Data: storage and processing

2019 ◽  
Author(s):  
Эдуард Дадян ◽  
Eduard Dadyan
Keyword(s):  
Data Storage ◽  
Relational Databases ◽  
Data Access ◽  
Analysis Data ◽  
Knowledge Bases ◽  
Data Models ◽  
Distributed Data ◽  
Distributed Data Processing ◽  
Entity Relationship ◽  
Entity Relationship Diagram

The textbook examines and analyzes: databases and DBMS, data and computers, database concept, DBMS architecture, infological, datological and physical data models, date types of logical data models, data presentation using the model " Entity-Relationship, Entity-Relationship diagram, data integrity. An overview of the notation used to build the entity-link diagrams is given. In detail: relational databases, operations with relational database tables, relational relationship generation rules from entity to link model. The following sections are presented in detail: fast data access tools, SQL language, physical database organization, client-server architecture, distributed data processing and database server structure. The textbook also formulates conceptual bases of the concept "knowledge", sets out concepts and definitions of knowledge, knowledge bases, models of representation of knowledge. Here are the principles of building systems for data analysis-data warehousing, data models used in building data warehouses. The tutorial ends with the consideration of data protection issues.

Modeling and Indexing Spatiotemporal Trajectory Data in Non-Relational Databases

2016 ◽  
pp. 133-162 ◽  
Author(s):  
Berkay Aydin ◽  
Vijay Akkineni ◽  
Rafal A Angryk
Keyword(s):  
Data Storage ◽  
Relational Databases ◽  
Large Scale ◽  
Database Systems ◽  
Distributed Database ◽  
Data Models ◽  
Trajectory Data ◽  
Nosql Databases ◽  
Distributed Database Systems ◽  
Partitioned Data

With the ever-growing nature of spatiotemporal data, it is inevitable to use non-relational and distributed database systems for storing massive spatiotemporal datasets. In this chapter, the important aspects of non-relational (NoSQL) databases for storing large-scale spatiotemporal trajectory data are investigated. Mainly, two data storage schemata are proposed for storing trajectories, which are called traditional and partitioned data models. Additionally spatiotemporal and non-spatiotemporal indexing structures are designed for efficiently retrieving data under different usage scenarios. The results of the experiments exhibit the advantages of utilizing data models and indexing structures for various query types.

A novel method for providing relational databases with rich semantics and natural language processing

2017 ◽  
Vol 30 (3) ◽  
pp. 503-525
Author(s):  
Kamal Hamaz ◽  
Fouzia Benchikha
Keyword(s):  
Natural Language ◽  
Data Storage ◽  
Language Processing ◽  
Relational Database ◽  
Relational Databases ◽  
Data Access ◽  
New Techniques ◽  
Content Type ◽  
Semantic Tree ◽  
Novel Method

Purpose With the development of systems and applications, the number of users interacting with databases has increased considerably. The relational database model is still considered as the most used model for data storage and manipulation. However, it does not offer any semantic support for the stored data which can facilitate data access for the users. Indeed, a large number of users are intimidated when retrieving data because they are non-technical or have little technical knowledge. To overcome this problem, researchers are continuously developing new techniques for Natural Language Interfaces to Databases (NLIDB). Nowadays, the usage of existing NLIDBs is not widespread due to their deficiencies in understanding natural language (NL) queries. In this sense, the purpose of this paper is to propose a novel method for an intelligent understanding of NL queries using semantically enriched database sources. Design/methodology/approach First a reverse engineering process is applied to extract relational database hidden semantics. In the second step, the extracted semantics are enriched further using a domain ontology. After this, all semantics are stored in the same relational database. The phase of processing NL queries uses the stored semantics to generate a semantic tree. Findings The evaluation part of the work shows the advantages of using a semantically enriched database source to understand NL queries. Additionally, enriching a relational database has given more flexibility to understand contextual and synonymous words that may be used in a NL query. Originality/value Existing NLIDBs are not yet a standard option for interfacing a relational database due to their lack for understanding NL queries. Indeed, the techniques used in the literature have their limits. This paper handles those limits by identifying the NL elements by their semantic nature in order to generate a semantic tree. This last is a key solution towards an intelligent understanding of NL queries to relational databases.

scholarly journals ABOUT DATA MODELING SUBJECT DOMAINS PRACTICE-ORIENTED DIRECTION FOR UNIVERSAL SYSTEM OF STORAGE AND PROCESSING DATA

2017 ◽  
pp. 4-12 ◽  
Author(s):  
L. V. Rudikova ◽  
E. V. Zhavnerko
Keyword(s):  
Data Warehouse ◽  
Data Storage ◽  
Data Modeling ◽  
Analysis Data ◽  
Data Models ◽  
Universal System ◽  
Current Time ◽  
High Data ◽  
General Data Model ◽  
Subject Domains

This article describes data modeling for practice-oriented subject domains they are basis of general data model for data warehouse creation. Describes short subject domains characteristic relationship to different types of any human activities at the current time. Offered appropriate data models, considered relationship between them as data processing and data warehouse creation, which can be built on information data storage technology and which has some characteristics as extensible complex subject domain, data integration, which get from any data sources, data time invariance with required temporal marks, relatively high data stability, search necessary compromises in data redundancy, system blocks modularity, flexibility and extensibility of architecture, high requirements to data storage security. It’s proposed general approach of data collection and data storage, appropriate data models, in the future, will integrate in one database scheme and create generalized scheme of data warehouse as type «constellation of facts». For getting of data models applies structural methodology and consider general principles of conceptual design. Using complex system, which can work with some information sources and represent data in convenient view for users will in-demand for analysis data selected subject domains and determination of possible relationships.

scholarly journals Perancangan Program Pengelolaan Transaksi Pembelian dan Penjualan Perlengkapan Olahraga Pada Abadi Sport

2018 ◽  
Vol 7 (1) ◽  
pp. 61
Author(s):  
Dede Nurahman ◽  
Feri Prasetyo ◽  
Eka Pratama
Keyword(s):  
Data Storage ◽  
Literature Study ◽  
Activity Diagram ◽  
Slow Presentation ◽  
Efficient Data ◽  
Waterfall Model ◽  
Entity Relationship ◽  
Entity Relationship Diagram ◽  
Observation Method ◽  
Analytical Tools

Abstract  –  Purchasing and Sale of Goods System is a system that provides information services in the form of transaction data purchase and sale of goods and stock of goods. The existence of this information system is important. In this case, ABADI SPORT serve as a place of research, because the system of purchase and sale of goods in the place has not been well managed so that there is often a mistake in making the existing report, ineffective and efficient data storage because only archived. So as to complicate the search of data, the form of invoice is similar to causing an error in Recording, slow presentation of information required by the leadership. The method used is structured programming language and development method using waterfall model. Data collection method used is using observation method, interview, literature study. Analytical tools used are Use Case Diagram, Activity Diagram, Entity Relationship Diagram (ERD), Logical Record Structure (LRS). The software used is: NetBeans IDE 8.1, java 1.7.7, and Xampp 1.7.7. The design of this program is built in order to provide convenience in processing data purchase and sale both from purchases to suppliers and sales to customers as well as processing reports purchase and sales to be more precise and accurate. Key Word: Program Design, Purchasing and Sales Program

scholarly journals Multi-Authority Secure Database for Enabling Authorized Encrypted Search with Privacy Preserving on Healthcare Databases

2020 ◽  
Vol 9 (1) ◽  
pp. 1671-1674
Keyword(s):  
Data Storage ◽  
Ad Hoc ◽  
Research Work ◽  
Data Access ◽  
Healthcare Sector ◽  
Distributed Data ◽  
Security Issues ◽  
Multiple Data ◽  
Access Scheme ◽  
Secure Data

Now a day’s in medical field number of application’s will develop for overcome the complexity of previous work. By using information technology and computer science provide various new techniques and medical equipment’s has improved digitalization in healthcare sector. In existing system much more advancement is providing to overcome the time and money of patients and perform exact treatments and store patient’s confidential records in securely but most important issues are security. To address the existing security issues to design and develop the proposed research work on security i.e. for patient’s confidential health data records in database servers. Existing work during data transmission can only protect the patient’s data records but they can’t stop the insider attacks. In proposed research work, first implement front end security with the help of keylogging technique, second to store patient’s confidential data in multiple data servers or chunks and to prevent the insider attacks and third and most important is access policy of search for encrypted data of multi-authority. The main contribution of this research work to assign patients data records in different chunks securely and applying the cryptosystems for security goals of a patient’s confidential records. Especially, proposed work advantages of SHA hashing technique to perform each and every user for access of particular data records. This research work explores secure data storage and sharing using proposed AES 128 encryption algorithm and Role Base Access Control (RBAC) for secure data access scheme for end user. This work also carried out backup server approach it works like proxy storage server for ad hoc data recovery for all distributed data servers.

A Data Model for Invertebrate Paleontological Collections Information

2000 ◽  
Vol 10 ◽  
pp. 105-108
Author(s):  
Paul J. Morris
Keyword(s):  
Data Model ◽  
Data Models ◽  
Added Value ◽  
Formal Description ◽  
Museum Collections ◽  
Collections Management ◽  
Type Specimens ◽  
Paleontological Data ◽  
Entity Relationship ◽  
Entity Relationship Diagram

PALEONTOLOGICAL data are complex. They involve a wide variety of different classes of information relating physical objects, such as type specimens to all manner of different things including collecting localities, systematic concepts such as a genus, and published statements about stratigraphic or systematic placement. This data model has been designed to describe the structure of information used in invertebrate paleontological museum collections (Appendix IX).The heart of the data model is the concept of Collections Objects. Collections objects are fossils and other such things that make up the material of invertebrate paleontological museum collections. Collections management involves essentially tracking collections objects and maintaining the data that is associated with collections objects. The key data associated with collections objects are their provenance (where and when they came from) and added value data such as what names, if any, have been applied to them, or what publications they have been illustrated in.A data model is a formal description of some set of information. It consists of a picture of the main concepts involved (the Entity-Relationship diagram) and a set of formal written documentation that defines these concepts and their relationships with each other. For an introduction to the concepts and symbols of data models see the references below, or good summaries provided in the ASC and PaleoBank models.

scholarly journals IMPLEMENTASI METODE CERTAINTY FACTOR PADA SISTEM PAKAR PENDETEKSI KERUSAKAN PRINTER

2020 ◽  
Vol 14 (1) ◽  
pp. 40-51
Author(s):  
Putu Bagus Adidyana Anugrah Putra
Keyword(s):  
Analysis Data ◽  
Flow Diagram ◽  
Unit Testing ◽  
Certainty Factor ◽  
Essential Requirement ◽  
Requirements Definition ◽  
Stage System ◽  
Data Flow Diagram ◽  
Entity Relationship ◽  
Entity Relationship Diagram

The printer is an essential requirement in supporting the daily activities of several business fields, namely printing, design, office, and others. Damage to the printer needs proper handling and right so that if not handled immediately will be detrimental to the user. The design of this system uses the Waterfall software development method which consists of five stages, namely requirements definition (feature determination stage), system and software design includes two activities, namely analysis (Data Flow Diagram and Entity Relationship Diagram) (table design, navigation design using a sitemap and interface), implementation and unit testing (realize and test the design results), integration and system testing and operation and maintenance (maintenance). The system was tested with Blackbox testing, which resulted in the system's functionality running well. The calculation process using the Certainty Factor will produce damage experienced and the solution

scholarly journals Analysis of data integrity and storage quality of a distributed storage system

2021 ◽  
Vol 251 ◽  
pp. 02035
Author(s):  
Adrian Eduard Negru ◽  
Latchezar Betev ◽  
Mihai Carabaș ◽  
Costin Grigoraș ◽  
Nicolae Țăpuş ◽  
...  
Keyword(s):  
Data Storage ◽  
Distributed Storage ◽  
Storage System ◽  
Essential Element ◽  
Data Access ◽  
Distributed Data ◽  
Distributed Data Storage ◽  
Data Lifetime ◽  
Operational Issues ◽  
And Storage

CERN uses the world’s largest scientific computing grid, WLCG, for distributed data storage and processing. Monitoring of the CPU and storage resources is an important and essential element to detect operational issues in its systems, for example in the storage elements, and to ensure their proper and efficient function. The processing of experiment data depends strongly on the data access quality, as well as its integrity and both of these key parameters must be assured for the data lifetime. Given the substantial amount of data, O(200 PB), already collected by ALICE and kept at various storage elements around the globe, scanning every single data chunk would be a very expensive process, both in terms of computing resources usage and in terms of execution time. In this paper, we describe a distributed file crawler that addresses these natural limits by periodically extracting and analyzing statistically significant samples of files from storage elements, evaluates the results and is integrated with the existing monitoring solution, MonALISA.

scholarly journals Self-Healing Cloud Computing

2021 ◽  
pp. 80-89
Author(s):  
Sergei Petrenko ◽  
Keyword(s):  
Data Processing ◽  
Data Storage ◽  
Fault Tolerant ◽  
Global Market ◽  
Annual Growth Rate ◽  
Distributed Data ◽  
Self Healing ◽  
Private Cloud ◽  
Distributed Data Processing ◽  
Container Orchestration

Purpose of the article: development of tools for building a cyber-stable private cloud. The relevance of building a cyber-resilient private cloud is confirmed by the dynamics of growth in the market volume of relevant solutions. According to PRnewswire, the market for private cloud solutions will reach 183 billion USD by 2025. At the same time, the average annual growth rate of the CAGR will be 29.4% during the forecast period. According to the analytical company Grand view research, the global market for private cloud solutions in 2018 was estimated at 30.24 billion US dollars, and it is expected that in the period from 2019 to 2025, the CAGR will be 29.6%. Research methods: It uses a set of open-source solutions that applies the advanced cloud technologies, including distributed data processing models and methods, container orchestration technologies, softwaredefined data storage architecture, and a universal database. Results: Developed tools for building a cyber-stable private cloud. Considered a possible approach to building a cyber-resilient private cloud based on the well-known and proprietary models and methods of the artificial immune systems (AIS), as well as technologies for distributed data processing, container orchestration, and others. In addition, the unique centralized fault-tolerant logging and monitoring subsystem has been developed for the described platform, as well as an innovative cybersecurity subsystem based on the following original technologies.

AN EXECUTABLE META MODEL FOR RE-ENGINEERING OF DATABASE SCHEMAS

1995 ◽  
Vol 04 (02n03) ◽  
pp. 237-258 ◽  
Author(s):  
MANFRED A. JEUSFELD ◽  
UWE A. JOHNEN
Keyword(s):  
Data Model ◽  
Cost Effective ◽  
Data Models ◽  
Meta Model ◽  
Cost Effective Method ◽  
Mapping Process ◽  
Entity Relationship ◽  
Entity Relationship Diagram ◽  
Entity Relationship Diagrams ◽  
Target Data

A logical database schema, e.g. a relational one, is the implementation of a specification, e.g. an entity-relationship diagram. Upcoming new data models require a cost-effective method for mapping from one data model to the other. We present an approach where the mapping process is divided into three parts. The first part reformulates the source and target data models into a so-called meta model. The second part classifies the input schema into the meta model, yielding a data model-independent representation. The third part synthesizes the output schema in terms of the target data model. The meta model, the data models as well as the schemas are all represented in the logic-based formalism of O-Telos. Its ability to quantify across data model concepts is the key to classifying schema elements independently of their data model. A prototype has been implemented on top of the deductive object base manager ConceptBase for the mapping of relational schemas to entity-relationship diagrams. From this, a C++-based tool has been derived as part of a commercial CASE environment for database applications.

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