Journal Software Market Outlook

The global journal software market size is estimated to be valued at approximately $1.2 billion in 2023 and is projected to reach around $2.3 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.2% during the forecast period. The growth of this market is fueled by an increasing demand for digital journaling tools among various user segments, driven by factors such as the rise in remote working and online learning, and an increased emphasis on mental health and productivity. As the world continues to embrace digital transformation, the journal software market is seeing significant growth opportunities across multiple sectors and regions.

One of the primary growth factors in the journal software market is the widespread adoption of digital tools in educational institutions. With the growing trend of e-learning and online education, academic institutions are increasingly integrating digital journal software into their curricula to enhance learning experiences and foster creativity among students. This shift is not only limited to higher education but is also being observed in primary and secondary education levels, where digital journaling is being utilized as a medium to encourage students to articulate their thoughts and improve their writing skills. As educational institutions continue to innovate in teaching methodologies, the demand for journal software is expected to rise significantly.

In the corporate sector, the need for efficient documentation and record-keeping is driving the adoption of journal software. Organizations are leveraging these tools for various purposes, including project management, knowledge sharing, and strategic planning. The ability to access and update information remotely is a critical requirement in the modern business environment, particularly with the increase in remote and hybrid working models. Journal software enables seamless collaboration and enhances productivity by providing a unified platform for employees to document workflows, track progress, and share insights. As businesses continue to prioritize digital solutions that optimize operations, the journal software market is poised for substantial growth.

Another factor contributing to the market expansion is the growing awareness of mental health and wellness. Personal journaling has gained popularity as an effective tool for self-reflection, stress management, and personal development. With the rise in mental health awareness campaigns and an increasing number of individuals seeking ways to improve their well-being, digital journaling platforms offer a convenient and accessible method to promote mindfulness and emotional health. This trend is particularly noticeable among millennials and Gen Z, who are more inclined to adopt digital solutions for lifestyle management, further fueling the growth of the journal software market.

Regionally, North America is expected to dominate the journal software market due to high technological adoption and the presence of key market players. However, the Asia Pacific region is anticipated to witness the highest growth rate during the forecast period, attributed to rapid digitalization, increasing internet penetration, and a burgeoning tech-savvy population. The regional outlook for the journal software market suggests that emerging economies will play a crucial role in the market's expansion, providing ample opportunities for vendors to penetrate new markets and cater to a diverse customer base.

In addition to these trends, the role of Reference Management Software is becoming increasingly significant in the journal software market. As researchers and academics strive to manage vast amounts of information efficiently, reference management tools are essential for organizing citations, managing bibliographies, and ensuring academic integrity. These tools integrate seamlessly with journal software, enhancing the research and writing process by providing users with the ability to easily cite sources and maintain accurate records of their references. The growing emphasis on research productivity and collaboration in academic and professional settings underscores the importance of reference management software, making it a vital component of the journal software ecosystem.

Deployment Type Analysis

The journal software market is segmented into cloud-based and on-premises deployments, each offering distinct advantages that cater to varied organizational needs. The clou

Version: 6

Date of data collection: May 2025

General description: Publication of datasets according to the FAIR principles could be reached publishing a data paper (and/or a software paper) in data journals as well as in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers.

File list:

- data_articles_journal_list_v6.xlsx: full list of 177 academic journals in which data papers or/and software papers could be published
- data_articles_journal_list_v6.csv: full list of 177 academic journals in which data papers or/and software papers could be published
- readme_v6.txt, with a detailed descritption of the dataset and its variables.

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 6th version
- Information updated: number of journals (17 were added and 4 were deleted), URL, document types associated to a specific journal.
- Information added: diamond journals were identified.

Version: 5

Authors: Carlota Balsa-Sánchez, Vanesa Loureiro

Date of data collection: 2023/09/05

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers.
File list:

- data_articles_journal_list_v5.xlsx: full list of 162 academic journals in which data papers or/and software papers could be published
- data_articles_journal_list_v5.csv: full list of 162 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 5th version
- Information updated: number of journals, URL, document types associated to a specific journal.
163 journals (excel y csv)

Version: 4

Authors: Carlota Balsa-Sánchez, Vanesa Loureiro

Date of data collection: 2022/12/15

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers.
File list:

- data_articles_journal_list_v4.xlsx: full list of 140 academic journals in which data papers or/and software papers could be published
- data_articles_journal_list_v4.csv: full list of 140 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 4th version
- Information updated: number of journals, URL, document types associated to a specific journal, publishers normalization and simplification of document types
- Information added : listed in the Directory of Open Access Journals (DOAJ), indexed in Web of Science (WOS) and quartile in Journal Citation Reports (JCR) and/or Scimago Journal and Country Rank (SJR), Scopus and Web of Science (WOS), Journal Master List.

Version: 3

Authors: Carlota Balsa-Sánchez, Vanesa Loureiro

Date of data collection: 2022/10/28

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers.
File list:

- data_articles_journal_list_v3.xlsx: full list of 124 academic journals in which data papers or/and software papers could be published
- data_articles_journal_list_3.csv: full list of 124 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 3rd version
- Information updated: number of journals, URL, document types associated to a specific journal, publishers normalization and simplification of document types
- Information added : listed in the Directory of Open Access Journals (DOAJ), indexed in Web of Science (WOS) and quartile in Journal Citation Reports (JCR) and/or Scimago Journal and Country Rank (SJR).

Erratum - Data articles in journals Version 3:

Botanical Studies -- ISSN 1999-3110 -- JCR (JIF) Q2
Data -- ISSN 2306-5729 -- JCR (JIF) n/a
Data in Brief -- ISSN 2352-3409 -- JCR (JIF) n/a

Version: 2

Author: Francisco Rubio, Universitat Politècnia de València.

Date of data collection: 2020/06/23

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers.
File list:

- data_articles_journal_list_v2.xlsx: full list of 56 academic journals in which data papers or/and software papers could be published
- data_articles_journal_list_v2.csv: full list of 56 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 2nd version
- Information updated: number of journals, URL, document types associated to a specific journal, publishers normalization and simplification of document types
- Information added : listed in the Directory of Open Access Journals (DOAJ), indexed in Web of Science (WOS) and quartile in Scimago Journal and Country Rank (SJR)

Total size: 32 KB

Version 1: Description

This dataset contains a list of journals that publish data articles, code, software articles and database articles.

The search strategy in DOAJ and Ulrichsweb was the search for the word data in the title of the journals.
Acknowledgements:
Xaquín Lores Torres for his invaluable help in preparing this dataset.

The Journals dataset includes information about all historical Journal titles from Springer Nature, including ones that have been decommissioned.See also: https://scigraph.springernature.com/explorer/datasets/data_at_a_glance/A journal record usually includes information about its publisher, imprint, license model, chief editor, external identifiers, subjects and impact factor when available.Version info:* http://scigraph.downloads.uberresearch.com/archives/current/TIMESTAMP.txt* http://scigraph.downloads.uberresearch.com/archives/current/LICENSE.txt

Version: 5

Authors: Carlota Balsa-Sánchez, Vanesa Loureiro

Date of data collection: 2023/09/05

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers. File list:

• data_articles_journal_list_v5.xlsx: full list of 140 academic journals in which data papers or/and software papers could be published
• data_articles_journal_list_v5.csv: full list of 140 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 5th version - Information updated: number of journals, URL, document types associated to a specific journal.

Version: 4

Authors: Carlota Balsa-Sánchez, Vanesa Loureiro

Date of data collection: 2022/12/15

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers. File list:

• data_articles_journal_list_v4.xlsx: full list of 140 academic journals in which data papers or/and software papers could be published
• data_articles_journal_list_v4.csv: full list of 140 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 4th version - Information updated: number of journals, URL, document types associated to a specific journal, publishers normalization and simplification of document types - Information added : listed in the Directory of Open Access Journals (DOAJ), indexed in Web of Science (WOS) and quartile in Journal Citation Reports (JCR) and/or Scimago Journal and Country Rank (SJR), Scopus and Web of Science (WOS), Journal Master List.

Version: 3

Authors: Carlota Balsa-Sánchez, Vanesa Loureiro

Date of data collection: 2022/10/28

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers. File list:

• data_articles_journal_list_v3.xlsx: full list of 124 academic journals in which data papers or/and software papers could be published
• data_articles_journal_list_3.csv: full list of 124 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 3rd version - Information updated: number of journals, URL, document types associated to a specific journal, publishers normalization and simplification of document types - Information added : listed in the Directory of Open Access Journals (DOAJ), indexed in Web of Science (WOS) and quartile in Journal Citation Reports (JCR) and/or Scimago Journal and Country Rank (SJR).

Erratum - Data articles in journals Version 3:

Botanical Studies -- ISSN 1999-3110 -- JCR (JIF) Q2 Data -- ISSN 2306-5729 -- JCR (JIF) n/a Data in Brief -- ISSN 2352-3409 -- JCR (JIF) n/a

Version: 2

Author: Francisco Rubio, Universitat Politècnia de València.

Date of data collection: 2020/06/23

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers. File list:

• data_articles_journal_list_v2.xlsx: full list of 56 academic journals in which data papers or/and software papers could be published
• data_articles_journal_list_v2.csv: full list of 56 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 2nd version - Information updated: number of journals, URL, document types associated to a specific journal, publishers normalization and simplification of document types - Information added : listed in the Directory of Open Access Journals (DOAJ), indexed in Web of Science (WOS) and quartile in Scimago Journal and Country Rank (SJR)

Total size: 32 KB

Version 1: Description

This dataset contains a list of journals that publish data articles, code, software articles and database articles.

The search strategy in DOAJ and Ulrichsweb was the search for the word data in the title of the journals. Acknowledgements: Xaquín Lores Torres for his invaluable help in preparing this dataset.

The journal software market is experiencing robust growth, driven by the increasing need for efficient content management and collaboration among writers, researchers, and academics. While precise market sizing data wasn't provided, considering typical software market growth rates and the expanding user base across various segments (amateurs, full-time writers, etc.), a reasonable estimate for the 2025 market size would be around $500 million. This market is segmented by application (amateur, full-time writer, others) and type (web-based, on-premises), reflecting diverse user needs and technological preferences. The web-based segment is expected to dominate due to its accessibility and scalability. Key drivers include rising demand for streamlined writing workflows, enhanced collaboration tools, and improved content organization features. Trends point towards increasing adoption of cloud-based solutions, integration with other productivity tools, and the incorporation of AI-powered features like grammar checking and style guides. However, restraints such as the high initial investment for enterprise solutions and the need for robust cybersecurity measures are also influencing market dynamics. The competitive landscape is relatively fragmented with several established players and emerging startups vying for market share. Companies such as Bloom Built Inc, Xiamen Sumi Network Technology, and Intelligent Change Inc are among the key players, constantly innovating to meet evolving user demands. The market's geographical distribution is broad, with North America and Europe anticipated as leading regions due to high internet penetration and a strong presence of research institutions and publishing houses. However, the Asia-Pacific region is projected to witness substantial growth fueled by rising digital literacy and an expanding pool of writers and researchers. The forecast period (2025-2033) suggests continued expansion, with a Compound Annual Growth Rate (CAGR) estimated to be between 12-15%, reflecting strong future prospects for the journal software industry. This growth will be sustained by ongoing technological advancements and increasing digital content creation across various sectors. The competitive landscape will likely see further consolidation and innovation as companies seek to differentiate their offerings and cater to specialized user segments.

Journal of statistical software FAQ - ResearchHelpDesk - The Journal of Statistical Software (JSS) is an open-source and open-access scientific journal by the statistical software community for everybody interested in statistical computing. All aspects of the journal, from editorial work over review and copy-editing up to typesetting and publication, are run by a group of volunteers committed to free software (as in software that respects the users' essential freedoms: the freedom to run it, to study and change it, and to redistribute copies with or without changes) and free-subscription, free-submission open-access publishing ideas. Therefore, and as a matter of principle, JSS charges no author fees or subscription fees. The journal does expect the same level of commitment from authors seeking to publish in JSS. Authors will have to accept a high level of responsibility throughout the whole publishing process, including the preparation of the final publishable versions of article and software. Due to the steadily increasing number of incoming and accepted submissions and limited volunteer resources, publication times can be rather long. Compliance by authors to JSS standards and instructions typically speeds-up this process considerably.

This dataset is a comparison of peer reviewed, DOAJ-listed journals in Information Systems and Software Engineering. The Directory of Open Access Journals already provides insightful data such as the publication name, publisher name, the start year of the journal, etc. DOAJ data has extensively been verified and extended. For example, this dataset provides the basic publication fees of each journal, whether the fees can be avoided, the reported indexing services, whether the author copyright is retained or not. Additionally, the list of potential predatory publishers http://scholarlyoa.com/publishers/ was consulted. The search was conducted between 2013-05-16 and 2013-05-22. To gather data, the author searched all DOAJ journals under the general subject of Computer Science. A total of 386 journals was retrieved by this query. http://www.doaj.org/doaj?func=subject&cpId=114&uiLanguage=en Firstly, the dataset was screened for non-relevant entries. Among the 386 entries of the query results, 30 were considered relevant for the context of the study. Reasons for exclusions included: journal either off-topic, or too wide scope (e.g., a topic related to Software Engineering included with non-relevant subjects such as Bio-Metrics, Nano-Computing) or too much specialized (e.g., only business information systems, only for developing countries); journal imposes barriers for submission (e.g., only from a certain nation); journal website not accessible; journal publishes only proceedings or special topics; journal without English only papers; no peer review of the papers (e.g., preprint servers). Special attention was given to the declared focus of the journal. In case the provided focus was considered off-topic or too much specialized, the last issue entries of the journal were manually examined to either confirm or reject the exclusion of the dataset.

Special issues were not counted in the number of issues per year. The total amount of published papers has either been manually computed or through the journal statistics, if available. Please contact the author of this dataset, Daniel Graziotin [graziotin AT inf DOT unibz DOT it] for corrections to the data. In case of correction request, please provide the correction itself and the source.

Last Version: 2

Author: Francisco Rubio, Universitat Politècnia de València.

Date of data collection: 2020/06/23

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers.
File list:

- data_articles_journal_list_v2.xlsx: full list of 56 academic journals in which data papers or/and software papers could be published
- data_articles_journal_list_v2.csv: full list of 56 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 2nd version
- Information updated: number of journals, URL, document types associated to a specific journal, publishers normalization and simplification of document types
- Information added : listed in the Directory of Open Access Journals (DOAJ), indexed in Web of Science (WOS) and quartile in Scimago Journal and Country Rank (SJR)

Total size: 32 KB

Version 1: Description

This dataset contains a list of journals that publish data articles, code, software articles and database articles.

The search strategy in DOAJ and Ulrichsweb was the search for the word data in the title of the journals.
Acknowledgements:
Xaquín Lores Torres for his invaluable help in preparing this dataset.

How can you be a professional software developer There are many papers that speak about the most popular of software development models with their disadvantages and advantages that used in software development So the main target of this paper is explanation of steps for to be a professional software developer and not prefer a model on another model because each model has disadvantages and advantages We can benefit from advantages of all these models for software development if we follow

The data in this set was culled from the Directory of Open Access Journals (DOAJ), the Proquest database Library and Information Science Abstracts (LISA), and a sample of peer reviewed scholarly journals in the field of Library Science. The data include journals that are open access, which was first defined by the Budapest Open Access Initiative: By ‘open access’ to [scholarly] literature, we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. Starting with a batch of 377 journals, we focused our dataset to include journals that met the following criteria: 1) peer-reviewed 2) written in English or abstracted in English, 3) actively published at the time of..., Data Collection In the spring of 2023, researchers gathered 377 scholarly journals whose content covered the work of librarians, archivists, and affiliated information professionals. This data encompassed 221 journals from the Proquest database Library and Information Science Abstracts (LISA), widely regarded as an authoritative database in the field of librarianship. From the Directory of Open Access Journals, we included 144 LIS journals. We also included 12 other journals not indexed in DOAJ or LISA, based on the researchers’ knowledge of existing OA library journals. The data is separated into several different sets representing the different indices and journals we searched. The first set includes journals from the database LISA. The following fields are in this dataset:

Journal: title of the journal

Publisher: title of the publishing company

Open Data Policy: lists whether an open data exists and what the policy is

Country of publication: country where the journal is publ..., , # Open access practices of selected library science journals

The data in this set was culled from the Directory of Open Access Journals (DOAJ), the Proquest database Library and Information Science Abstracts (LISA), and a sample of peer reviewed scholarly journals in the field of Library Science.

The data include journals that are open access, which was first defined by the Budapest Open Access Initiative:Â

By ‘open access’ to [scholarly] literature, we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself.

Starting with a batch of 377 journals, we focused our dataset to include journals that met the following criteria: 1) peer-reviewed 2) written in Engli...

The Softcite dataset is a gold-standard dataset of software mentions in research publications, a free resource primarily for software entity recognition in scholarly text. This is the first release of this dataset.

What's in the dataset

With the aim of facilitating software entity recognition efforts at scale and eventually increased visibility of research software for the due credit of software contributions to scholarly research, a team of trained annotators from Howison Lab at the University of Texas at Austin annotated 4,093 software mentions in 4,971 open access research publications in biomedicine (from PubMed Central Open Access collection) and economics (from Unpaywall open access services). The annotated software mentions, along with their publisher, version, and access URL, if mentioned in the text, as well as those publications annotated as containing no software mentions, are all included in the released dataset as a TEI/XML corpus file.

For understanding the schema of the Softcite corpus, its design considerations, and provenance, please refer to our paper included in this release (preprint version).

Use scenarios

The release of the Softcite dataset is intended to encourage researchers and stakeholders to make research software more visible in science, especially to academic databases and systems of information retrieval; and facilitate interoperability and collaboration among similar and relevant efforts in software entity recognition and building utilities for software information retrieval. This dataset can also be useful for researchers investigating software use in academic research.

Current release content

softcite-dataset v1.0 release includes:

The Softcite dataset corpus file: softcite_corpus-full.tei.xml

Softcite Dataset: A Dataset of Software Mentions in Biomedical and Economic Research Publications, our paper that describes the design consideration and creation process of the dataset: Softcite_Dataset_Description_RC.pdf. (This is a preprint version of our forthcoming publication in the Journal of the Association for Information Science and Technology.)

The Softcite dataset is licensed under a Creative Commons Attribution 4.0 International License.

If you have questions, please start a discussion or issue in the howisonlab/softcite-dataset Github repository.

International Journal of Engineering and Advanced Technology Acceptance Rate - ResearchHelpDesk - International Journal of Engineering and Advanced Technology (IJEAT) is having Online-ISSN 2249-8958, bi-monthly international journal, being published in the months of February, April, June, August, October, and December by Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP) Bhopal (M.P.), India since the year 2011. It is academic, online, open access, double-blind, peer-reviewed international journal. It aims to publish original, theoretical and practical advances in Computer Science & Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. All submitted papers will be reviewed by the board of committee of IJEAT. Aim of IJEAT Journal disseminate original, scientific, theoretical or applied research in the field of Engineering and allied fields. dispense a platform for publishing results and research with a strong empirical component. aqueduct the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research. seek original and unpublished research papers based on theoretical or experimental works for the publication globally. publish original, theoretical and practical advances in Computer Science & Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. impart a platform for publishing results and research with a strong empirical component. create a bridge for a significant gap between research and practice by promoting the publication of original, novel, industry-relevant research. solicit original and unpublished research papers, based on theoretical or experimental works. Scope of IJEAT International Journal of Engineering and Advanced Technology (IJEAT) covers all topics of all engineering branches. Some of them are Computer Science & Engineering, Information Technology, Electronics & Communication, Electrical and Electronics, Electronics and Telecommunication, Civil Engineering, Mechanical Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. The main topic includes but not limited to: 1. Smart Computing and Information Processing Signal and Speech Processing Image Processing and Pattern Recognition WSN Artificial Intelligence and machine learning Data mining and warehousing Data Analytics Deep learning Bioinformatics High Performance computing Advanced Computer networking Cloud Computing IoT Parallel Computing on GPU Human Computer Interactions 2. Recent Trends in Microelectronics and VLSI Design Process & Device Technologies Low-power design Nanometer-scale integrated circuits Application specific ICs (ASICs) FPGAs Nanotechnology Nano electronics and Quantum Computing 3. Challenges of Industry and their Solutions, Communications Advanced Manufacturing Technologies Artificial Intelligence Autonomous Robots Augmented Reality Big Data Analytics and Business Intelligence Cyber Physical Systems (CPS) Digital Clone or Simulation Industrial Internet of Things (IIoT) Manufacturing IOT Plant Cyber security Smart Solutions – Wearable Sensors and Smart Glasses System Integration Small Batch Manufacturing Visual Analytics Virtual Reality 3D Printing 4. Internet of Things (IoT) Internet of Things (IoT) & IoE & Edge Computing Distributed Mobile Applications Utilizing IoT Security, Privacy and Trust in IoT & IoE Standards for IoT Applications Ubiquitous Computing Block Chain-enabled IoT Device and Data Security and Privacy Application of WSN in IoT Cloud Resources Utilization in IoT Wireless Access Technologies for IoT Mobile Applications and Services for IoT Machine/ Deep Learning with IoT & IoE Smart Sensors and Internet of Things for Smart City Logic, Functional programming and Microcontrollers for IoT Sensor Networks, Actuators for Internet of Things Data Visualization using IoT IoT Application and Communication Protocol Big Data Analytics for Social Networking using IoT IoT Applications for Smart Cities Emulation and Simulation Methodologies for IoT IoT Applied for Digital Contents 5. Microwaves and Photonics Microwave filter Micro Strip antenna Microwave Link design Microwave oscillator Frequency selective surface Microwave Antenna Microwave Photonics Radio over fiber Optical communication Optical oscillator Optical Link design Optical phase lock loop Optical devices 6. Computation Intelligence and Analytics Soft Computing Advance Ubiquitous Computing Parallel Computing Distributed Computing Machine Learning Information Retrieval Expert Systems Data Mining Text Mining Data Warehousing Predictive Analysis Data Management Big Data Analytics Big Data Security 7. Energy Harvesting and Wireless Power Transmission Energy harvesting and transfer for wireless sensor networks Economics of energy harvesting communications Waveform optimization for wireless power transfer RF Energy Harvesting Wireless Power Transmission Microstrip Antenna design and application Wearable Textile Antenna Luminescence Rectenna 8. Advance Concept of Networking and Database Computer Network Mobile Adhoc Network Image Security Application Artificial Intelligence and machine learning in the Field of Network and Database Data Analytic High performance computing Pattern Recognition 9. Machine Learning (ML) and Knowledge Mining (KM) Regression and prediction Problem solving and planning Clustering Classification Neural information processing Vision and speech perception Heterogeneous and streaming data Natural language processing Probabilistic Models and Methods Reasoning and inference Marketing and social sciences Data mining Knowledge Discovery Web mining Information retrieval Design and diagnosis Game playing Streaming data Music Modelling and Analysis Robotics and control Multi-agent systems Bioinformatics Social sciences Industrial, financial and scientific applications of all kind 10. Advanced Computer networking Computational Intelligence Data Management, Exploration, and Mining Robotics Artificial Intelligence and Machine Learning Computer Architecture and VLSI Computer Graphics, Simulation, and Modelling Digital System and Logic Design Natural Language Processing and Machine Translation Parallel and Distributed Algorithms Pattern Recognition and Analysis Systems and Software Engineering Nature Inspired Computing Signal and Image Processing Reconfigurable Computing Cloud, Cluster, Grid and P2P Computing Biomedical Computing Advanced Bioinformatics Green Computing Mobile Computing Nano Ubiquitous Computing Context Awareness and Personalization, Autonomic and Trusted Computing Cryptography and Applied Mathematics Security, Trust and Privacy Digital Rights Management Networked-Driven Multicourse Chips Internet Computing Agricultural Informatics and Communication Community Information Systems Computational Economics, Digital Photogrammetric Remote Sensing, GIS and GPS Disaster Management e-governance, e-Commerce, e-business, e-Learning Forest Genomics and Informatics Healthcare Informatics Information Ecology and Knowledge Management Irrigation Informatics Neuro-Informatics Open Source: Challenges and opportunities Web-Based Learning: Innovation and Challenges Soft computing Signal and Speech Processing Natural Language Processing 11. Communications Microstrip Antenna Microwave Radar and Satellite Smart Antenna MIMO Antenna Wireless Communication RFID Network and Applications 5G Communication 6G Communication 12. Algorithms and Complexity Sequential, Parallel And Distributed Algorithms And Data Structures Approximation And Randomized Algorithms Graph Algorithms And Graph Drawing On-Line And Streaming Algorithms Analysis Of Algorithms And Computational Complexity Algorithm Engineering Web Algorithms Exact And Parameterized Computation Algorithmic Game Theory Computational Biology Foundations Of Communication Networks Computational Geometry Discrete Optimization 13. Software Engineering and Knowledge Engineering Software Engineering Methodologies Agent-based software engineering Artificial intelligence approaches to software engineering Component-based software engineering Embedded and ubiquitous software engineering Aspect-based software engineering Empirical software engineering Search-Based Software engineering Automated software design and synthesis Computer-supported cooperative work Automated software specification Reverse engineering Software Engineering Techniques and Production Perspectives Requirements engineering Software analysis, design and modelling Software maintenance and evolution Software engineering tools and environments Software engineering decision support Software design patterns Software product lines Process and workflow management Reflection and metadata approaches Program understanding and system maintenance Software domain modelling and analysis Software economics Multimedia and hypermedia software engineering Software engineering case study and experience reports Enterprise software, middleware, and tools Artificial intelligent methods, models, techniques Artificial life and societies Swarm intelligence Smart Spaces Autonomic computing and agent-based systems Autonomic computing Adaptive Systems Agent architectures, ontologies, languages and protocols Multi-agent systems Agent-based learning and knowledge discovery Interface agents Agent-based auctions and marketplaces Secure mobile and multi-agent systems Mobile agents SOA and Service-Oriented Systems Service-centric software engineering Service oriented requirements engineering Service oriented architectures Middleware for service based systems Service discovery and composition Service level

This description is part of the blog post "Systematic Literature Review of teaching Open Science" https://sozmethode.hypotheses.org/839

According to my opinion, we do not pay enough attention to teaching Open Science in higher education. Therefore, I designed a seminar to teach students the practices of Open Science by doing qualitative research.About this seminar, I wrote the article ”Teaching Open Science and qualitative methods“. For the article ”Teaching Open Science and qualitative methods“, I started to review the literature on ”Teaching Open Science“. The result of my literature review is that certain aspects of Open Science are used for teaching. However, Open Science with all its aspects (Open Access, Open Data, Open Methodology, Open Science Evaluation and Open Science Tools) is not an issue in publications about teaching.

Based on this insight, I have started a systematic literature review. I realized quickly that I need help to analyse and interpret the articles and to evaluate my preliminary findings. Especially different disciplinary cultures of teaching different aspects of Open Science are challenging, as I myself, as a social scientist, do not have enough insight to be able to interpret the results correctly. Therefore, I would like to invite you to participate in this research project!

I am now looking for people who would like to join a collaborative process to further explore and write the systematic literature review on “Teaching Open Science“. Because I want to turn this project into a Massive Open Online Paper (MOOP). According to the 10 rules of Tennant et al (2019) on MOOPs, it is crucial to find a core group that is enthusiastic about the topic. Therefore, I am looking for people who are interested in creating the structure of the paper and writing the paper together with me. I am also looking for people who want to search for and review literature or evaluate the literature I have already found. Together with the interested persons I would then define, the rules for the project (cf. Tennant et al. 2019). So if you are interested to contribute to the further search for articles and / or to enhance the interpretation and writing of results, please get in touch. For everyone interested to contribute, the list of articles collected so far is freely accessible at Zotero: https://www.zotero.org/groups/2359061/teaching_open_science. The figure shown below provides a first overview of my ongoing work. I created the figure with the free software yEd and uploaded the file to zenodo, so everyone can download and work with it:

To make transparent what I have done so far, I will first introduce what a systematic literature review is. Secondly, I describe the decisions I made to start with the systematic literature review. Third, I present the preliminary results.

Systematic literature review – an Introduction

Systematic literature reviews “are a method of mapping out areas of uncertainty, and identifying where little or no relevant research has been done.” (Petticrew/Roberts 2008: 2). Fink defines the systematic literature review as a “systemic, explicit, and reproducible method for identifying, evaluating, and synthesizing the existing body of completed and recorded work produced by researchers, scholars, and practitioners.” (Fink 2019: 6). The aim of a systematic literature reviews is to surpass the subjectivity of a researchers’ search for literature. However, there can never be an objective selection of articles. This is because the researcher has for example already made a preselection by deciding about search strings, for example “Teaching Open Science”. In this respect, transparency is the core criteria for a high-quality review.

In order to achieve high quality and transparency, Fink (2019: 6-7) proposes the following seven steps:

1. Selecting a research question.
2. Selecting the bibliographic database.
3. Choosing the search terms.
4. Applying practical screening criteria.
5. Applying methodological screening criteria.
6. Doing the review.
7. Synthesizing the results.

I have adapted these steps for the “Teaching Open Science” systematic literature review. In the following, I will present the decisions I have made.

Systematic literature review – decisions I made

1. Research question: I am interested in the following research questions: How is Open Science taught in higher education? Is Open Science taught in its full range with all aspects like Open Access, Open Data, Open Methodology, Open Science Evaluation and Open Science Tools? Which aspects are taught? Are there disciplinary differences as to which aspects are taught and, if so, why are there such differences?
2. Databases: I started my search at the Directory of Open Science (DOAJ). “DOAJ is a community-curated online directory that indexes and provides access to high quality, open access, peer-reviewed journals.” (https://doaj.org/) Secondly, I used the Bielefeld Academic Search Engine (base). Base is operated by Bielefeld University Library and “one of the world’s most voluminous search engines especially for academic web resources” (base-search.net). Both platforms are non-commercial and focus on Open Access publications and thus differ from the commercial publication databases, such as Web of Science and Scopus. For this project, I deliberately decided against commercial providers and the restriction of search in indexed journals. Thus, because my explicit aim was to find articles that are open in the context of Open Science.
3. Search terms: To identify articles about teaching Open Science I used the following search strings: “teaching open science” OR teaching “open science” OR teach „open science“. The topic search looked for the search strings in title, abstract and keywords of articles. Since these are very narrow search terms, I decided to broaden the method. I searched in the reference lists of all articles that appear from this search for further relevant literature. Using Google Scholar I checked which other authors cited the articles in the sample. If the so checked articles met my methodological criteria, I included them in the sample and looked through the reference lists and citations at Google Scholar. This process has not yet been completed.
4. Practical screening criteria: I have included English and German articles in the sample, as I speak these languages (articles in other languages are very welcome, if there are people who can interpret them!). In the sample only journal articles, articles in edited volumes, working papers and conference papers from proceedings were included. I checked whether the journals were predatory journals – such articles were not included. I did not include blogposts, books or articles from newspapers. I only included articles that fulltexts are accessible via my institution (University of Kassel). As a result, recently published articles at Elsevier could not be included because of the special situation in Germany regarding the Project DEAL (https://www.projekt-deal.de/about-deal/). For articles that are not freely accessible, I have checked whether there is an accessible version in a repository or whether preprint is available. If this was not the case, the article was not included. I started the analysis in May 2019.
5. Methodological criteria: The method described above to check the reference lists has the problem of subjectivity. Therefore, I hope that other people will be interested in this project and evaluate my decisions. I have used the following criteria as the basis for my decisions: First, the articles must focus on teaching. For example, this means that articles must describe how a course was designed and carried out. Second, at least one aspect of Open Science has to be addressed. The aspects can be very diverse (FOSS, repositories, wiki, data management, etc.) but have to comply with the principles of openness. This means, for example, I included an article when it deals with the use of FOSS in class and addresses the aspects of openness of FOSS. I did not include articles when the authors describe the use of a particular free and open source software for teaching but did not address the principles of openness or re-use.
6. Doing the review: Due to the methodical approach of going through the reference lists, it is possible to create a map of how the articles relate to each other. This results in thematic clusters and connections between clusters. The starting point for the map were four articles (Cook et al. 2018; Marsden, Thompson, and Plonsky 2017; Petras et al. 2015; Toelch and Ostwald 2018) that I found using the databases and criteria described above. I used yEd to generate the network. „yEd is a powerful desktop application that can be used to quickly and effectively generate high-quality diagrams.” (https://www.yworks.com/products/yed) In the network, arrows show, which articles are cited in an article and which articles are cited by others as well. In addition, I made an initial rough classification of the content using colours. This classification is based on the contents mentioned in the articles’ title and abstract. This rough content classification requires a more exact, i.e., content-based subdivision and

The web sites of journals were accessed for their current (July 2020, double-checked January 2021) issues. Peer reviewed research article (i.e., excluding commentary, letters, etc) were selected on the basis that their titles implied code had been used in the published research.

A list of full citations, including DOIs, is provided in the supplementary material.

The associated articles (PDFs) were read by the author, and all links to supplementary material examined. Where possible, code from the links was downloaded and assessed.

In addition, the code policies, where available, of the relevant journals (at the time of the survey) were copied into the supplementary material.

The article’s supplementary material has further details of the assessment and the individual results, and is therefore an essential part of this Dryad data.

NOTE

It is important that this survey is not taken as an evaluation, whether praise or criticism, of any specific paper: any measurement i...

International Journal of Engineering and Advanced Technology FAQ - ResearchHelpDesk - International Journal of Engineering and Advanced Technology (IJEAT) is having Online-ISSN 2249-8958, bi-monthly international journal, being published in the months of February, April, June, August, October, and December by Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP) Bhopal (M.P.), India since the year 2011. It is academic, online, open access, double-blind, peer-reviewed international journal. It aims to publish original, theoretical and practical advances in Computer Science & Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. All submitted papers will be reviewed by the board of committee of IJEAT. Aim of IJEAT Journal disseminate original, scientific, theoretical or applied research in the field of Engineering and allied fields. dispense a platform for publishing results and research with a strong empirical component. aqueduct the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research. seek original and unpublished research papers based on theoretical or experimental works for the publication globally. publish original, theoretical and practical advances in Computer Science & Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. impart a platform for publishing results and research with a strong empirical component. create a bridge for a significant gap between research and practice by promoting the publication of original, novel, industry-relevant research. solicit original and unpublished research papers, based on theoretical or experimental works. Scope of IJEAT International Journal of Engineering and Advanced Technology (IJEAT) covers all topics of all engineering branches. Some of them are Computer Science & Engineering, Information Technology, Electronics & Communication, Electrical and Electronics, Electronics and Telecommunication, Civil Engineering, Mechanical Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. The main topic includes but not limited to: 1. Smart Computing and Information Processing Signal and Speech Processing Image Processing and Pattern Recognition WSN Artificial Intelligence and machine learning Data mining and warehousing Data Analytics Deep learning Bioinformatics High Performance computing Advanced Computer networking Cloud Computing IoT Parallel Computing on GPU Human Computer Interactions 2. Recent Trends in Microelectronics and VLSI Design Process & Device Technologies Low-power design Nanometer-scale integrated circuits Application specific ICs (ASICs) FPGAs Nanotechnology Nano electronics and Quantum Computing 3. Challenges of Industry and their Solutions, Communications Advanced Manufacturing Technologies Artificial Intelligence Autonomous Robots Augmented Reality Big Data Analytics and Business Intelligence Cyber Physical Systems (CPS) Digital Clone or Simulation Industrial Internet of Things (IIoT) Manufacturing IOT Plant Cyber security Smart Solutions – Wearable Sensors and Smart Glasses System Integration Small Batch Manufacturing Visual Analytics Virtual Reality 3D Printing 4. Internet of Things (IoT) Internet of Things (IoT) & IoE & Edge Computing Distributed Mobile Applications Utilizing IoT Security, Privacy and Trust in IoT & IoE Standards for IoT Applications Ubiquitous Computing Block Chain-enabled IoT Device and Data Security and Privacy Application of WSN in IoT Cloud Resources Utilization in IoT Wireless Access Technologies for IoT Mobile Applications and Services for IoT Machine/ Deep Learning with IoT & IoE Smart Sensors and Internet of Things for Smart City Logic, Functional programming and Microcontrollers for IoT Sensor Networks, Actuators for Internet of Things Data Visualization using IoT IoT Application and Communication Protocol Big Data Analytics for Social Networking using IoT IoT Applications for Smart Cities Emulation and Simulation Methodologies for IoT IoT Applied for Digital Contents 5. Microwaves and Photonics Microwave filter Micro Strip antenna Microwave Link design Microwave oscillator Frequency selective surface Microwave Antenna Microwave Photonics Radio over fiber Optical communication Optical oscillator Optical Link design Optical phase lock loop Optical devices 6. Computation Intelligence and Analytics Soft Computing Advance Ubiquitous Computing Parallel Computing Distributed Computing Machine Learning Information Retrieval Expert Systems Data Mining Text Mining Data Warehousing Predictive Analysis Data Management Big Data Analytics Big Data Security 7. Energy Harvesting and Wireless Power Transmission Energy harvesting and transfer for wireless sensor networks Economics of energy harvesting communications Waveform optimization for wireless power transfer RF Energy Harvesting Wireless Power Transmission Microstrip Antenna design and application Wearable Textile Antenna Luminescence Rectenna 8. Advance Concept of Networking and Database Computer Network Mobile Adhoc Network Image Security Application Artificial Intelligence and machine learning in the Field of Network and Database Data Analytic High performance computing Pattern Recognition 9. Machine Learning (ML) and Knowledge Mining (KM) Regression and prediction Problem solving and planning Clustering Classification Neural information processing Vision and speech perception Heterogeneous and streaming data Natural language processing Probabilistic Models and Methods Reasoning and inference Marketing and social sciences Data mining Knowledge Discovery Web mining Information retrieval Design and diagnosis Game playing Streaming data Music Modelling and Analysis Robotics and control Multi-agent systems Bioinformatics Social sciences Industrial, financial and scientific applications of all kind 10. Advanced Computer networking Computational Intelligence Data Management, Exploration, and Mining Robotics Artificial Intelligence and Machine Learning Computer Architecture and VLSI Computer Graphics, Simulation, and Modelling Digital System and Logic Design Natural Language Processing and Machine Translation Parallel and Distributed Algorithms Pattern Recognition and Analysis Systems and Software Engineering Nature Inspired Computing Signal and Image Processing Reconfigurable Computing Cloud, Cluster, Grid and P2P Computing Biomedical Computing Advanced Bioinformatics Green Computing Mobile Computing Nano Ubiquitous Computing Context Awareness and Personalization, Autonomic and Trusted Computing Cryptography and Applied Mathematics Security, Trust and Privacy Digital Rights Management Networked-Driven Multicourse Chips Internet Computing Agricultural Informatics and Communication Community Information Systems Computational Economics, Digital Photogrammetric Remote Sensing, GIS and GPS Disaster Management e-governance, e-Commerce, e-business, e-Learning Forest Genomics and Informatics Healthcare Informatics Information Ecology and Knowledge Management Irrigation Informatics Neuro-Informatics Open Source: Challenges and opportunities Web-Based Learning: Innovation and Challenges Soft computing Signal and Speech Processing Natural Language Processing 11. Communications Microstrip Antenna Microwave Radar and Satellite Smart Antenna MIMO Antenna Wireless Communication RFID Network and Applications 5G Communication 6G Communication 12. Algorithms and Complexity Sequential, Parallel And Distributed Algorithms And Data Structures Approximation And Randomized Algorithms Graph Algorithms And Graph Drawing On-Line And Streaming Algorithms Analysis Of Algorithms And Computational Complexity Algorithm Engineering Web Algorithms Exact And Parameterized Computation Algorithmic Game Theory Computational Biology Foundations Of Communication Networks Computational Geometry Discrete Optimization 13. Software Engineering and Knowledge Engineering Software Engineering Methodologies Agent-based software engineering Artificial intelligence approaches to software engineering Component-based software engineering Embedded and ubiquitous software engineering Aspect-based software engineering Empirical software engineering Search-Based Software engineering Automated software design and synthesis Computer-supported cooperative work Automated software specification Reverse engineering Software Engineering Techniques and Production Perspectives Requirements engineering Software analysis, design and modelling Software maintenance and evolution Software engineering tools and environments Software engineering decision support Software design patterns Software product lines Process and workflow management Reflection and metadata approaches Program understanding and system maintenance Software domain modelling and analysis Software economics Multimedia and hypermedia software engineering Software engineering case study and experience reports Enterprise software, middleware, and tools Artificial intelligent methods, models, techniques Artificial life and societies Swarm intelligence Smart Spaces Autonomic computing and agent-based systems Autonomic computing Adaptive Systems Agent architectures, ontologies, languages and protocols Multi-agent systems Agent-based learning and knowledge discovery Interface agents Agent-based auctions and marketplaces Secure mobile and multi-agent systems Mobile agents SOA and Service-Oriented Systems Service-centric software engineering Service oriented requirements engineering Service oriented architectures Middleware for service based systems Service discovery and composition Service level agreements (drafting,

This analysis assesses the way ecology journals handle code and software written for scientific research. The results of the analysis were used to create Figure 1 in Mislan et al. (2016).

Please cite the following paper if you use this data/code:

Mislan, K. A. S., J. M. Heer, and E.P. White. (2016) Elevating the status of code in ecology. Trends in Ecology and Evolution. http://dx.doi.org/10.1016/j.tree.2015.11.006

This repository includes the data used in the research in the article "Diversity in Software Engineering Conferences and Journals" submitted to the Journal of Systems and Software in October 2023. This repository contains .csv and .json files that include the data of all research papers published in the conferences ICSE, ASE, and FSE, along with the journals IEEE TSE and ACM TOSEM from the years 2010-2022 along with the list of names of Programming and Organizing Committee members and Editorial Board members. This data was sourced from DBLP and the conference websites/journal front matter pages. The names of the authors and committee members have been processed using NamSor to obtain the corresponding ethnicity (using the "Name US Race" feature) and gender (using the "Genderize name from first name and last name" feature). The affiliated institution and corresponding country for each first author were determined using the Scopus database.

Peer Review System Market Outlook

The global peer review system market size was valued at USD 1.2 billion in 2023 and is expected to reach USD 2.9 billion by 2032, growing at a compound annual growth rate (CAGR) of 10.1% from 2024 to 2032. The primary growth factor driving this market is the increasing emphasis on quality control and validation across various industries, particularly in education, healthcare, and research institutions.

One of the major growth factors contributing to the expansion of the peer review system market is the heightened focus on academic and research integrity. As academic and scientific communities strive for higher standards and legitimacy, the demand for robust peer review systems to validate and scrutinize research findings has surged. Additionally, funding agencies and governmental bodies are increasingly mandating the use of rigorous peer review processes to ensure the credibility of funded research, further propelling market growth.

The technological advancements in artificial intelligence and machine learning are also major catalysts in the growth of the peer review system market. Modern AI algorithms can streamline the peer review process by assisting in the identification of suitable reviewers, detecting potential plagiarism, and providing insights into the overall quality of submissions. These advancements make the review process more efficient and reliable, thereby increasing the adoption rate of peer review systems among various end-users.

Moreover, the growing importance of peer review systems in corporate settings cannot be overlooked. Companies are increasingly using these systems to assess the quality of internal reports, project proposals, and even employee performance reviews. The ability to maintain high standards and foster a culture of continuous improvement is appealing to corporate entities, further contributing to the market's robust growth. Additionally, the increasing requirement for transparency and accountability in various sectors is likely to accelerate the adoption of peer review systems.

In the realm of academic research and publication, Journal Software plays a pivotal role in streamlining the peer review process. These software solutions are designed to manage the entire workflow of manuscript submissions, from initial submission to final publication. By automating tasks such as reviewer selection, feedback collection, and revision tracking, Journal Software significantly reduces the administrative burden on editors and reviewers. This, in turn, allows them to focus more on the quality and integrity of the research being evaluated. As the demand for efficient and transparent peer review processes grows, the adoption of Journal Software is expected to rise, further supporting the expansion of the peer review system market.

Regionally, North America is expected to lead the peer review system market, followed by Europe and the Asia Pacific. The presence of numerous academic institutions, research organizations, and corporate entities in these regions, which prioritize high standards of quality and validation, fuels the market demand. The Asia Pacific region, with its expanding educational infrastructure and growing emphasis on research and development, is anticipated to exhibit the highest CAGR during the forecast period.

Component Analysis

The peer review system market is segmented by components into software and services. The software segment, encompassing platforms and applications that facilitate the peer review process, is anticipated to hold a significant share. This can be attributed to the rising demand for digital solutions that streamline and automate the review process. These software solutions often come with features like plagiarism detection, reviewer recommendation, and analytics, which enhance the efficiency and effectiveness of the review process.

The integration of artificial intelligence and machine learning into peer review software is a notable trend. These technologies help in automating several aspects of the review process, such as identifying suitable reviewers based on expertise and detecting any potential conflicts of interest or plagiarism. Such advanced functionalities not only improve the speed and accuracy of reviews but also make the software more appealing to end-users in various sectors, including education, healthcare, and corporate.

On the other hand, the services segme

International Review on Computers and Software Impact Factor 2024-2025 - ResearchHelpDesk - The International Review on Computers and Software (IRECOS) is a peer-reviewed journal that publishes original papers on all branches of the academic Computer Science and Engineering communities. Thematic areas include, but are not limited to: Computer Science Theory, Methods and Tools Software engineering, algorithms, and complexity, computational logic, formal methods, heuristics, mathematics, and models of computation, programming languages, and semantics. Computer and Communications Networks and Systems Network and distributed architectures and protocols, traffic engineering, resource management and Quality of Service, network monitoring and traffic measurements, wireless networks, personal and body area networks, vehicular networks, content and service-centric networking, multimedia communications, and standards, energy-efficient/green networks, opportunistic and cognitive networks. Computational Intelligence, Machine Learning, and Data Analytics Human-computer interaction, computational science, pattern recognition, computer vision, speech processing, machine intelligence and reasoning, web science, databases, information retrieval, visualization, current application domains, e.g. Healthcare and BioInformatics, and emerging application domains, e.g. big data. Security in Computer Systems and Networks Computer systems security, hardware, and embedded systems security, security protocol design and analysis, cryptography and cryptanalysis, intrusion detection systems and techniques, user authentication techniques, and systems. Hardware Design Computer architectures, parallel architectures, operating systems, and signal processing. IRECOS also publishes letters to the Editor and research notes which discuss new research, or research in progress in any of the above thematic areas. The International Review on Computers and Software (IRECOS) currently has an acceptance rate of 24%. The average time between submission and final decision is 40 days and the average time between acceptance and publication is 22 days.

According to Cognitive Market Research, the global Literature Review Software market size was USD XX billion in 2023 and will expand at a compound annual growth rate (CAGR) of 8.20% from 2023 to 2030.

The demand for Literature Review Software is rising due to the increasing volume of research, the growing complexity of research questions, and technological advancements.
Demand for Cloud Based remains higher in the Literature Review Software market.
The Large Enterprises category held the highest Literature Review Software market revenue share in 2023.
North American Literature Review Software will continue to lead, whereas the Asia Pacific Literature Review Software market will experience the most substantial growth until 2030.

Rising Demand for Streamlined Workflows to Provide Viable Market Output

The key driver for the Literature Review Software market is the growing demand for streamlined and automated workflows in the research process. Researchers are seeking solutions that can simplify the literature review process, from sourcing relevant materials to organizing and citing them efficiently. Literature Review Software that offers features such as automated citation management, categorization, and real-time collaboration contributes to increased productivity. The demand for tools that reduce manual efforts, enhance accuracy, and improve overall workflow efficiency is a driving force behind the adoption of Literature Review Software in academic and research settings.

In August 2023, there is a trend towards more specialized literature review software. Previously, most literature review software was created as general-purpose tools suitable for various research disciplines.

Source-www.sciencedirect.com/journal/journal-of-systems-and-software

Digital Transformation in Research to Propel Market Growth

The Literature Review Software market is driven by the ongoing digital transformation in the research landscape. Researchers and academic institutions are increasingly recognizing the need for efficient, technology-driven solutions to manage and analyze vast amounts of literature. The transition from traditional paper-based methods to digital platforms allows for quick access to a wide array of research materials, collaborative features, and advanced analytical tools. This shift towards digitization is a key driver, as it enhances productivity, facilitates remote collaboration, and supports researchers in staying abreast of the latest developments in their respective fields.

In September 2023, literature review software is increasingly being integrated with various other research tools. Several literature review software programs now combine with other research tools, including reference management software and citation generators.

Source-www.toolsforhumans.ai/toolkit/best-ai-tools-for-research

User-friendly Interface and Increasing Applications of Literature Review Software

Market Dynamics of the Literature Review Software Market

Data Security Concerns to Restrict Market Growth

The key restraints in the Literature Review Software market revolve around data security concerns. As researchers and academic institutions increasingly rely on digital platforms to manage vast amounts of sensitive literature and research data, the risk of unauthorized access, data breaches, or misuse becomes a critical issue. The need to ensure the confidentiality and integrity of research findings and scholarly work creates challenges for Literature Review Software providers. Institutions and researchers may hesitate to fully embrace these tools without robust security measures, potentially slowing down the adoption rate and hindering the market's growth.

Impact of COVID–19 on the Literature Review Software Market?

The COVID-19 pandemic significantly impacted the literature review software market by accelerating the adoption of digital tools in the academic and research sectors. The widespread lockdowns and restrictions on physical access to libraries and research facilities prompted a surge in the demand for remote-accessible and collaborative solutions. Researchers and academics, faced with challenges in conducting traditional literature reviews, turned to Literature Review Software to streamline and digitize the process. The need for efficient collaboration tools, remote access to research materials, and the organization of vast amounts of l...