scholarly journals Modeling and Management Big Data in Databases—A Systematic Literature Review

2020 ◽  
Vol 12 (2) ◽  
pp. 634 ◽  
Author(s):  
Diana Martinez-Mosquera ◽  
Rosa Navarrete ◽  
Sergio Lujan-Mora

The work presented in this paper is motivated by the acknowledgement that a complete and updated systematic literature review (SLR) that consolidates all the research efforts for Big Data modeling and management is missing. This study answers three research questions. The first question is how the number of published papers about Big Data modeling and management has evolved over time. The second question is whether the research is focused on semi-structured and/or unstructured data and what techniques are applied. Finally, the third question determines what trends and gaps exist according to three key concepts: the data source, the modeling and the database. As result, 36 studies, collected from the most important scientific digital libraries and covering the period between 2010 and 2019, were deemed relevant. Moreover, we present a complete bibliometric analysis in order to provide detailed information about the authors and the publication data in a single document. This SLR reveal very interesting facts. For instance, Entity Relationship and document-oriented are the most researched models at the conceptual and logical abstraction level respectively and MongoDB is the most frequent implementation at the physical. Furthermore, 2.78% studies have proposed approaches oriented to hybrid databases with a real case for structured, semi-structured and unstructured data.

2021 ◽  
Vol 312 ◽  
pp. 09002
Author(s):  
Ali Aghazadeh Ardebili ◽  
Antonella Longo ◽  
Antonio Ficarella

In the industry 4.0 era, the Smart Energy System (SES) should be able to address the emerging challenges of digitization and socioeconomic/ecologic transition along with other critical entities of the society. However, because of the complexity of this system, both researchers and practitioners are seeking an agile and smart solution. The main motive of this review is to investigate the applications and implementation of Digital Twin (DT) in the provision of energy services. Research Questions (RQ) of this study include: RQ1: What are the applications of DT in SES and how effective is DT in that use case of EIoT? RQ2: Which issues of an SES can be addressed efficiently by using DT? Through answering the mentioned questions, the current study is heading to following objectives (O), O1: Describe the state of the art of DT in SES. O2: Develop a direction for energy 4.0 management through listing the applications, challenges and important factors of implementing DTs. O3: Provide a list of various approaches in employing DT in the scope of SES. The current study is a systematic literature review (SLR), based on SCOPUS, WOS and IEEE digital libraries. Two keywords (namely “Digital Twin” and “Energy Systems”) have been first used. To achieve the final list of articles, 2 levels of screening have been conducted. The first Screening was based on the relevance of the results concerning research objectives. The second screening was an abstract study. The exclusion/inclusion criteria in the abstract study were based on the research questions. The papers that have the potential of answering one of the research questions have been included. Since the implementation of DT is a rather new topic, both backward snowballing and forward snowballing strategies are implemented to finalize the article selection phase. 60 articles identified by searching through scientific databases and 11 articles have been appended to the list during the snowballing process. The results of the current review provide a managerial guideline for practitioners that are heading to utilize DT, along with an anthology of DT within SES scope to feed possible future studies.


Author(s):  
Abdulkadir Seker ◽  
Banu Diri ◽  
Halil Arslan ◽  
Mehmet Fatih Amasyalı

GitHub is the most common code hosting and repository service for open-source software (OSS) projects. Thanks to the great variety of features, researchers benefit from GitHub to solve a wide range of OSS development challenges. In this context, the authors thought that was important to conduct a literature review on studies that used GitHub data. To reach these studies, they conducted this literature review based on a GitHub dataset source study instead of a keyword-based search in digital libraries. Since GHTorrent is the most widely known GitHub dataset according to the literature, they considered the studies that cite this dataset for the systematic literature review. In this study, they reviewed the selected 172 studies according to some criteria that used the dataset as a data source. They classified them within the scope of OSS development challenges thanks to the information they extract from the metadata of studies. They put forward some issues about the dataset and they offered the focused and attention-grabbing fields and open challenges that we encourage the researchers to study on them.


2020 ◽  
Vol 11 (4) ◽  
pp. 1-26
Author(s):  
Abdulkadir Seker ◽  
Banu Diri ◽  
Halil Arslan ◽  
Mehmet Fatih Amasyalı

GitHub is the most common code hosting and repository service for open-source software (OSS) projects. Thanks to the great variety of features, researchers benefit from GitHub to solve a wide range of OSS development challenges. In this context, the authors thought that was important to conduct a literature review on studies that used GitHub data. To reach these studies, they conducted this literature review based on a GitHub dataset source study instead of a keyword-based search in digital libraries. Since GHTorrent is the most widely known GitHub dataset according to the literature, they considered the studies that cite this dataset for the systematic literature review. In this study, they reviewed the selected 172 studies according to some criteria that used the dataset as a data source. They classified them within the scope of OSS development challenges thanks to the information they extract from the metadata of studies. They put forward some issues about the dataset and they offered the focused and attention-grabbing fields and open challenges that we encourage the researchers to study on them.


2022 ◽  
pp. 2134-2164
Author(s):  
Abdulkadir Seker ◽  
Banu Diri ◽  
Halil Arslan ◽  
Mehmet Fatih Amasyalı

GitHub is the most common code hosting and repository service for open-source software (OSS) projects. Thanks to the great variety of features, researchers benefit from GitHub to solve a wide range of OSS development challenges. In this context, the authors thought that was important to conduct a literature review on studies that used GitHub data. To reach these studies, they conducted this literature review based on a GitHub dataset source study instead of a keyword-based search in digital libraries. Since GHTorrent is the most widely known GitHub dataset according to the literature, they considered the studies that cite this dataset for the systematic literature review. In this study, they reviewed the selected 172 studies according to some criteria that used the dataset as a data source. They classified them within the scope of OSS development challenges thanks to the information they extract from the metadata of studies. They put forward some issues about the dataset and they offered the focused and attention-grabbing fields and open challenges that we encourage the researchers to study on them.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rajesh Kumar Singh ◽  
Saurabh Agrawal ◽  
Abhishek Sahu ◽  
Yigit Kazancoglu

PurposeThe proposed article is aimed at exploring the opportunities, challenges and possible outcomes of incorporating big data analytics (BDA) into health-care sector. The purpose of this study is to find the research gaps in the literature and to investigate the scope of incorporating new strategies in the health-care sector for increasing the efficiency of the system.Design/methodology/approachFora state-of-the-art literature review, a systematic literature review has been carried out to find out research gaps in the field of healthcare using big data (BD) applications. A detailed research methodology including material collection, descriptive analysis and categorization is utilized to carry out the literature review.FindingsBD analysis is rapidly being adopted in health-care sector for utilizing precious information available in terms of BD. However, it puts forth certain challenges that need to be focused upon. The article identifies and explains the challenges thoroughly.Research limitations/implicationsThe proposed study will provide useful guidance to the health-care sector professionals for managing health-care system. It will help academicians and physicians for evaluating, improving and benchmarking the health-care strategies through BDA in the health-care sector. One of the limitations of the study is that it is based on literature review and more in-depth studies may be carried out for the generalization of results.Originality/valueThere are certain effective tools available in the market today that are currently being used by both small and large businesses and corporations. One of them is BD, which may be very useful for health-care sector. A comprehensive literature review is carried out for research papers published between 1974 and 2021.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shahriar Akter ◽  
Md Afnan Hossain ◽  
Qiang (Steven) Lu ◽  
S.M. Riad Shams

PurposeBig data is one of the most demanding topics in contemporary marketing research. Despite its importance, the big data-based strategic orientation in international marketing is yet to be formed conceptually. Thus, the purpose of this study is to systematically review and propose a holistic framework on big data-based strategic orientation for firms in international markets to attain a sustained firm performance.Design/methodology/approachThe study employed a systematic literature review to synthesize research rigorously. Initially, 2,242 articles were identified from the selective databases, and 45 papers were finally reported as most relevant to propose an integrative conceptual framework.FindingsThe findings of the systematic literature review revealed data-evolving, and data-driven strategic orientations are essential for performing international marketing activities that contain three primary orientations such as (1) international digital platform orientation, (2) international market orientation and (3) international innovation and entrepreneurial orientation. Eleven distinct sub-dimensions reflect these three primary orientations. These strategic orientations of international firms may lead to advanced analytics orientation to attain sustained firm performance by generating and capturing value from the marketplace.Research limitations/implicationsThe study minimizes the literature gap by forming knowledge on big data-based strategic orientation and framing a multidimensional framework for guiding managers in the context of strategic orientation for international business and international marketing activities. The current study was conducted by following only a systematic literature review exclusively in firms' overall big data-based strategic orientation concept in international marketing. Future research may extend the domain by introducing firms' category wise systematic literature review.Originality/valueThe study has proposed a holistic conceptual framework for big data-driven strategic orientation in international marketing literature through a systematic review for the first time. It has also illuminated a future research agenda that raises questions for the scholars to develop or extend theory in this area or other related disciplines.


2019 ◽  
Vol 38 (1) ◽  
pp. 113-137
Author(s):  
Tsvetanka Georgieva-Trifonova ◽  
Kaloyan Zdravkov ◽  
Donika Valcheva

Purpose The purpose of this paper is to summarize the current state of the existing research on the application of semantic technologies in bibliographic databases by providing answers to a set of research questions resulting from a systematic literature review. Design/methodology/approach The present study consists of conducting a systematic literature review of research works related to the application of semantic technologies in bibliographic databases. A manual keyword search is performed in known academic databases. As a result, a total of 78 literature sources are identified as related to the topic and included in the review. From the selected literature sources, information is extracted, which is then summarized and analyzed according to previously defined research questions and finally reported. Besides, a framework is defined to classify literature sources found and collected as a result of the study. The main criteria, according to which the classification is performed, are the used semantic technology and the research problem for which semantic technologies are applied in bibliographic databases. The classification of the publications is verified by each author independently of others. Findings The conducted systematic scientific review establishes that the evolution of semantic technologies sets a period of increased interest in the researchers, as a result of which the advantages of using them for bibliographic descriptions are examined and practically confirmed. After defining semantic models for bibliographic descriptions and approaches to transform existing bibliographic data into their correspondence, the research interest is directed at their comparison, collation; enrichment to facilitate search and retrieval of useful information. Possible perspectives for future research are outlined, which mainly relate to the complete use of the created data sets and their transformation into knowledge repositories. Originality/value Despite the increasing importance of the semantic technologies in various areas, including the bibliographic databases, there is a lack of comprehensive literature review and classification of literature sources relevant to this topic. The detailed study proposed in the present paper supports introducing with the existing experience in the application of semantic technologies in bibliographic databases, as well as facilitates the discovery of trends and guidelines for future research.


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