Category: Publishing Automation

How to Enhance Content Workflows with the Power of NLP?

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Natural Language Processing (NLP) empowers publishers to reduce manual touchpoints and expedite content flow through the publishing pipeline. This accelerates time to market and therefore knowledge dissemination. NLP technologies, such as automated summarization, disambiguation, part-of-speech tagging, context extraction, and linguistic understanding and recognition, have led to the development of large language models (LLMs) that facilitate AI-based language analysis and generation.

 

Image Source: https://www.statista.com/statistics/1388542/authors-using-ai/

 

Scholarly authors and publishers are leveraging AI tools for diverse purposes, including the improvement of efficiency, accuracy, and quality of research and content. This article provides a stepwise guide to integrate NLP into existing publishing workflows.

 

The Pre-Integration Checklist

Before integrating any technology, the existing process should be audited to identify current performance and quality bottlenecks and determine areas of improvement. Next, list out the potential touchpoints where NLP enhancement can expedite or refine the process. You can also seek help from experienced technology providers, like Integra, to gauge the capabilities of NLP and determine how you can make the most of the technology to improve workflows.

 

Using the touchpoints for NLP integration, define and set clear goals. Establish qualitative and quantitative KPIs for the NLP augmentation. Using these goals, define the software and integration requirements, along with necessary training and skill-building requirements, to effectively leverage the innovative tools.

 

Steps to Integrating NLP

Integration is rarely a straight-forward process. Enhancing the existing technology stack for API-based tools requires putting together and executing an implementation plan.

 

Step 1. Data Collection and Preparation

Language models train using existing data, learning its patterns and anomalies. To prepare for NLP integration, start by identifying and collating data from all available sources. Next, clean, structure, and migrate the data to the cloud, where ML models can be trained.

 

Step 2. Choose the Right NLP Tools

You can choose off-the-shelf NLP solutions or get them customized to your specific requirements. While off-the-shelf options might be cost-effective and offer immediate usability, tools with dedicated purposes will need to be integrated to obtain the overall process improvements. On the other hand, customized tools may take a little more time and investment, but will address specific business requirements and pain points, transforming workflows sustainably for the long term.

 

Step 3. Implementation in Workflows

With the help of technical teams, perform API integrations, with the content management system (CMS), process monitoring system, work allocation subsystems, etc., to reap comprehensive benefits of NLP enhancement.

 

Leverage NLP automation for first-level language quality assessment, sentiment analysis, content tagging, keyword extraction, summarization, and much more. This can help in classifying manuscript submissions based on quality, accuracy, and the required level of manual editing to expedite movement.

 

Step 4. Training and Optimization

Integrate the NLP model training within processes to align its capabilities with your content and facilitate continuous refinement for improved accuracy.

 

Step 5. Monitoring and Maintenance

Consistently check the relevance and accuracy of model and technology updates to ensure long-term value extraction. Also, monitor the workflows to track the performance, speed, and quality of NLP tools using metrics such as processing time saved, man-hours saved, language accuracy improved, etc., to assess the performance of these tools.

 

Using the KPIs established, performance data of NLP tools, and business outcomes measure the impact of NLP integration. Use quantifiable benefits such as time saved, content reach improved, and engagement enhanced to measure ROI.

 

AI Revolutionizing Publishing

While NLP directly works to expedite and enhance manuscript processing, AI integration across business functions aids in managing timelines, mapping reviewers to content according to subject matter, and even marketing. To stay relevant and ahead of the competition, publishers must stay updated with innovations in NLP and other cutting-edge technologies. Partnering with a technology provider with profound AI and NLP integration experience, such as Integra, eliminates the need, time, and costs required to build and maintain in-house technology teams. Schedule a call with the experts to make an informed NLP integration decision.

Powering Language Quality Assessment in Digital Publishing with AI

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The average manuscript acceptance rate stands at a mere 32%, according to research on 2,300 publishers. The study also revealed that large journals could accept even less than 10% of their submissions. There are multiple reasons for rejection and with the volume of manuscripts journals receive, desk rejections (DR) are quite high. Poor language is the second most common cause of outright DR, following closely behind irrelevant topics.

 

With AI-based first inspections, language quality assessment does not consider the author’s background or linguistic expertise. This further emphasizes the need for authors to deliver manuscripts with a focus on high-quality language; mere salvageability is no longer enough.

Challenges in Maintaining Linguistic Integrity in Digital Publishing

With constantly rising number of research and submissions, journal publishers have largely automated initial screening to streamline the movement of manuscripts from the digital to the manual review stage. Further, limitations in human oversight make relying on technologies such as AI and NLP for the first review essential. Due to a limited reviewer base, publishers enforce stringent language quality checks to eliminate unfit manuscripts at the earliest stage to expedite the process.

 

But, both quality and quantity of research impact a journal’s reputation. Clarity of text and knowledge conveyance are crucial for research publication. However, language inefficiencies should not become an obstacle to high-quality research being published. This calls for strategically filtering high-research-quality but low-language-proficiency manuscripts by facilitating linguistic improvement rather than outright rejection. This is where AI-based linguistic analytics and assistive editing come into play.

How AI Tools Identify and Rectify Subtle Inconsistencies

Language clarity, consistency, and correctness are all essential for high-quality research publication. Maintaining the flow and correctness of the manuscript are non-negotiable. Here’s how AI is ensuring all this and more.

 

Automated Proofreading and Grammar Checks

NLP-powered tools enable the analysis of manuscripts based on syntax and semantics. These tools assess and suggest corrections to enhance language quality. Advanced tools even categorize manuscripts to expedite the progress of those with excellent language and schedule ones with poor language for manual editing.

 

Detecting Inconsistencies in Style, Tone, and Language

Large language models are trained to assess the style, tone, and nuances of the language. They reveal underlying inconsistencies in the message being conveyed and conclusion inferences. By suggesting appropriate corrections, these tools facilitate the alignment of content with the journal’s preferred language style and tone.

 

Enhancing Scalability and Speed of Language Checks

AI-powered tools expedite the first-proof duration and progress of the manuscript through the editing funnel while eliminating linguistic inaccuracies. These tools reduce assessment time from months to just a few minutes, eliminating human error and bias from the process.

AI-Powered Language Analysis Empowering Publishers

Technology lends speed, flexibility, and impartiality to language assessment. Modern customizable AI tools not only facilitate language assessment and correction but also schematic, flow, and layout improvements. These tools also identify analysis inconsistencies and research gaps to notify authors.

 

To minimize publishing times while ensuring high language quality, editing automation with AI proves invaluable. At Integra, we pride ourselves on reducing copyediting costs by 40% and delivering 90% accuracy in error identification with our highly customizable and flexible language assessment solution. Contact us now to learn how Integra’s ContentPilot can transform language assessment for your journal.

AI-Powered Feedback Loops Elevate Journal Publishing Quality

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Feedback is critical for publishers to understand their audience and improve their published works. Plus, the opportunity to provide feedback enhances reader engagement and allows the publisher to build trust and establish credibility in a primarily digital world. This blog discusses leveraging modern technologies, such as AI, to leverage the value of feedback for your publishing house.

Efficient Collection and Categorization of Reader Feedback Using AI

Since online publishing expands the surface area of visibility and access to published content, accumulating feedback across reader streams and extracting insights requires extensive effort.

 

Although web scouring techniques can facilitate the assimilation of such data, categorizing, assessing, and eliciting valuable insights still remains a massive task to accomplish, especially when done manually. This is where AI can help, collating and categorizing data from diverse sources. Plus, NLP-powered feedback assessment offers further support, categorizing the feedback into positive, negative, feed-forward, and other categories to facilitate analysis.

 

Once the feedback is categorized, large language models (LLMs) can distinguish genuine feedback and filter comments accordingly. ML and deep learning algorithms can “understand” the comments and generate feedback analysis reports to provide actionable insights for authors, editors, reviewers, and the publisher.

Tools for Real-Time Content Adjustments Based on Ongoing Feedback

Amid hyper-personalization across industries, readers expect similar offerings from research publications. AI-powered content management systems can transform how content is served to readers in multiple ways. It allows publishers to:

  • Offer content in the reader’s regional language dynamically, taking cultural preferences into consideration by assessing user location data and reading preferences.
  • Analyze previous feedback and reading patterns to suggest more readings and improve the discoverability of existing content.
  • Assess content in real-time using AI models and update it according to any new industry updates or flag inaccuracies and outdated content.

Strategies for Predictive Feedback Analysis

The biggest strength of powering publishing workflows with AI is the use of predictive and generative analytics. Machine learning models can assess the content and evaluate its performance and potential to elicit feedback. Generative AI can use historical data to artificially generate reader feedback and suggest content improvements to minimize negative comments.

How AI Transforms Feedback into Actionable Editorial Strategies

Feedback reports with AI-suggested corrective measures can be quantified for better understanding and converted to visual reports to gain a clear picture of content performance, quality perception among the audience, and demand. Moreover, editorial decisions can be driven by AI insights, such as the direction of research, topics in demand, reader-preferred learning modes, and even incorporating assistive technologies for certain segments of readers. It can also identify areas of improvement, such as onboarding more SMEs, choosing appropriate content and research quality metrics, or suitable research or data collection methodologies.

 

Creating a feedback loop and making the most of the insights it offers allows publishers to improve the efficacy of research publications. However, a feedback loop cannot work in isolation. Equipping the publishing process with AI-powered tools to incorporate findings from feedback assessment at every stage of manuscript progress can transform publishing. Talk to the experts at Integra to learn more about upgrading your publishing process with AI-powered feedback loops to enrich each stage of publishing.

AI as the Silent Writing Partner: Aiding Language Refinement in Scholarly Publishing

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Delve into the crucial role of effective academic communication and the obstacles authors encounter in achieving high language quality. Uncover the capabilities of AI-powered language and editing tools, offering a contextual approach that goes beyond grammar checks to enhance coherence and clarity. Explore the collaborative synergy between human expertise and AI, resulting in polished academic manuscripts. Emphasize the advantages of embracing AI technology to elevate language standards in academic publishing, benefiting authors and journals alike. Delve into the significance of language clarity on the credibility of scholarly work and address the complexities involved in evaluating language quality, including the limitations of traditional grammar-checking tools. Introduce readers to innovative AI-powered tools that offer contextual language recommendations, focus on authors’ intent while generating content, and automate workflows, reducing manual intervention. Ultimately, emphasize how AI elevates language quality, fosters effective academic communication, and enhances research dissemination.

The Human-AI Synergy in Enhancing Language Quality for Journal Publishers

Every research is an attempt to answer a critical question. Your hard work might help answer the question wonderfully or even throw up new questions for future research. However, unless you can communicate your hypothesis, methodology, findings, and conclusions effectively, there is little hope of your efforts being recognized or the scientific community benefiting from your work.

Scholarly publishers, on the other hand, need to sustain the trust of their readers and win over new ones by upholding the highest quality standards. They not only check every manuscript for the quality of research, but also the language. For this, every approved manuscript is put through a rigorous editing process to refine the writing and meet the journal’s quality criteria.

Challenges to Meeting Academic Language Quality Standards

“The language barrier between thoughts and written words constitutes a hindrance for non-native speakers,” says a research paper published in Linguistics and Literature Studies in March 2021. But this isn’t just true for non-native speakers. After all, a brilliant researcher need not also be a prolific writer.

 

Academic language is very different from the usual written language. To be considered academic, the writing should be formal, factual, analytical, objective, clear, and explicit. In fact, poor language is among the top reasons for manuscripts being rejected by scholarly journals. Academic writing requires distinct styles of sentence construction and expression and even a different lexicon.

 

Communicating your thoughts and research findings in an organized, accurate and sensitive manner can be a challenge, even if grammar isn’t one. For non-native speakers, drawing inferences with clarity and overcoming the difference in structural construction between the mother tongue and English can also pose a problem.

 

The reality is that scholarly research is meant for a niche audience, which puts specific demands on the language, based on the field of research. Logical, ethnographic, socio-linguistic, and pedagogical challenges might need to be dealt with by both authors and editors.

 

Overcoming Language Challenges with Technology The rapid evolution of AI/ML and NLP has brought highly sophisticated technology tools to ensure quality control right from the writing stage of the journal publishing cycle. Today, AI-powered platforms are even helping journal publishers identify the best-fit reviewers for the peer review stage while automating multiple tasks to ensure higher speed and accuracy.

 

With an AI-powered authoring and publishing platform, researchers can save significant time and effort in preparing manuscripts according to a journal’s specific standards and submission criteria. With the power of NLP, authors can ensure concise, accurate, and well-structured text, freeing up their mind space to focus on the more important aspects of the manuscript, such as data analysis.

 

Some of the specific areas where AI can complement human effort for best results are:

Formatting of Manuscripts

Both authors and publishers can benefit from automated, standardized formatting, compliant with each journal’s specific style guidelines. This includes ensuring that citations follow the suggested style, including how author names, journal titles, publication dates, etc., are formatted. AI/NLP can also ease editing and translation, where required. The end result is better chances of the manuscript being approved.

Identifying and Resolving Issues Early

AI can scour large amounts of text to automatically identify irregularities, missing information, language editing needs, and much more. Early red flags ensure early resolution, saving authors and publishers time and effort in the submission process.

Language Review

IGrammar and spelling tools are old hat now. Today, machine learning and natural language processing (NLP) algorithms flag inaccuracies, helping authors easily meet stringent language standards. While semantic and syntactical analysis leads to linguistic accuracy, ontological and taxonomical analysis helps with statistical reporting consistency.

With such tools, regulatory compliance can be ascertained from the manuscript creation stage, while publishers get to enhance and accelerate the editing and peer review processes at scale. In addition, early identification of research inaccuracies and content manipulation prevents reputational damage for authors and publishers.

The Right Technology Partner Enriches Scholarly Publishing

With a powerful cloud-based technology platform, powered by AI, ML, and NLP, authors, editors, and publishers can collaborate seamlessly to bring the highest quality academic papers to the public. Such platforms not only automate and streamline workflows, but also accelerate each stage of publishing to bring the latest research to the market in the least possible time. In fact, AI-powered language tools have proven to reduce turnaround time to mere minutes from the traditional 60-90 days. This could translate into remarkable language accuracy, assuring over 80% correctness in the first go and 40% cost savings for publishers.

Onshore vs. Offshore Editing: Choosing the Best Option for Your Publishing Needs

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Editing polishes a manuscript at three levels – developmental edit, line edit, and copy edit, ensuring that basic errors and inconsistencies are prevented. Editing also ensures the manuscript avoids the most common reasons for rejection, such as poor language use, flawed arguments or conclusions, and methodical flaws. This makes editing a defining step in any manuscript’s publishing journey.

 

However, choosing the right editing practice is critical to success. The foremost concern is whether to pick onshore or offshore editing services. Here’s an overview to help you decide.

 

Onshore Editing

Traditionally, publishers have preferred onshore content editing due to concerns regarding language quality and expertise.

  • Onshore editing services tend to offer native English speakers with better linguistic skills.
  • It is easier to embed such services into the existing publishing environment since time and space do not hinder collaboration.
  • Onshore content editing facilitates quality control with both the publisher and the editing services provider being aware of regional regulatory requirements.

Offshore Editing

Advanced technologies have given offshore content editing services powerful tools to ensure quality. This has introduced better collaborative opportunities, consistent oversight, editing quality analysis, and friction-free communication channels.

  • Offshore content editing allows publishers to access subject matter experts from across the world.
  • Offshore editors are better equipped to align the content with the cultural nuances of different regions, when required.
  • Offshore editing services tend to be more cost-effective due to intense competition.
  • Offshore editing services often have the capacity to handle large volumes of content, making them suitable for projects with extensive editing requirements.

Choosing The Right Editing Fit

AI-powered cloud-based solutions reduce the gaps between onshore and offshore editorial models. This allows publishers to choose their preferred editing model based on the most relevant criteria.

 

A key way to determine whether a written piece should be edited onshore or offshore is the level and extent of editing required and publisher preference on type of content.

 

NLP-powered automated language assessment tools help evaluate the extent of editing needed. They assess the language to categorize the manuscript into one of several sets:

  • No copyediting needed
  • Guided or automated editing required, or
  • Extensive editing required.

The system also identifies whether an onshore or offshore editor should be chosen. The platform assesses the language quality and scope of the journal to decide whether a specific article should be assigned for onshore or offshore editing. A popular choice is to use AI-enabled offshore editing tools for simpler editing and leveraging onshore editors for extensive requirements.

 

Other criteria that help make a choice are:

Modern Technologies Support Evolving Publishing Needs

Cloud-based platforms can be easily integrated into any environment, accelerating the transition to newer technology and limiting data loss. The progress of a manuscript through its publishing journey and collaboration among the different parties across the different stages of publishing becomes streamlined and seamless. AI and NLP have helped reduce turnaround time by automating a considerable amount of work, such as scheduling and rescheduling, and first-level assessment of language quality. This facilitates the use of a hybrid editing model, where both onshore and offshore services can be effortlessly used, without added costs or infrastructural needs.

 

Integra’s complete journal publishing lifecycle platform is equipped with cloud-based sub-modules that automate and ease diverse editing activities, while also facilitating manual editing. The language and copyediting tools reduce turnaround time from the usual 60-90 days to just a few minutes, which translates to 40% cost savings in copyediting for publishers. The remarkable accuracy of the editing module, which assures over 80% correctness in the first go, improves the editor’s experience with the publisher too. The best part is that it can be used for both onshore and offshore editing services with comprehensive access rights management facilities. The platform is equipped with tools, such as iEnrich, which can be used for in-house editing, and iLancer, which facilitates the management of freelancers. Integra also has a team of highly qualified and experienced editors, adept at using these tools to expedite editing.

 

Contact us to learn how the cloud-based automation of editorial services can accelerate publishing while enhancing quality and reducing costs.

Transforming Journal Publishing with an AI-Driven Content Assessment Platform

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Advances in technology have made academic publishing more efficient, accessible, and impactful for readers, researchers, and publishers. Advanced digital platforms accelerate the navigation of the entire publishing process, from research to writing, submissions, peer review, design, and distribution. AI is empowering the scholarly publishing industry in multiple ways:

 

  • Automating repetitive tasks to free up time that can be better utilized.
  • Aligning content and authors with journal and publisher guidelines to facilitate scholarly collaboration.
  • Assisting in the assessment of the novelty and accuracy of research to ensure high-quality outcomes.
  • Journal content assessment platforms equipped with AI and ML enrich all aspects of scholarly publishing. Here’s a look.

Language and Grammar Assistance

AI language assessment tools perform seamless language and grammar analysis. They flag inaccuracies and assist non-native English writers attain competitive language standards. Taxonomy and ontology analysis improves consistency in statistical reporting, while syntactical and semantic analysis ensures linguistic accuracy. This also ensures adherence to journal/publication guidelines. Plus, AI tools ease regulatory compliance right from the manuscript creation stage.

Enhanced Review Process

The foremost responsibility during peer review is identifying academicians most suited for the specific scholarly content. AI-based journal content assessment platforms are integrated into the publishing workflow. They match the expertise and availability of users with the subjects and deadlines of the paper. Therefore, AI helps find the best-fit peer groups for review purposes and also notifies all members of their assignments to ensure timely submissions. Facilities to create and share knowledge graphs enhance both peer and editorial reviews and accelerate proofreading at a scale. AI can analyze reviewer feedback to identify potential biases, such as gender or institutional biases, and address them to ensure fair and objective evaluations.

 

AI-powered tools can automatically screen submitted manuscripts for adherence to journal guidelines and basic formatting requirements. By filtering out improperly formatted or irrelevant papers, the peer review process becomes more efficient for both authors and reviewers. With AI automating various aspects of the review process, the time taken for peer review is significantly reduced.

 

Data Mining and Analysis

Machine learning-based pattern analysis and anomaly assessments ensure data integrity. This improves the quality, accuracy, and reliability of the data. NLP and machine learning models identify missing citations and stylistic issues ahead of the manual review process, preventing non-necessary manuscript movement. Early identification of content manipulation, research inaccuracies, research gaps, and unlicensed use of copyrighted materials minimizes retractions and prevents reputational damage. Furthermore, researchers can analyze large amounts of data (often referred to as Big Data) quickly, which helps them make better inferences and discover insights than with manual analysis.

 

Enhanced Metadata Management

AI is empowering decision-makers to unleash the full potential of massive data in complex business ecosystems. It offers deep insights using metadata-driven warehousing. AI automates metadata extraction and the development of data schemes, accelerating the creation and enhancing the maintenance of metadata. AI-powered algorithms can automatically extract relevant metadata from research articles, including author names, affiliations, abstracts, keywords, and publication dates. This saves time for publishers and authors, ensuring accurate and standardized metadata. Additionally, advanced tagging and anonymization help enforce privacy and security restrictions.

 

Content Discovery and Recommendation

Appropriate meta-tagging and enhanced metadata management, along with content optimization with the help of analytics, boost paper discovery and reachability. Metadata automation also helps in automating paper summary creation and refining copies to share with diverse audiences. Additionally, using AI-based analytics to identify market trends and predictive analyses to discover upcoming user needs is a great way to plan future content. Researchers can explore related articles within a specific domain, enabling interdisciplinary collaborations and a deeper understanding of subjects. AI-powered tools use bibliometric approaches to enhance the dynamic searchability and archival of manuscripts.

 

AI-powered scholarly content assessment platforms benefit researchers and publishers alike by facilitating fast and accurate access and analysis of data and manuscripts. Contact Integra to learn more about leveraging AI to transform the academic publishing process.

How AI-Powered Workflow Automation Benefits Your Publishing Operations?

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In the digital age, meeting customer expectations for convenient access to their preferred journals and eBooks has become crucial. The traditional journal publishing process must adapt to evolving customer demands which necessitates optimizing workflows, and intelligent workflow automation incorporating advanced technologies like AI is the key solution. Real-world statistics highlight the transformative impact of workflow automation on productivity within the publishing sector. According to a Zapier study, 63% of knowledge workers credit automation with helping them combat work burnout, while 65% believe it effectively reduces stress levels. This implies that AI driven workflow automation within journal publishing is aimed to enhance productivity and scale the output for publishers.

 

Prominent Challenges in the Publishing Industry

From submission of the manuscript to final distribution of the journal, the multiple runs of editing, corrections, revisions, and styling, have their own set of challenges.

  • Submission and Review– The authoring and editing phase might require numerous runs. Often, these are delayed due to out-of-sync timelines to manage both peer reviews and edits. Additionally, authors are often researchers first and writers second, which means huge gaps in their proficiency with language and writing tools.
  • Layout Design– Another prominent challenge for publishers comes after the final round of editing. The content design must be optimized for production across screens of all sizes and underlying platforms. All this has to be achieved while ensuring that digital publishing standards are met. Then, there is another round of author and editor proofing.
  • Content Standardization and Management– Finally, the gigantic task of distribution begins. Despite distribution being just a few swipes away with the digital format, it takes significant publisher effort to have it discovered and referred by scholars. XML-tagging, meta-tagging, managing the digital asset repository and ensuring appropriate credits are critical. This requires high-speed, cloud-based archive and license management.

Making Lives Easier for Publishers with AI-powered Workflow Automation Platform

To address the above at scale, publishers must employ cutting edge and efficient technologies to overcome workflow bottlenecks and deliver faster, better, and cheaper journals. In short, they need technology-driven intelligent workflow management platforms.

 

Leveraging artificial intelligence for efficient workflows has the potential to disrupt the publishing industry in many ways.

  • Accelerating turnarounds from content ideation to publishing: Automated grammar checks to assessing language quality and making recommendations for change speed up language quality checks and editing; NLP-based editing tools also facilitate guided editing to improve speed and quality.
  • Improved citation management with cross-linking and referencing from repositories: AI/ML-powered technical diagnosis helps identify missing information and references much faster and more accurately than human checks. It also aids adequate source-tagging.
  • Automated XML-tagging: Completely configurable cloud-based style managers can automate XML-tagging to style the documents according to each journal’s style guide. They also ensure compliance with industry standards. Machine-readable stylesheets reduce manual labor and accelerate layout design.

The most pressing challenge is choosing the right technology partner to facilitate efficiency in publishing workflows using AI services, such that the complexities of the publishing process are simplified via technology. Leveraging an intelligent automated publishing platform that comes with analytics capabilities can help publishers make informed decisions on content style and publishing format. It can also help them discover the most in-demand topics. In short, automation enables publishers to focus on strategic and creative aspects of journal publishing rather than tying up resources. Intelligent workflow automation ensures meeting timelines by streamlining and managing every step of the publishing process.

 

The full-cycle authoring and publishing platform from Integra ensures efficient workflow automation, powered by artificial intelligence. Its intuitive interface and rich functionalities can ease your content production journey. Contact us to streamline your workflows with the latest new technology in book and journal publishing.

Leverage Artificial Intelligence to Maximize Manuscript Acceptance

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After you have spent months researching and then writing it all down, you and your article will only receive the deserved recognition if it is accepted for publication. In 2020, there were 46,736 academic journals worldwide with 5.14 million academic articles being published annually as of 2022. Unfortunately, research by Elsevier on more than 2,300 journals reveals that the average manuscript acceptance rate stands at a mere 32%, with the acceptance range varying from just over 1% to 93.2%. As a researcher and/or author, you’d want to be at the upper end of that range.

 

While every journal might have its own guidelines for accepting manuscripts, quality is paramount for all journal publishers. Therefore, acceptance criteria tend to be extremely stringent. The advancement of scientific knowledge relies on publishing innovative, disruptive, and well-researched content. Now, researchers need not necessarily be prolific writers. Meeting the publishing standards and guidelines can be daunting for them. This is where a manuscript language assessment solution might come in handy.

 

What else could help you ensure manuscript acceptance? Here’s a stepwise guide to improving the acceptance rate.

 

1. Choose the Right Journal

Do the necessary due diligence of journals related to your area of research to find one that aligns perfectly with your school of thought. In addition, picking high-impact journals can help you improve the number of times your research is accessed, helping you gain recognition.

 

2. Conduct Rigorous Data Analysis

Data analysis lends credibility to research and presenting the analysis adequately ensures that readers can easily assimilate the information. Therefore, utilizing effective and, if required, multiple analysis techniques can be beneficial. When using multiple techniques, clearly presenting the conclusions and their interactions is paramount.

 

3. Highlight the Significance and Novelty of the Research

This is essential to ensure that the publisher recognizes the value your research may add to the domain. Including the significance and novelty of the research within the introduction, abstract, and conclusion is a good practice. Also, acknowledging the potential for further research is a good idea to add extensibility to the paper. Remember to use a manuscript editing software to perfect the writing before submitting the final draft.

 

4. Accommodate Peer and Mentor Suggestions

Peers review is a critical step in manuscript acceptance by journals. Peers may give you valuable feedback and insights into improving your paper to not just meet the publishing criteria but also enhance its value for readers. You can always ask questions to gain more clarity on the peer review before you make changes.

 

5. Be Prompt in Including Reviewer Feedback

Reviewers know what can get your paper rejected, so including their feedback is indispensable. However, it is important to do so in a thoughtful and professional manner. Maintain gap-free communication and politely reason for your stand on things you disagree with.

 

6. Adhere to the Submission Guidelines and Timelines

The easiest way to get rejected is to ignore timelines or guidelines. A manuscript editing tool on a powerful authoring platform can help ensure that guidelines are met while speeding up the process to help you meet timelines.

 

7. Ensure a Clear and Concise Writing Style

Your writing should clearly express the findings you want to share. It should follow the writing style approved by the publishing house and incorporate all the references correctly. Maintaining transparency and presenting unbiased findings is essential.

 

Improve Manuscript Acceptance with Powerful Editing Software

Although the research and data analysis are solely the author’s responsibility, ensuring manuscript acceptance can be simplified with an AI-powered digital authoring solution that includes a tool for manuscript language assessment. Integra’s iMLA is an advanced solution that aids language assessment and helps ensure a friction free forward journey for the manuscript. It empowers researchers and authors with quick technical diagnosis, which expedites the writing process.

 

In addition, advanced manuscript editing software takes care of stylistic guidelines, so that authors can focus on the content. By streamlining the entire process from writing right up to publication, a powerful digital solution can significantly enhance the acceptance rate.

Simplify, Streamline, Succeed: Why You Should Choose an Online HTML Editor?

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HTML is the preferred language for online publishing because it is incredibly easy to learn, simple to use, and can be extended effortlessly with XML and CSS. The digital publishing industry has embraced HTML with open arms to accelerate operations. It helps simplify content creation, streamline workflows, and seamlessly deliver high-quality content. Read on to learn why every ePublisher should have a powerful HTML editor in their arsenal.

 

Benefits of HTML-Based ePublishing Solutions

An HTML-based content editing tool offers multiple business benefits, such as:

1. Time and Effort Savings

HTML is free, as are its complementary languages, CSS and XML. This cuts down technology costs for ePublishing companies. Since HTML files are lightweight, they require less server storage space and loading time. HTML editing tools also reduce manual labor for data integration. All this improves productivity and cuts down time to market.

 

2. Responsive Design and Interoperability

HTML is compatible with all screen sizes, platforms, and search engines. It is easy for search engines to access, crawl, and index HTML content. Additionally, semantic coding ensures indexing accuracy. Markup tags reduce loading time, improving user experience. Using HTML-based editing tools allows publishers to optimize content for diverse browsers. HTML editors facilitate ease of augmenting designing and customization for different types of content since HTML is compatible with almost every digital content development tool. Most importantly, HTML is the official language for ePub – the online publishing standard. Therefore, using HTML editors inherently ensures compatibility with global standards.

 

3. Version Control and Revision History

Storing and managing workflows is easier too. This eliminates the need for a third party-based content management system. This also eliminates the need for backward compatibility if the HTML-powered editing tool gets an upgrade. This also means that the editing tool remains reliable over the long term, without the need for regular investments.

 

4. User-Friendly Interface

This optimizes costs and time for the entire process of production, updating, development, customization, and distribution. Once loaded, content can be viewed offline as well. This makes it easy to quickly deploy the platform and streamline workflows. Some of the most beneficial seamless features that improve user experience include native multimedia storage with a cloud-based publishing solution, font embedding, and zoom-in and out controls.

 

5. Accessibility and Collaboration

All browsers support the language, giving the content greater visibility and ease of accessibility. The ease of supplementing HTML with XML and other web publishing add-ons facilitates the creation of interactive and multimedia content. It also simplifies content sharing and cross-linking with data repositories. Additionally, HTML inherently facilitates the separation of content from structure, ensuring that workflows across content creation, designing, styling, and publishing are streamlined.

 

Integra’s iEnrich is an HTML based editor that allows collaboration and simplifies the workflow, iPubEdit is an ML/NLP-powered, cloud-based technical editing solution. It facilitates the integration of journal-specific validations and is independent of traditional editors like MS Word. This allows independent content design and management. Advanced auto structuring with an accuracy of 92% frees writers from the complexities of publishing-ready design. Contact us to learn how adopting a complete digital editing and publishing solution can transform your ePublishing experience.

Streamlining Publishing Workflow with the Latest Technology Solutions

Posted on by aashish-dev

Technology has had a transformational impact on the publishing industry since the invention of the first publishing press in 1455 by Johannes Gutenberg. Five centuries later, cutting-edge tech is revolutionizing the industry once again, helping accelerate editorial and production processes by streamlining workflows and eliminating redundancies. Consequently, the $91.39 billion publishing industry releases around 4 million titles annually, including over 1.7 million self-published titles.

 

Both technology and the publishing industry have evolved significantly since Gutenberg’s invention. Over the years, the applications of the latest technology in the publishing industry have made the process easier. This has powered the growth of the industry in multiple ways. Here’s a look.

 

Removal of Redundancies

Publishing has long been plagued by multiple iterations of content development, editing, and review. Moreover, when multiple authors, editors, freelancers, and vendor partners work on a project, there is a high probability of content redundancy, flow discontinuation, and lack of cohesiveness. Incorporating new technologies in the publishing industry reduces the review cycle duration while ensuring quality.

 

AI-powered automated editing tools prove valuable in eliminating content redundancies. Equipped with NLP capabilities, these tools help reduce the manual effort needed for spotting errors and maintaining cohesive content flow. Another advantage of this new technology in publishing is that it provides suggestions to improve the content, based on pre-determined parameters. Further, content scanning helps identify repeat instances, alerting the author and editor of content duplicity.

 

Workflow Integration

Integrating workflows facilitates better task coordination and seamless team coordination. This helps in the swift movement and audit of data. Advanced publishing workflow management platforms eliminate manual tracking and communication chains by automating task scheduling and serialized assignment.

 

Additionally, these systems notify users of upcoming deadlines to help meet timelines and improve the author’s experience. Use of advanced technologies in publishing thus optimizes workflows. Workflow management software addresses the dynamic requirements of a broad and sensitive demography.

 

Content Consolidation

The greatest benefit of embracing the latest publishing workflow management system is freeing up mind space and time to focus on content quality and creativity. Digital Content Management Systems (DCMS) define customer and content journeys to enhance the process of content assimilation from diverse channels. These tools solve the prominent problem of tracking content progress and author royalties.

 

DCMSs are often supplemented with Digital Asset Management Systems (DAMS) to expedite the production of content internally and digital rights acquisition for external assets. Well-designed DCM and DAM systems enable speedy compilation of disparate content pieces into a cohesive whole. This enhances business efficiency and prevents bottlenecks in one stage from spilling over to another.

 

Enhanced Decision Making

Another persistent challenge in journal and book publishing is keeping track of changing consumer demand. Employing data analytics helps address this challenge. It allows publishers to discover reader behaviors and make insight-driven decisions. Leveraging advanced technologies, such as big data and predictive analysis, helps publishers know their audience and cater to their ever-changing needs. Data-backed insights also help in developing a quantifiable approach to adopting new business models.

 

Technology Helps Establish Market Dominance in the Publishing Industry

The key advantage of effectively employing new technologies in the publishing industry is that it allows a brand to differentiate itself in a highly competitive landscape. Accelerated production, superior-quality content creation, and streamlined management improve user experience and help achieve business goals strategically.

The most effective way to harness all these benefits is via cloud-based systems. Having technology experts create, manage, and customize the toolkit for your specific business requirements can help you maintain a future-ready tech stack. The full-cycle suite from Integra can be tailored to meet all your publishing needs, enhancing your content production journey. The modular architecture allows publishers to hand-pick features according to their requirements and only pay for what they use. Contact us to enhance your business processes with pioneering new technology in book and journal publishing.