Query Technologies Research Articles

A survey on the efficiency, reliability, and security of data query in blockchain systems

With the emergence of digital currencies, blockchain systems have been committed to the efficient and trusted storage of data, building decentralized, tamper-proof, persistent, and anonymous digital ledger. Researchers have devoted considerable attention to query methods on blockchain platforms, leading to numerous developments and advancements. There is an imperative need for a comprehensive investigation of all these efforts, as well as their most recent progress and results. This study strives to provide a comprehensive and thorough survey of notable works and recent progress related to query technologies and theories. In general, blockchain query methods rely on utilizing distributed databases, data indexing structures, and cryptographic algorithms to achieve efficient, verifiable, and secure queries. Beyond the above, we examine existing issues of blockchain query technologies and theories on query efficiency, reliability, and security. In the end, this work concludes with a summarization on typical scenarios of blockchain query schemes, as well as a discussion of future challenges to be addressed in future research.

A cross-technology benchmark for incremental graph queries

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.

METHODS FOR CONSTRUCTING AND IMPLEMENTING A DIGITAL GEOINFORMATION MODEL USING MS EXCEL IN A SCHOOL INFORMATICS COURSE

The article describes a methodology for teaching the technology of constructing a geoinformation model using MS Excel. This methodology is built taking into account the Federal State Educational Standard of Secondary General Education and the requirements provided for in the implementation of the approximate educational program of the course "Informatics" along the line "Modeling and Formalization". The authors proposed a laboratory work, within which the students, firstly, learn the new capabilities of the MS Excel package, associated with the use of Power Query and 3D Maps technologies; secondly, they get the initial skills in processing "raw" data in real time; thirdly, they learn the modeling process, in fact, without going beyond the competence of the school informatics course. In general, the laboratory work describes the technology of geoinformation modeling of real processes and has great variability, and therefore can be easily adapted for research and visualization of other updated data. The format for describing the methodology for performing laboratory work is presented in the form of the traditional Key-by-Key technology, which is widely used in obtaining professional competencies in the field of information technology.

A survey of RDF management technologies and benchmark datasets

With the fast development of semantic web and some other areas, the amount of resource description framework (RDF) data has increased significantly. How to efficiently manage these masses of RDF data has become a challenging task, and has attracted many scholars to research. This paper introduces the state-of-the-art of the RDF storage and query technologies according to some classification criteria. In addition, several prevailing benchmark datasets are introduced and compared. Finally, research challenges and opportunities in future are discussed.

Evaluation of Optimization Strategies for Incremental Graph Queries

The last decade brought considerable improvements in distributed storage and query technologies, known as NoSQL systems. These systems provide quick evaluation of simple retrieval operations and are able to answer certain complex queries in a scalable way, albeit not instantly. Providing scalability and quick response times at the same time for querying large data sets is still a challenging task. Evaluating complex graph queries is particularly difficult, as it requires lots of join, antijoin and filtering operations. This paper presents optimization techniques used in relational database systems and applies them on graph queries. We evaluate various query plans on multiple datasets and discuss the effect of different optimization techniques.

Generating IFC models from heterogeneous data using semantic web

Purpose – This paper aims to develop a framework to represent semantic web query results as Industry Foundation Class (IFC) building models. The subject of interoperability has received considerable attention in the construction literature in recent years. Given the distributed, semantically heterogeneous data sources, the problem is to retrieve information accurately and with minimal human intervention by considering their semantic descriptions. Design/methodology/approach – This paper provides a framework to translate semantic web query results into the XML representations of IFC schema and data. Using the concepts and relationships in an IFC schema, the authors first develop an ontology to specify an equivalent IFC entity in the query results. Then, a mapping structure is defined and used to translate and fill all query results into an ifcXML document. For query processing, the proposed framework implements a set of predefined query mappings between the source schema and a corresponding IFC output schema. The resulting ifcXML document is validated with an XML schema validating parser and then loaded into a building information modeling (BIM) authoring tool. Findings – The research findings indicate that semantic web technology can be used, accurately and with minimal human intervention, to maintain semantic-level information when transforming information between web-based and BIM formats. The developed framework for representing IFC-compatible outputs allows BIM users to query and access building data at any time over the web from data providers. Originality/value – Currently, the results of semantic web queries are not supported by BIM authoring tools. Thus, the proposed framework utilizes the capabilities of semantic web and query technologies to transform the query results to an XML representation of IFC data.

Performance comparison of query-based techniques for anti-pattern detection

ContextProgram queries play an important role in several software evolution tasks like program comprehension, impact analysis, or the automated identification of anti-patterns for complex refactoring operations. A central artifact of these tasks is the reverse engineered program model built up from the source code (usually an Abstract Semantic Graph, ASG), which is traditionally post-processed by dedicated, hand-coded queries. ObjectiveOur paper investigates the costs and benefits of using the popular industrial Eclipse Modeling Framework (EMF) as an underlying representation of program models processed by four different general-purpose model query techniques based on native Java code, OCL evaluation and (incremental) graph pattern matching. MethodWe provide in-depth comparison of these techniques on the source code of 28 Java projects using anti-pattern queries taken from refactoring operations in different usage profiles. ResultsOur results show that general purpose model queries can outperform hand-coded queries by 2–3 orders of magnitude, with the trade-off of an increased in memory consumption and model load time of up to an order of magnitude. ConclusionThe measurement results of usage profiles can be used as guidelines for selecting the appropriate query technologies in concrete scenarios.

Access Efficiency to Data in DIM DBMS

In the article is provided the review of tools used in new type object DBMS for increasing the efficiency of access to data. Described object DBMS features based on the use of the classes of objects relations as objects sets (inheritance, inclusion, interaction and history) and objects relations (inheritance, internal inheritance, inclusion, internal inclusion, interaction and history). description of subject domain is entered by means of an object and dynamic data model (OD-model), and DBMS completeness for any OD-model is justified. ODQL object query language allowing to combine the exact description complexity with the simplicity of use due to two query levels introduction is described. For the elucidation of the most effective way of the appeal to DBMS the study of various query technologies for this environment is conducted, and mechanisms for users work with it are developed and realized. For this purpose a software complex necessary for work with DBMS is developed. description of the DIM Navigator main software development concepts, necessary for data manipulation opportunity in the available DB by means of the graphic interface is provided. Software development The Generator of ODQL-queries is considered which is necessary for simplification of query creation to DBMS, needlessly for the user to know the syntax of a modern query language. Problems of converting data from the existing DBMS in DBMS are considered. article is published in the author’s wording

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In the article the review of tools used in a new type object DBMS for increasing the efficiency of access to data is provided. Some object DIM DBMS features based on the use of the classes of object relations as object sets (inheritance, inclusion, interaction and history) and object relations (inheritance, internal inheritance, inclusion, internal inclusion, interaction and history) are described. The description of the subject domain is entered by means of an object and dynamic data model (OD-model), and DIM DBMS completeness for any OD-model is justified. An ODQL object query language allowing to combine the exact description complexity with the simplicity of use due to two query level introduction is described. For the elucidation of the most effective way of the appeal to DIM DBMS the study of various query technologies for this environment is conducted, and mechanisms for user work with it are developed and realized. Software development ”The Generator of ODQL-queries” is considered which is necessary for simplification of query creation to DIM DBMS, needless for the user to know the syntax of a modern query language. Problems of converting data from the existing DBMS into DIM DBMS are considered.

A Theme-Oriented Data Automatic Organization Method

In order to automatic organization data according to customers’ requirement, and improve the data reusability, an idea of data meta-component is proposed, the definition of data meta-component is present, the model of data meta-component is established. A theme-oriented data automatic organization method is proposed; on the basis of data mete-component, the theme domain data automatic organization is realized by means of nature language processing, semantic query, association analysis, share distribution, and other technologies; experimental results show that this method is feasible and effective.

CQPweb — combining power, flexibility and usability in a corpus analysis tool

CQPweb is a new web-based corpus analysis system, intended to address the conflicting requirements for usability and power in corpus analysis software. To do this, its user interface emulates the BNCweb system. Like BNCweb, CQPweb is built on two separate query technologies: the IMS Open Corpus Workbench and the MySQL relational database. CQPweb’s main innovative feature is its flexibility; its more generalised data model makes it compatible with any corpus. The analysis options available in CQPweb include: concordancing; collocations; distribution tables and charts; frequency lists; and keywords or key tags. An evaluation of CQPweb against criteria earlier laid down for a future web-based corpus analysis tool suggests that it fulfils many, but not all, of the requirements foreseen for such a piece of software. Despite some limitations, in making a sophisticated query system accessible to untrained users, CQPweb combines ease of use, power and flexibility to a very high degree.

Delay aware querying with Seaweed

Large highly distributed data sets are poorly supported by current query technologies. Applications such as endsystem-based network management are characterized by data stored on large numbers of endsystems, with frequent local updates and relatively infrequent global one-shot queries.The challenges are scale (103 to 109 endsystems)and endsystem unavailability. In such large systems, a significant fraction of endsystems and their data will be unavailable at any given time. Existing methods to provide high data availability despite endsystem unavailability involve centralizing, redistributing or replicating the data. At large scale these methods are not scalable.We advocate a design that trades query delay for completeness, incrementally returning results as endsystems become available. We also introduce the idea of completeness prediction, which provides the user with explicit feedback about this delay/completeness trade-off. Completeness prediction is based on replication of compact data summaries and availability models. This metadata is orders of magnitude smaller than the data.Seaweed is a scalable query infrastructure supporting incremental results, online in-network aggregation and completeness prediction. It is built on a distributed hash table (DHT) but unlike previous DHT based approaches it does not redistribute data across the network. It exploits the DHT infrastructure for failure resilient metadata replication, query dissemination, and result aggregation. We analytically compare Seaweed's scalability against other approaches and also evaluate the Seaweed prototype running on a large-scale network simulator driven by real-world traces.