tests addressed basic operations of adding, collecting, updating and deleting data. Thisthesis makes a hypothesis "PostgreSQL is more efficient for desktop application while loaded with small data, in that case 1000 of queries", that was confirmed by achieved results from tests performed.

The recent years, marked by an unprecedented increase in the volume of data stored and managed, have simultaneously brought many problems and difficulties regarding the adequate management systems of very large databases, especially the traditional ones, most of them dedicated to relational databases, which are rather oriented towards ensuring data integrity and transaction coherence. The solution to this problem was a new database model, called NoSQL, an emerging alternative to the traditional relational databases, a popular choice especially due to applications in web requirements. NoSQL databases are not only simple replacements for SQL databases, they usually co-exist due to their complements. SQL databases are currently facing many challenges such as scalability and agility proving the inability to adapt to currently available facilities like cheap memory and processing power, while the NoSQL databases are increasingly proving their ability to handle very large volumes of stored data in terms of the number of users. Thus, following the same major objective, as the creation, recovery, updating, and management of data, two complementary database models are currently used, both with pros and cons. This paper aims to be a review of the benefits and limits of NoSQL over the relational highlight by recent literature on the subject.

Aquest treball de final de grau té com a objectiu demostrar l'aplicació dels Models Conceptuals Deductius a través de la combinació de blockchain i bases de dades relacionals. La proposta dels MCD's va ser introduïda per Antoni Olivé l'any 1989, quan encara no exisitia la tecnologia blockchain. Aquesta tecnologia presenta un seguit de semblances amb la proposta d'Olivé, i en aquest projecte es demostra la possible implementació pràctica d'aquest concepte per a obtenir un sistema d'informació funcional. This final degree project has the purpose of demonstrating the application of the Deductive Conceptual Models through the combination of blockchain and relational databases. The Deductive Conceptual Models were introduced by Antoni Olivé on year 1989, before the blockchain technology was created. This very same technology presents multiple similarities with Olivé's proposal, so in this project we prove the possible practical implementation of this concept in order to accomplish a functional information system.

Data curation is a complex, multi-faceted task. While dedicated data stewards are starting to take care of these activities in close collaboration with researchers for many types of (usually file-based) data in many institutions, this is rarely yet the case for data held in relational databases. Beyond large-scale infrastructures hosting e.g. climate or genome data, researchers usually have to create, build and maintain their database, care about security patches, and feed data into it in order to use it in their research. Data curation, if at all, usually happens after a project is finished, when data may be exported for digital preservation into file repository systems. We present DBRepo, a semantic digital repository for relational databases in a private cloud setting designed to (1) host research data stored in relational databases right from the beginning of a research project, (2) provide separation of concerns, allowing the researchers to focus on the domain aspects of the data and their work while bringing in experts to handle classic data management tasks, (3) improve findability, accessibility and reusability by offering semantic mapping of metadata attributes, and (4) focus on reproducibility in dynamically evolving data by supporting versioning and precise identification/cite-ability for arbitrary subsets of data.

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.

When researchers speak of BM25, it is not entirely clear which variant they mean, since many tweaks to Robertson et al.’s original formulation have been proposed. When practitioners speak of BM25, they most likely refer to the implementation in the Lucene open-source search library. Does this ambiguity “matter”? We attempt to answer this question with a large-scale reproducibility study of BM25, considering eight variants. Experiments on three newswire collections show that there are no significant effectiveness differences between them, including Lucene’s often maligned approximation of document length. As an added benefit, our empirical approach takes advantage of databases for rapid IR prototyping, which validates both the feasibility and methodological advantages claimed in previous work.

Spectral Information Systems provide a framework to assemble, curate, and serve spectral data and their associated metadata. This article documents the evolution of the SPECCHIO system, devised to enable long-term usability and data-sharing of field spectroradiometer data. The new capabilities include a modern, web-based client-server architecture, a flexible metadata storage scheme for generic metadata handling, and a rich application programming interface, enabling scientists to directly access spectral data and metadata from their programming environment of choice. The SPECCHIO system source code has been moved into the open source domain to stimulate contributions from the spectroscopy community while binary distributions, including the SPECCHIO virtual machine, simplify the installation and use of the system for the end-users.

Interactive data analysis is often conveniently done on personal computers that have limited memory. Current analytical data management systems rely almost exclusively on main memory for computation. When the data size exceeds the memory limit, many systems cannot complete queries or resort to an external execution strategy that assumes a high I/O cost. These strategies are often much slower than the in-memory strategy. However, I/O cost has gone down: Most modern laptops have fast NVMe storage. We believe that the difference between in-memory and external does not have to be this big. We implement a parallel external sorting operator in DuckDB that demonstrates this. Experimental results with our implementation show that even when the data size far exceeds the memory size, the performance loss is negligible. From this result, we conclude that it is possible to have a graceful degradation from in-memory to external sorting.

Interactive data analysis is often conveniently done on personal computers that have limited memory. Current analytical data management systems rely almost exclusively on main memory for computation. When the data size exceeds the memory limit, many systems cannot complete queries or resort to an external execution strategy that assumes a high I/O cost. These strategies are often much slower than the in-memory strategy. However, I/O cost has gone down: Most modern laptops have fast NVMe storage. We believe that the difference between in-memory and external does not have to be this big. We implement a parallel external sorting operator in DuckDB that demonstrates this. Experimental results with our implementation show that even when the data size far exceeds the memory size, the performance loss is negligible. From this result, we conclude that it is possible to have a graceful degradation from in-memory to external sorting.

Data is being generated and processed at an unprecedented scale. Statistical data analysis is in high demand, with many organizations using it for a broad range of interests, from researching to guiding business decisions. However, this massive generation of data raises privacy concerns, as most of this data contains sensitive information about individuals. In turn, several regulations have emerged to give people more control over their data, such as the European General Data Protection Regulation. For organizations, the challenge is how to analyze and publish data without compro- mising an individual’s privacy. In the context of Relational Databases, they still lack features for this, with solutions involving manually removing identifying information from the data or only allowing certain aggregate queries. However, these solutions can be susceptible to attacks and do not provide strong privacy guarantees. In this thesis, we propose to explore a solution to address the challenge of privately analyzing and publishing data on Relational Databases. To this end, we present a new type of Views - privacy-preserving views - which allow for computing statistical aggre- gations on data while preserving privacy. We focus our studies on Differential Privacy, a recent mathematical definition of privacy, and explore how to turn common aggregation functions into their private counterparts. We present our solution in two parts. In the first part, we present a solution to create privacy-preserving views for a specific database, namely PostgreSQL. In the second part, we present the design and implementation of a database proxy, which supports any SQL database and produces private statistical results. The experimental results show that our proposed solutions can achieve balanced performance - views containing count functions perform better than views containing other functions. They also show that both solutions are capable of providing accurate privacy-preserving data for large databases and sample sizes. Dados estão a ser gerados e processados a uma escala sem precedentes. A análise de dados estatísticos é uma área bastante requisitada, com muitas organizações a utilizá-la para uma ampla variedade de interesses, desde investigação até à orientação de decisões empresariais. No entanto, esta geração massiva de dados tem suscitado preocupações quanto à privacidade, uma vez que a maioria destes dados contém informações sensíveis sobre indivíduos. Por sua vez, vários regulamentos têm surgido para dar às pessoas mais controlo sobre os seus dados, tais como o Regulamento Geral sobre a Proteção de Dados na União Europeia. Para as organizações, o desafio é como analisar e publicar dados sem comprometer a privacidade das pessoas. No contexto das Bases de Dados Relacionais, estas não tem qualquer mecanismo para tal, sendo que as soluções existentes envolvem a remoção ma- nual de informação sensível ou permitir apenas a execução de consultas de agregação. No entanto, estas soluções são suscetíveis a ataques e não oferecem garantias de privacidade suficientes. Nesta dissertação propomos explorar uma solução para endereçar o desafio da análise e publicação de dados de forma privada, em Bases de Dados Relacionais. Para este efeito, apresentamos um novo tipo de vistas - vistas privadas - que permitem calcular agregações estatísticas sobre os dados a ao mesmo tempo preservar a privacidade. Iremos estudar o conceito de Privacidade Diferencial, uma definição matemática recente de privacidade, e explorar como transformar funções de agregação comuns em funções privadas. Iremos apresentar a nossa solução em duas partes. Na primeira parte apresentaremos uma solução para criar vistas privadas para uma base de dados específica - PostgreSQL. Na segunda parte apresentaremos o design e implementação de um proxy que suporta qualquer base de dados SQL e produz resultados estatísticos privados. Os resultados ex- perimentais mostram que as soluções propostas são capazes de alcançar um desempenho equilibrado e de produzir dados privados precisos.

The increasing availability of real-time in situ measurements and remote sensing observations have the potential to contribute to the optimisation of water resources management. Global challenges such as climate change, intensive agriculture and urbanisation put a high pressure on our water resources. Due to recent innovations in measuring both water quantity and quality, river systems can now be monitored in real time at an unprecedented spatial and temporal scale. To interpret the sensor measurements and remote sensing observations additional data, for example on the location of the measurement, and upstream and downstream catchment characteristics, are required. In this paper, we present a data management system to support flow-path-related functionality for decision making and prediction modelling. Adding meta-datasets and facilitating (near) real-time processing of sensor data questions are key concepts for the systems. The potential of the database framework for hydrological applications is demonstrated using different applications for the river system of Flanders. In one, the database framework is used to simulate the daily discharge for each segment within a catchment using a simple data-driven approach. The presented system is useful for numerous applications including pollution tracking, alerting and inter-sensor validation in river systems, or related networks.

Although not usually acknowledged as such, forgetting is a crucial aspect of human reasoning. It allows us to deal with large amounts of information, pushing irrelevant details out of our consciousness so that we can focus on the essential knowledge. Motivated by its beneficial effect on the human brain, this operation has been emulated in many formalisms in the field of Knowledge Representation and Reasoning, where several approaches to forgetting have been proposed. In common, these support computer systems dealing with inaccurate or excessive information without negatively affecting the remaining knowledge. More recently, the General Data Protection Regulation’s ‘right to be forgotten’ has given additional impetus to the study of this operation. Surprisingly, forgetting has not yet been studied in relational databases, the most widespread technology for knowledge representation. This is a serious drawback that needs to be addressed, considering the prominence of databases in our society and the relevance of the operation in numerous knowledge processing tasks. In this dissertation, we take the first steps to tackle this need, proposing a theoretical investigation of forgetting relations in relational databases. We start by introducing an alternative formalisation of the relational model, which includes a novel notion of equivalence between databases. Afterwards, we look further into the problem of forgetting. We formally define the general concept of a relation forgetting operator and present concrete operators, each aligned with a distinct view on the operation and thus with its unique features. Moreover, we illustrate the operators with examples inspired by realistic situations. Finally, we evaluate them. For that, we formalise in the form of properties the requirements that guided the definition of the operators and prove that they satisfy desirable properties. Ultimately, with this work, we motivate the importance of forgetting in relational databases and lay the foundations for its study. Embora nem sempre reconhecido como tal, o esquecimento é um aspeto crucial do raciocínio humano, pois permite-nos lidar com grandes quantidades de informação, ajudandonos a concentrar no conhecimento essencial. Motivada pelo seu efeito benéfico no cérebro humano, esta operação tem sido emulada em diversos formalismos na área da Representação do Conhecimento e Raciocínio, onde várias abordagens ao esquecimento têm sido propostas. Em comum, estas apoiam sistemas informáticos a lidar com informação imprecisa ou excessiva sem afetar negativamente o restante conhecimento. Mais recentemente, o ‘direito ao esquecimento’ do Regulamento Geral sobre a Proteção de Dados deu um impulso extra ao estudo desta operação. Surpreendentemente, o esquecimento ainda não foi estudado em bases de dados relacionais, a tecnologia mais utilizada para representação de conhecimento. Este é um grave inconveniente a resolver, tendo em conta a proeminência das bases de dados na nossa sociedade e a relevância da operação em inúmeras tarefas de processamento de conhecimento. Nesta dissertação, damos os primeiros passos no sentido de fazer frente a esta necessidade, propondo uma investigação teórica do esquecimento de relações em bases de dados relacionais. Começamos por introduzir uma formalização alternativa do modelo relacional, que inclui uma nova noção de equivalência entre bases de dados. Posteriormente, analisamos mais aprofundadamente o problema do esquecimento. Definimos formalmente o conceito geral de um operador de esquecimento de relações e apresentamos operadores concretos, cada um alinhado com uma visão distinta sobre a operação e, portanto, com as suas características únicas. Ademais, ilustramos os operadores com exemplos inspirados em situações reais. Finalmente, avaliamo-los. Para isso, formalizamos sob a forma de propriedades os requisitos que orientaram a definição dos operadores e provamos que estes satisfazem propriedades desejáveis. Em última análise, com este trabalho, motivamos a importância do esquecimento em bases de dados relacionais e estabelecemos as bases para o seu estudo.

[ES] La plataforma de geolocalización servirá para que los gestores municipales puedan ubicar vehículos, en un entorno real, mediante dispositivos IoT GPS conectados a LoRaWAN y desarrollados a medida a partir de placas electrónicas de amplio uso, con el fin de dar respuesta a una necesidad real. Los aspectos clave que va a abordar este TFG, serán: - El fenómeno SmartCity. - Análisis y desarrollo de dispositivos IoT con GPS. - Análisis de redes LoRaWAN. - Desarrollo de una plataforma de geolocalización. - Creación de mapas, paneles y cuadros de mando de gestión. - Validación del sistema completo en un entorno productivo. - Análisis de los datos extraídos con plataformas externas. Este TFG tiene un carácter puro de aplicación real y está destinado a cubrir las necesidades para mejorar la gestión de la ciudad. En la actualidad, la ciudad de Alcoy cuenta con una red LoRaWAN totalmente operativa, con cobertura en toda la ciudad y sus parques naturales., [EN] The geolocation platform will allow municipal managers to locate vehicles, in a real environment, using IoT GPS devices connected to LoRaWAN and developed from widely used electronic boards, to respond to a real need. The key aspects to be addressed by this TFG will be: - The Smart City phenomenon. - Analysis and development of IoT devices with GPS. - Analysis of LoRaWAN networks. - Development of a geolocation platform. - Creation of maps, panels, and management dashboards. - Validation of the complete system in a production environment. This TFG has a purely real-application character and is intended to cover the needs to improve the management of the city. Nowadays, the city of Alcoy has a fully operational LoRaWAN network, with coverage throughout the city and its natural parks.

Relacijske baze podataka zasnovane su na semantičkim relacijama između entiteta koji su određeni svojim skupom atributa. Za pristup i manipulaciju podacima koristi se standardizirani jezik SQL. S druge strane, NoSQL baze podataka ne zasnivaju se na relacijskom modelu, već koriste pohranu u modalitetima dokumenata, uređenih parova ključ-vrijednost, širokih stupaca te grafova. U ovome radu implementirana je web aplikacija kojom se testirala učinkovitost dvaju sustava za upravljanje bazama podataka. Kao predstavnik upravitelja relacijskom bazom podataka odabran je sustav MySQL, a za NoSQL baze sustav MongoDB. Ispitna aplikacija omogućava testiranje potpornih baza podataka na način da se automatski može zapisivati, ažurirati, brisati i pretraživati zapise, pri čemu podaci u pojedinom zapisu mogu biti različite veličine i pri čemu se koristi različita frekvencija dotične operacije. Izlazne metrike obuhvaćaju vrijeme odziva baze podataka (tj. vrijeme izvršavanja operacije) i potrošnju računalnih resursa – opterećenje procesora i utrošak memorije. Provedeni su eksperimenti za različite konfiguracije ulaznih varijabli, a rezultati, koji ukazuju na različitu učinkovitost sustava za upravljanjem relacijskih i NoSQL baza podataka, prezentirani su na razini deskriptivne statistike., Relational databases are based on semantic relations between entities determined by a set of attributes. The standardized SQL language is used to access and manipulate the data. NoSQL databases, on the other hand, are not based on a relational model, but use documents, key-value pairs, wide-column stores, and graphs as storage modalities. In this thesis, a web application was implemented to test the effectiveness of two database management systems. The MySQL system was chosen to represent relational database management and the MongoDB system was chosen to represent NoSQL database management. The provided application allows testing the supporting databases in such a way that it is possible to automatically insert, update, delete and search records, where the data in a single record can be of different sizes and a different frequency of each operation is used. Output metrics include database response time (i.e., operation execution time) and computational resource consumption - CPU and memory load. Experiments were conducted for different configurations of input variables, and the results, indicating different efficiency of relational and NoSQL database management systems, were presented at the descriptive statistics level.

Тема выпускной квалификационной работы: «Сравнительный анализ реляционного и документо-ориентированного Ð¿Ð¾Ð´Ñ Ð¾Ð´Ð° к организации баз Ð´Ð°Ð½Ð½Ñ‹Ñ Ð² СУБД MySQL».Предметом исследования являются реляционные и документо-ориентированные базы Ð´Ð°Ð½Ð½Ñ‹Ñ Ð¿Ð¾Ð´ управлением СУБД MySQL.Цель данной работы: провести сравнительный анализ эффективности Ñ Ñ€Ð°Ð½ÐµÐ½Ð¸Ñ и поиска Ð´Ð°Ð½Ð½Ñ‹Ñ Ð² реляционной и документо-ориентированной Ð±Ð°Ð·Ð°Ñ Ð´Ð°Ð½Ð½Ñ‹Ñ . Задачи, которые были решены в Ñ Ð¾Ð´Ðµ работы:1. Сравнить особенности Ñ Ñ€Ð°Ð½ÐµÐ½Ð¸Ñ Ð´Ð°Ð½Ð½Ñ‹Ñ Ð² Ñ€ÐµÐ»ÑÑ†Ð¸Ð¾Ð½Ð½Ñ‹Ñ Ð¸ Ð½ÐµÑ€ÐµÐ»ÑÑ†Ð¸Ð¾Ð½Ð½Ñ‹Ñ ÑÑ‚Ñ€ÑƒÐºÑ‚ÑƒÑ€Ð°Ñ Ð´Ð°Ð½Ð½Ñ‹Ñ ;2. Изучить документо-ориентированные базы Ð´Ð°Ð½Ð½Ñ‹Ñ Ñ Ñ Ñ€Ð°Ð½ÐµÐ½Ð¸ÐµÐ¼ в JSON;3. Оценить эффективность Ñ Ñ€Ð°Ð½ÐµÐ½Ð¸Ñ и поиска в ÑÑ‚Ñ€ÑƒÐºÑ‚ÑƒÑ€Ð°Ñ Ð´Ð°Ð½Ð½Ñ‹Ñ , влияние индексов на время выполнения запросов;4. Выявить особенности использования MySQL как Ñ Ñ€Ð°Ð½Ð¸Ð»Ð¸Ñ‰Ð° документов;5. Провести эксперимент со сравнительным анализом скорости обработки запросов в Ñ€ÐµÐ»ÑÑ†Ð¸Ð¾Ð½Ð½Ñ‹Ñ Ñ‚Ð°Ð±Ð»Ð¸Ñ†Ð°Ñ Ð¸ JSON Ð´Ð¾ÐºÑƒÐ¼ÐµÐ½Ñ‚Ð°Ñ . Используемая в работе база Ð´Ð°Ð½Ð½Ñ‹Ñ ÑÐ¾Ð´ÐµÑ€Ð¶Ð¸Ñ‚ данные в реляционном и документо-ориентированном виде.6. Оценить скорость выполнения запросов для Ð´Ð²ÑƒÑ ÑÑ‚Ñ€ÑƒÐºÑ‚ÑƒÑ€ Ð´Ð°Ð½Ð½Ñ‹Ñ . В результате были разработаны рекомендации и определена общая ÑÑ ÐµÐ¼Ð° работы по выбору реляционной или документо-ориентированной структур для Ð¾Ð¿Ñ€ÐµÐ´ÐµÐ»ÐµÐ½Ð½Ñ‹Ñ Ð·Ð°Ð´Ð°Ñ‡., The topic of the final qualifying work: "Comparative analysis of the relational and document-oriented approach to the organization of databases in the MySQL database management system". The subject of the study is relational and document-oriented databases managed by the MySQL database management system. The purpose of this work is to conduct a comparative analysis of the efficiency of data storage and retrieval in relational and document-oriented databases. Tasks that were solved during the work:1. Compare the features of data storage in relational and non-relational data structures;2. Study document-oriented databases with storage in JSON;3. Evaluate the efficiency of storage and search in data structures, the impact of indexes on query execution time optimization;4. Identify the features of using MySQL as a document repository;5. Conduct an experiment with a comparative analysis of query processing speed in relational tables and JSON documents. The database used in the work contains data in a relational and document-oriented form.6. Evaluate the query execution speed for two data structures.As a result, recommendations were developed and a general scheme of work was defined for choosing relational or document-oriented structures for certain tasks.

Powerful abstractions such as dataframes are only as efficient as their underlying runtime system. The de-facto distributed data processing framework, Apache Spark, is poorly suited for the modern cloud-based data-science workloads due to its outdated assumptions: static datasets analyzed using coarse-grained transformations. In this paper, we introduce the Indexed DataFrame, an in-memory cache that supports a dataframe abstraction which incorporates indexing capabilities to support fast lookup and join operations. Moreover, it supports appends with multi-version concurrency control. We implement the Indexed DataFrame as a lightweight, standalone library which can be integrated with minimum effort in existing Spark programs. We analyze the performance of the Indexed DataFrame in cluster and cloud deployments with real-world datasets and benchmarks using both Apache Spark and Databricks Runtime. In our evaluation, we show that the Indexed DataFrame significantly speeds-up query execution when compared to a non-indexed dataframe, incurring modest memory overhead., Accepted for publication at IEEE IPDPS 2022

Тема выпускной квалификационной работы: «Разработка библиотеки для работы с реляционными базами Ð´Ð°Ð½Ð½Ñ‹Ñ Ð½Ð° языке Java». Целью данной работы является разработка программного обеспечения (библиотеки) для взаимодействия с реляционными базами Ð´Ð°Ð½Ð½Ñ‹Ñ Ð¸Ð· приложений, Ð½Ð°Ð¿Ð¸ÑÐ°Ð½Ð½Ñ‹Ñ Ð½Ð° языке программирования Java. Задачи работы: - Изучение Ð°Ñ€Ñ Ð¸Ñ‚ÐµÐºÑ‚ÑƒÑ€Ñ‹ и принципов работы ÑÑƒÑ‰ÐµÑÑ‚Ð²ÑƒÑŽÑ‰Ð¸Ñ Ñ€ÐµÑˆÐµÐ½Ð¸Ð¹; - Формулировка предлагаемого альтернативного Ð¿Ð¾Ð´Ñ Ð¾Ð´Ð°; - Разработка нового средства; - Анализ и сравнение свойств полученного ПО с ранее изученными существующими средствами., The topic of this thesis: "Development of a library for working with relational databases in the Java language". The purpose of this work is to develop software (a library) for interacting with relational databases from applications written in the Java programming language. This work includes the following tasks: - Studying the architecture and operating principles of existing solutions; - Formulating and proposing an alternative technical approach; - Developing a new solution; - Analyzing and comparing the properties of the developed software and the previously studied existing solutions.

Programmable logic controllers (PLCs) are everywhere today and perform critical tasks in industries. They are considered as a key component for the Industry 4.0. Before they are put into operation, it is necessary to check the accuracy of the PLC programs. This verification operation can be performed using model checkers. This stage is often long and costly and requires a domain expert who can understand the system, as well as the different model checker tools able to verify the code implemented in the controller. Furthermore, this verification often requires a conversion of the PLC code into a language understood by a model checker which can influence the behavior of the observed PLC. Hence, there is a need to propose methods and tools which could be used by technicians and engineers. The aim of this paper is to propose methods that require little work to set up and are robust to program sizes used in Industry 4.0. This paper explores some fresh ideas for human-adapted PLC code verification. We present different methods to test codes in structured text (ST) compliant with the IEC 61131-3 standard. Hence, the first idea is to test the ST code that will be directly implemented on a controller. For that, we propose a method using the model checker UPPAAL which allows us to obtain exact results on short codes. Second, we propose verifying the generic properties that a PLC program must avoid: deadlocks, non-accessible states and fugitive states or actions. To solve combinatory explosion problems encountered with the UPPAAL software, the third proposition consists of using relational databases. The same verification as previously followed can be obtained, but the search time is longer. The fourth and last proposal is to process the ST code with a neural network composed of long short-term memory layers (LSTM) to quickly determine the validity of the code. This method could give an approximation of code errors in a few seconds. The different proposed methods are supported with several examples.

The object of research is indexing methods in non-relational databases. The article reviews the most common hashing algorithms and the proposed hashing algorithm based on prime numbers and binary number system. This work is based on the basic theorem of arithmetic, which states the possibility of factorizing any natural number with a unique set of prime numbers. This approach makes it possible to use a mathematical apparatus to justify the properties of the algorithm. The algorithms considered in the article are based on the execution of a sequence of bit operations and thus cannot be resistant to collisions. This characteristic is the most important for the use of extended hashing instead of a balanced binary tree when indexing in non-relational databases. This will not only increase the speed of queries, but also allow you to use the hardware as efficiently as possible. Since the main goal of the work is to adapt the combined algorithm for non-relational databases, to achieve this goal it is necessary to have a hash function that has high resistance to collisions. The proposed algorithm was implemented using a high-level programming language C ++, as it allows you to create abstractions with low "cost" and be able to work at a low level with information. In the context of work, the most useful option is to perform operations at the bit level.As a practical part, two experiments were performed to identify different input data sets that would yield the same hashes. The main idea of the experiments was to generate random data and obtain hashes using the proposed algorithm. The result of testing is the absence of such input data sets. The results of the experiment showed that it is advisable to continue to investigate the proposed algorithm using a mathematical apparatus to analyze its properties. Ref. 4, tabl. 1., Об’єктом дослідження є методи індексування у нереляційних базах даних. У статті був зроблений огляд найбільш поширених алгоритмів хешування та запропонованого алгоритму хешування на основі простих чисел та двійкової системи числення. Ця робота грунтується на основній теоремі арифметики, яка стверджує про можливість факторизації будь-якого натурального числа унікальним набором простих чисел. Даний підхід дає можливість використовувати математичний апарат для обгрунтування властивостей алгоритму. Алгоритми, що розглянуті у статті, базуються навиконанні послідовності бітових операцій і тим самим, не можуть бути стійкими до колізій. Саме ця характеристика є найважливішою для використання розширеного хешування замість збалансованого бінарного дерева при індексації у нереляційних базах даних. Це дасть можливість не тільки підвищити швидкодію запитів, а ще дозволитьвикористовувати апаратні засоби максимально ефективно. Оскільки головною метою роботи є адаптація комбінованого алгоритму для нереляційних баз даних, то для досягнення цієї мети необхідно мати хеш-функцію, якамає високу стійкість до колізій. Запропонований алгоритм було реалізовано з використанням мови програмування високого рівня С++, оскільки вона дозволяє створювати абстракції з низькою “вартістю” та мати можливість роботи на низькому рівні з інформацією. У контексті роботи, найбільш корисною можливістю є виконання операцій набітовому рівні. В якості практичної частини було проведено два експерименти, метою яких було виявлення різних вхідних масивів даних, які на виході давали би однакові хеші. Основною ідею експериментів була генерація випадкових даних та отримання хешів, використовуючи запропонований алгоритм. Результатом тестування є відсутність таких вхідних масивів даних. Результати досліду показали доцільним продовжувати досліджувати запропонований алгоритм з використанням математичного апарату для аналізу його властивостей. Бібл. 4, табл. 1.

The object of research is indexing methods in non-relational databases. The article reviews the most common hashing algorithms and the proposed hashing algorithm based on prime numbers and binary number system. This work is based on the basic theorem of arithmetic, which states the possibility of factorizing any natural number with a unique set of prime numbers. This approach makes it possible to use a mathematical apparatus to justify the properties of the algorithm. The algorithms considered in the article are based on the execution of a sequence of bit operations and thus cannot be resistant to collisions. This characteristic is the most important for the use of extended hashing instead of a balanced binary tree when indexing in non-relational databases. This will not only increase the speed of queries, but also allow you to use the hardware as efficiently as possible. Since the main goal of the work is to adapt the combined algorithm for non-relational databases, to achieve this goal it is necessary to have a hash function that has high resistance to collisions. The proposed algorithm was implemented using a high-level programming language C ++, as it allows you to create abstractions with low "cost" and be able to work at a low level with information. In the context of work, the most useful option is to perform operations at the bit level. As a practical part, two experiments were performed to identify different input data sets that would yield the same hashes. The main idea of the experiments was to generate random data and obtain hashes using the proposed algorithm. The result of testing is the absence of such input data sets. The results of the experiment showed that it is advisable to continue to investigate the proposed algorithm using a mathematical apparatus to analyze its properties. Ref. 4, tabl. 1.

Relational databases are one of the most used data sources. However, as a storage source, they present a group of shortcomings. It is complex to store semantic knowledge in relational databases. To solve the deficiencies in knowledge representation of relational databases, one trend has been to use ontologies. Ontologies possess a richer semantic and are closer to the end user vocabulary than relational database schemas. The objective of the present research was to carry out a systematic mapping about the scenarios where relational databases and ontologies are linked to provide a better integration, query, and visualization of stored data. The mapping was carried out by applying a methodological proposal established in the literature. As outcomes of the research, it was detected that the mapping of relational databases to ontologies and the ontologies usage for the integration of heterogeneous data sources were the most common scenarios. Likewise, trends and challenges were identified in each scenario, which might deserve further research efforts in the future., Las bases de datos relacionales constituyen una de las fuentes de datos más utilizadas. Sin embargo, como fuente de almacenamiento presenta un grupo de limitaciones. En las bases de datos relacionales se dificulta almacenar conocimiento semántico. Para solventar las carencias en la representación de conocimiento de las bases de datos relacionales, una tendencia ha sido el uso de las ontologías. Las ontologías poseen una mayor riqueza semántica y son más cercanas al vocabulario del usuario final que los esquemas de las bases de datos relacionales. El objetivo de la presente investigación consiste en realizar un mapeo sistemático acerca de los escenarios en que se vinculan las bases de datos relacionales y las ontologías para brindar una mejor integración, consulta y visualización de los datos almacenados. El mapeo se llevó a cabo aplicando una propuesta metodológica establecida en la literatura. Como resultado de la investigación, se detectó que el mapeo de bases de datos relacionales a ontologías y la utilización de las ontologías para la integración de fuentes de datos heterogéneas fueron los escenarios de mayor presencia. Igualmente, se identificaron tendencias y desafíos en cada uno de los escenarios que pueden merecer mayores esfuerzos de investigación en el futuro.

U radu se opisuju različiti pristupi relacijskim bazama podataka iz objektno-orijentiranih jezika. Detaljno se obrađuje objektno-relacijsko mapiranje (engl. Object Relational Mapping, ORM) te istražuju njegove prednosti i nedostaci. Opisani su najpopularniji ORM razvojni okviri i analizirane su njihove mogućnosti, pri čemu je poseban fokus na Django razvojnom okviru, njegovoj primjeni i integraciji u razvojni proces. U sklopu rada razvijena je aplikacija u programskom jeziku Python, koja koristi ORM za komunikaciju sa PostgreSQL bazom podataka. Osim jednostavnih operacija s podacima, demonstrirana su ažuriranja strukture tablica kroz migracije, načini korištenja ORM-a za obradu podataka u drugim formatima (JSON, XML) te definirani Python upiti koji se izvršavaju nad bazom podataka. This paper focuses on different approaches to relational databases from object oriented programming languages. Object relational mapping (ORM) is discussed at lenght, and its strenghts and weaknesses are further explored. ORM frameworks are described with emphasis on their capabilities specifically focusing on Django framework, its application and integration into the developing process. Furthermore, an application programmed in Python programming language which uses ORM to communicate with PostgreSQL database is developed for the purposes of this paper. Alongside simple data operations, updating the structure of the tables, ways of using ORM to process data in other formates (JSON, XML) and defining Python queries executing over database are also demonstrated.

Cataloged from PDF version of article. Thesis (Ph.D.): Bilkent University, Department of Computer Engineering, İhsan Doğramacı Bilkent University, 2021. Includes bibliographical references (leaves 91-105). Relational databases is one of the most popular and broadly utilized infrastruc-tures to store data in a structured fashion. In order to retrieve data, users have to phrase their information need in Structured Query Language (SQL). SQL is a powerfully expressive and flexible language, yet one has to know the schema underlying the database on which the query is issued and to be familiar with SQL syntax, which is not trivial for casual users. To this end, we propose two different strategies to provide more intelligent user interfaces to relational databases by utilizing deep learning techniques. As the first study, we propose a solution for keyword mapping in Natural Language Interfaces to Databases (NLIDB), which aims to translate Natural Language Queries (NLQs) to SQL. We define the key-word mapping problem as a sequence tagging problem, and propose a novel deep learning based supervised approach that utilizes part-of-speech (POS) tags of NLQs. Our proposed approach, called DBTagger (DataBase Tagger), is an end-to-end and schema independent solution. Query recommendation paradigm, a well-known strategy broadly utilized in Web search engines, is helpful to suggest queries of expert users to the casual users to help them with their information need. As the second study, we propose Conquer, a CONtextual QUEry Recom-mendation algorithm on relational databases exploiting deep learning. First, we train local embeddings of a database using Graph Convolutional Networks to ex-tract distributed representations of the tuples in latent space. We represent SQL queries with a semantic vector by averaging the embeddings of the tuples returned as a result of the query. We employ cosine similarity over the final representations of the queries to generate recommendations, as a Witness-Based approach. Our results show that in classification accuracy of database rows as an indicator for embedding quality, Conquer outperforms state-of-the-art techniques. by Arif Usta Ph.D.

Among the many digital tools available to aid linguistic research, notably absent are tools for managing semantic and, more broadly, linguistic analysis by keeping data organized, structured, and retrievable, and providing the flexibility to construct our own analytical frameworks. In this note, we consider the advantages offered by relational databases in this respect and relate the experience of a lexicographical project. We review relational databases’ main features and workings, describe the design of the one used in said project, and present the benefits yielded by using this tool., Entre las muchas herramientas digitales disponibles para la investigación lingüística, se hace notar la ausencia de herramientas que permitan gestionar el análisis semántico y lingüístico en general, manteniendo los datos organizados, estructurados y recuperables, y brindando la flexibilidad para elaborar aparatos analíticos propios. En esta nota, consideramos las bondades que, en este sentido, ofrecen las bases de datos relacionales y referimos la experiencia de un proyecto lexicográfico. Reseñamos las principales características y el funcionamiento de las bases de datos relacionales, describimos el diseño de la utilizada en dicho proyecto y presentamos los beneficios que nos ha reportado el uso de esta herramienta.

Tema ovog diplomskog rada je razvoj sustava za pomoć pri administraciji relacijskih baza podataka. Sustav nudi grafičko web-sučelje u kojem administratori mogu upravljati podacima iz baza podataka bez korištenja upitnog jezika SQL. Funkcionalnosti uključuju čitanje, stvaranje, uređivanje i brisanje podataka. Svaka promjena podataka se bilježi te se cijela povijest promjena može na jedinstven način rekonstruirati. Dodatno sustav podržava rad s proizvoljno mnogo administratorskih uloga, od kojih svaka ima svoj skup dozvoljenih akcija. Poslužiteljski dio aplikacije razvijen je u okruženju Node, dok je za klijentski dio korištena biblioteka React. Metamodel produkcijske baze čuva se u SQLite bazi podataka koja se pakira izravno u programsko rješenje. This thesis deals with the development of a system for the administration of data in relational databases. The system offers a web based graphical user interface for administrators for managing data in a database without the knowledge of SQL. Functionalities include the standard create, read, update and delete operations. Each change of data is logged, which allows for full reconstruction of the change history. Additionally, the system supports multiple administrative roles, with their own set of allowed actions. The server side was developed using the Node environment, while the client application was built with the help of React library. Metamodel of the production database is stored in the SQLite database engine, which is packet directly in the project solution.

The paper presents the problem of material requirements planning with optimization of load distribution between work centers and workers’ groups. Moreover, it discusses the computational example for shop orders optimization. The data for this example were taken from the relational database. The method of Constraint Logic Programming (CLP) for shop orders optimization has been suggested. Using Constraint Logic Programming, the constraints may be directly introduced to the problem declaration, which is equivalent to the source code of the program. The ECLiPSe-CLP software system has been presented. It allows for solving optimization problems concerning dimensions greater than in the case of the professional mathematical programming solver “LINGO”. The application of ECLiPSe-CLP in accessing data from relational databases has been presented.

The subject of the research is the method of constructing areal, linear and volumetric anamorphoses cartographic models for the analysis of geodata. The object of the research is the process of creating various types of anamorphoses cartographic models. The aim of the work is to improve the quality of geodata perception in cartographic models based on a new approach to their visualization, provided by an unusual representation of the geodata structure while taking into account a large number of parameters that they contain. Conclusions: Methods for constructing areal, linear and volume anamorphoses cartographic models have been developed, a mathematical model and an algorithm for creating anamorphoses cartographic models using the ArcGIS software package have been obtained. The methodology for constructing areal anamorphoses cartographic models, in particular, provides, through the use of the Cartogram module, the possibility of implementing anamorphoses cartographic models of demographic position in Ukraine based on data on the population size in the ArcMap package ArcGIS. At the same time, it is also possible to obtain volumetric anamorphoses cartographic models of the demographic state. In addition, based on an analysis of the activities of Wizz Air (as an example of modern lowcost air carriers), a methodology has been developed for constructing linear anamorphoses cartographic flight models performed by this company from Ukraine in the ArcMap environment. At the same time, the mandatory components of such cartographic models are specially implemented relational geodatabases containing comprehensive flight characteristics. The technique is universal and can be used for any airline and geolocation flights. The proposed methods for constructing anamorphic cartographic models allow obtaining their various types, due to specific visualization providing an opportunity to look at the geodata under study from different sides and gain new knowledge on nearby natural and technogenic phenomena. It is anamorphoses cartographic models that provide a unique opportunity to visually present non-obvious facts with the possibility of illuminating hidden natural and geographical patterns, analyzing the relationships between environmental phenomena against the background of their defining characteristics., Предметом исследования является методика построения площадных, линейных и объемных анаморфозных картографических моделей для анализа геоданных. Объектом исследования является процесс создания различных типов анаморфозных картографических моделей. Целью работы является повышение качества восприятия геоданных в картографических моделях на основании нового подхода к их визуализации, что обеспечивается необычным представлением структуры геоданных при одновременном учете большого количества параметров, которые они содержат. Выводы. Разработаны методики построения площадных, линейных и объемных анаморфозных картографических моделей, получена математическая модель и алгоритм процесса создания анаморфозных картографических моделей с использованием программного пакета ArcGIS. Методика построения площадных анаморфозных картографических моделей, в частности, предусматривает, благодаря использованию модуля Cartogram, возможность реализации в среде ArcMap пакета ArcGIS анаморфозных картографических моделей демографической ситуации в Украине на основании данных о численности населения. При этом обеспечивается возможность получения также и объемных анаморфозных картографических моделей демографического состояния. Кроме того, на основании анализа деятельности авиакомпании Wizz Аir (в качестве примера современных lowcost-авиаперевозчиков) разработана методика построения в среде ArcMap линейных анаморфозных картографических моделей перелетов, выполняемых данной компанией из Украины. При этом обязательными составляющими таких картографических моделей являются специально внедренные реляционные базы геоданных, содержащих исчерпывающие характеристики авиарейсов. Методика является универсальной и может применяться для любых авиакомпаний и геолокаций перелетов. Предложенные методики построения анаморфозных картографических моделей позволяют получать наиразнообразнейшиеих типы, которые за счет специфической визуализации обеспечивают возможность с разных сторон взглянуть на исследуемые геоданные и получить новые знания об окружающих природных и техногенных явлениях. Именно анаморфозные картографические модели дают уникальную возможность визуально представить неочевидные факты с возможностью освещения скрытых природно-географических закономерностей и проведения анализа взаимосвязей между явлениями окружающей среды на фоне их определяющих характеристик., Предметом дослідження є методика побудови площадкових, лінійних та об’ємних анаморфозних картографічних моделей для аналізу геоданих. Об’єктом дослідження є процес створювання різноманітних типів анаморфозних картографічних моделей. Метою роботи є підвищення якості сприйняття геоданих в картографічних моделях на підставі нового підходу до їх візуалізації, що забезпечується незвичним представленням структури геоданих при одночасному врахуванні великої кількості параметрів, які вони містять. Висновки. Розроблено методики побудови площадкових, лінійних та об’ємних анаморфозних картографічних моделей, отримано математичну модель та алгоритм процесу створення анаморфозних картографічних моделей з використанням програмного пакетуArcGIS. Методика побудови площадкових анаморфозних картографічних моделей, зокрема, передбачає, завдяки використанню додаткового модуля Cartogram, можливість реалізації в середовищі ArcMap пакету ArcGIS анаморфозних картографічних моделей демографічного стану в Україні на підставі даних про кількість населення. При цьому забезпечується можливість отримання також і об’ємних анаморфозних картографічних моделей демографічного стану. Крім того, на підставі аналізу діяльності авіакомпанії Wizz Аir (у якості прикладу сучасних lowcost-авіаперевізників) розроблено методику побудови в середовищі ArcMap лінійних анаморфозних картографічних моделей перельотів, що виконуються даною компанією з України. При цьому обов’язковими складовими таких картографічних моделей є спеціально впроваджені реляційні бази геоданих, що містять вичерпні характеристики авіарейсів. Методика є універсальною і може застосовуватись для будь-яких авіакомпаній і геолокацій перельотів. Запропоновані методики побудови анаморфозних картографічних моделей дозволяють отримувати їх найрізноманітніші типи, що за рахунок специфічної візуалізації забезпечують можливість з різних боків поглянути на досліджувані геодані та отримати нові знання щодо довколишніх природних і техногенних явищ. Саме анаморфозні картографічні моделі дають унікальну можливість візуально представити неочевидні факти з можливістю висвітлення прихованих природно-географічних закономірностей та проведення аналізу взаємозв’язків між явищами довкілля на тлі їх визначальних характеристик.

Content-based image retrieval poses many problems to computer systems. The content of images has to be described by some feature extraction methods. As image databases are often very large, they are sometimes to complex to be processed by traditional computing methods. We have to use big data solutions to fast retrieve images. The paper presents a system for retrieving images in relational databases in a distributed environment. Content of the query image and images in the database is compared using global colour information and local image keypoints. Image keypoint descriptors are indexed by fuzzy sets directly in a relational database by our algorithm. The process is distributed to several machines thanks to the Apache Hadoop software framework with HDFS.

This article describes a collaborative project across three institutions to develop, implement, and evaluate a series of tutorials and case studies that highlight fundamental tools of data science—such as visualization, data manipulation, and database usage—that instructors at a wide-range of institutions can incorporate into existing statistics courses. The resulting materials are flexible enough to serve both introductory and advanced students, and aim to provide students with the skills to experiment with data, find their own patterns, and ask their own questions. In this article, we discuss a tutorial on data visualization and a case study synthesizing data wrangling and visualization skills in detail, and provide references to additional class-tested materials. R and R Markdown are used for all of the activities.

DNA sequencers output a large set of very long biological data strings that we should persist in databases rather than basic text file systems. Many different data models and database management systems (DBMS) may deal with both storage and efficiency issues regarding genomic datasets. Specifically, there is a need for handling strings with variable sizes while keeping their biological meaning. Relational database management systems (RDBMS) provide several data types that could be further explored for the genomics context. Besides, they enforce integrity, consistency, and enable good abstractions for more conventional data. We propose the relational text data type to represent and manipulate biological sequences and their derivatives. We present a logical schema for representing the core biological information, which may be inferred from a given biological conceptual data schema and the corresponding function manipulations. We implement and evaluate these stored functions into an actual RDBMS for both efficacy and efficiency. We show that it is possible to enforce basic and complex requirements for the genomic domain. We claim that the well-established relational text data type in RDBMS may appropriately handle the representation and persistency of biological sequences. We base our approach on the idea of domain-specific abstract data types that can store data with semantically defined functions while hiding those details from non-technical end-users.

O acesso globalizado à informação demanda soluções que permitam o acesso a fontes de dados descritas em diferentes idiomas. Por outro lado, grande parte da informação disponível no mundo está armazenada em bancos de dados relacionais. As principais alternativas que permitem consultar essas fontes de informação são monolíngues ou necessitam de interação do usuário. O presente estudo propõe uma solução que possibilita a um usuário, sem conhecimento prévio de esquemas ou linguagem de consulta, acessar dados em bancos de dados relacionais descritos por metadados multilíngues, utilizando uma técnica de consultas por palavras-chave. Para isso, o método proposto executa o pré-processamento da consulta expandindo e traduzindo os termos que serão mapeados para os metadados nos idiomas disponíveis, preservando a semântica pretendida pelo usuário na consulta. O pré-processamento da solução proposta potencializa o acesso aos dados ao realizar consultas em diversas fontes de dados descritas em diversos idiomas. The globalized access to information demands solutions that allow access to data sources described in different languages. On the other hand, much of the information available in the world is stored in relational databases. The main alternatives that allow consulting these sources of information are monolingual or require user interaction. The present study proposes a solution that allows a user without prior knowledge of schemas or query language, to access data in relational databases described by multilingual metadata, using keyword query technique. For this, the proposed method performs the pre-processing of the query, expanding and translating the terms that will be mapped to the metadata in the available languages, preserving the semantics intended by the user in the query. The pre-processing of the proposed solution enhances access to data by querying different datasources described in different languages.

U sklopu ovog rada napravljena je detaljna analiza mehanizama zaštite podataka kod relacijskih i nerelacijskih sustava za baze podataka. Predmet istraživanja bilo je ustvrditi mogu li mehanizmi za očuvanje integriteta podataka, kontrolu pristupa, obnovu baze u slučaju razrušenja te mehanizmi za istodobni pristup jedne nerelacijske baze podataka biti dostojna zamjena istim mehanizmima implementiranim kod relacijskih baza, koje je eventualne kompenzacijske metode potrebno implementirati na aplikativnoj razini kako bi se dobilo jednako ponašanje sustava i isplati li se neke od mehanizama žrtvovati u korist funkcionalnosti koje su specifične nerelacijskim bazama podataka. U svrhu toga izgrađena su i tri odvojena projekta te kreirane dvije baze podataka. Za izgradnju relacijske baze korišten je sustav PostgreSQL, dok je za nerelacijsku korišten MongoDB. Izgrađena je i web aplikacija koja je za cilj imala dokazati je li jednoj aplikaciji moguće korištenje obje gore spomenute vrste baza. As part of this paper, a detailed analysis of data protection mechanisms in relational and non-relational database systems was made. The subject of the research was to determine whether the mechanisms for preserving data integrity, access control, database recovery in case of destruction and concurrency of a non-relational database can be a worthy replacement for the same mechanisms implemented in relational databases, can equal system behavior be obtained and whether it pays to sacrifice some of the mechanisms in favor of functionalities that are specific to non-relational databases. For this purpose, three separate projects were built and two databases were created. The PostgreSQL system was used to build the relational database, while MongoDB was used for the non-relational one. A web application was also built with the aim of proving whether one application can use both of the above-mentioned types of databases.

El projecte tractarà de la concepció, disseny i implementació d'un mapa de contaminació ambiental a Terrassa en temps real