Ontology Driven Meta-Modeling for NoSQL Databases: A Conceptual Perspective

Banerjee, Shreya; Sarkar, Anirban

doi:10.14257/ijseia.2016.10.12.05

Cited by 11 publications

(7 citation statements)

References 9 publications

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“…In addition, this kind of models, for example 3NF subject creation in RDA, are concepts belonging to the relational database models. Today, technological enhancements on cloud computing and systems involving big data analytics have caused the emergence of non-relational database models such as NoSQL databases [26]. Hence, relational models are being replaced, or used in conjunction with non-relational databases.…”

Section: B Assessment Of the Data Analysis Processmentioning

confidence: 99%

Measureability of Functional Size in Agile Software Projects: Multiple Case Studies with COSMIC FSM

Hacaloğlu

Demirörs

2019

2019 45th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

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Functional size measurement (FSM) has been used in software engineering for decades as a main driver for estimation and significant input for other various project management activities throughout the project life span. To apply FSM accurately at the early stages of software development process, especially for estimation purposes, functional user requirements need to be available in detail as required by the adopted FSM method. However, in agile software development, requirement specifications, in general, are kept minimal. For this reason, the adjustment of the requirements to the necessary granularity level has been articulated as one of the barriers preventing the diffusion of FSM practices among agile teams. In this paper, we take a closer look at this problem in order to investigate the usability of FSM and to reveal FSM related challenges empirically through case studies on real agile projects from different software organizations. This study also provides a snapshot of agile organizations in terms of requirement specification and estimation related practices

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Section: B Assessment Of the Data Analysis Processmentioning

confidence: 99%

Measureability of Functional Size in Agile Software Projects: Multiple Case Studies with COSMIC FSM

Hacaloğlu

Demirörs

2019

2019 45th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

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“…NoSQL databases present many advantages over traditional ones, among which [10] mentions:High concurrent reading and writing of data with low latency in cloud specific systems; String scalability and availability;Lower operational and management cost; The ability to replicate and scatter data over over many servers; Efficient use of distributed indexes and RAM for data storage; The ability to dynamically add new attributes in data records; Flexible schema support; and Compatibility with the CAP (Consistency, Availability and Partition tolerance) model and BASE (Basic Availability, Soft state, Eventual Consistency) principles to comply with distributed systems characteristics.…”

Section: Characteristics and Uses Of Nosql Databasesmentioning

confidence: 99%

“…transactions) has led to a growing demand for data intensive cloud based applications and has created new challenges for big-data-era databases. [10] cites among the characteristics of new and emerging data sets: Variety (diversity of types), Velocity (rapid synthesis and flow), Volume (large size) and Veracity (i.e., biases, noise and abnormality in data). These types of datasets can range from a schema-based to a schema-less nature, and from structured to unstructured types.…”

Section: Introductionmentioning

confidence: 99%

NoSQL Databases: Yearning for Disambiguation

Asaad,

Baïna,

Ghogho

2020

Preprint

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The demanding requirements of the new Big Data intensive era raised the need for flexible storage systems capable of handling huge volumes of unstructured data and of tackling the challenges that traditional databases were facing. NoSQL Databases, in their heterogeneity, are a powerful and diverse set of databases tailored to specific industrial and business needs. However, the lack of theoretical background creates a lack of consensus even among experts about many NoSQL concepts, leading to ambiguity and confusion. In this paper, we present a survey of NoSQL databases and their classification by data model type. We also conduct a benchmark in order to compare different NoSQL databases and distinguish their characteristics. Additionally, we present the major areas of ambiguity and confusion around NoSQL databases and their related concepts, and attempt to disambiguate them.

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“…Our research is complementary to this study because it explores how to take advantage of the unique features of the prototypes of column‐oriented NoSQL databases using OWL ontologies. In the work of Banerjee and Sarkar, an ontology‐driven metamodel called Ontology Driven NoSQL Data Model is proposed, to achieve common abstraction over varied types of databases. This approach also leads to semantic interoperability among distinct databases.…”

Section: Background Concepts and Literature Reviewmentioning

confidence: 99%

Tool for materializing OWL ontologies in a column‐oriented database

2018

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Summary Big data technologies enable people to store, analyze, and utilize large amounts of complex data effectively. In this context, NoSQL (Not only Structured Query Language) databases have emerged as the most commonly used infrastructure for handling big Resource Description Framework data. In this paper, we present our proposal to materialize classified OWL (Web Ontology Language) ontologies in a NoSQL database. This materialization process enables the distributed storage of Resource Description Framework data by exploiting the inherent distribution of the NoSQL database nodes. Furthermore, this approach supposes the first step toward a novel approach to scalable OWL reasoning, which enables scalable Linked Data reasoning. To validate our proposal, we developed a prototype for a tool that stores an OWL ontology in a Cassandra database following our approach. Finally, we introduce our reasoning strategy to compute the ontology closure using this Cassandra database.

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Ontology Driven Meta-Modeling for NoSQL Databases: A Conceptual Perspective

Abstract: In cloud environment, data intensive applications required to interact with various kinds of databases ranged from SQL (Structured Query Language)

Cited by 11 publications

References 9 publications

Measureability of Functional Size in Agile Software Projects: Multiple Case Studies with COSMIC FSM

Measureability of Functional Size in Agile Software Projects: Multiple Case Studies with COSMIC FSM

NoSQL Databases: Yearning for Disambiguation

Tool for materializing OWL ontologies in a column‐oriented database

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