Categories
en Uncategorized

Deep Dive: The benefits of expert peer review in research

What is peer review?

Peer review is the assessment of research papers by field experts, it is a collaborative process between research paper authors and field experts. The purpose of this process is to evaluate the quality of the research, suitability of publication, and acts as a rigorous quality control measure while also serving the author with valuable feedback. 

Understanding peer review

The peer review process is vital to upholding the standard and quality of scholarly research, it also serves as an important support for authors. Peer reviews can alert authors to overlooked gaps in research and general errors as well. A survey conducted by sense about science found that 91% of respondents say their papers were significantly improved through peer review. 

The different types of peer review

Single-anonymousDouble-anonymousOpen
In this approach, reviewers are aware of the author’s identity; however, the author does not know the identity of the reviewer. This method is usually applied in science and medical journalsThe double-anonymous process is when neither the author or reviewer is aware of each other’s identities, this is when utmost objectivity is achieved. This method is usually applied in fields of humanities and social sciences. The open method does not have a singular definition, however, it is when the author and reviewer are aware of each other’s identities. Furthermore, once the paper is published, the reviewers names and reports are also present alongside the article.

The benefits of peer review

  • Ensures quality and accuracy

Peer review encourages authors to adhere to high standards in academic research, it stands to ensure only the best quality of research is disseminated. The process is designed to assess the validity, quality, and originality of submitted articles, hence filtering out those that are invalid. Furthermore, the reviewers are selected by journal editors that adhere to high standards and a comprehensive criteria to find the correct reviewer. 

  • Promotes objectivity and fairness

The double-anonymous method is the most reliable method to reduce bias as both parties are not aware of each other’s identity, the process is designed to tackle inequality in scholarly publishing as it reduces bias with respect to gender, race, country, origin or affiliation. 

  • Encourages scholarly collaboration

Peer reviews provide authors the platform to exchange ideas, methodologies, and findings while receiving insight from field experts, which enriches the academic landscape. It serves as a good networking opportunity and knowledge exchange. A taylor and francis study found that most researchers across all subject areas rated the contribution of peer review towards improving their articles as 8 or above, out of 10. 

  • Identifies and mitigates ethical issues

Peer review catches ethical considerations like plagiarism, data fabrication, and conflicts of interest. To ensure an ethical process takes place, all conflicts of interest should be disclosed and confidentiality should be maintained. Ethics ensure the responsible conduct of research by providing clear guidelines, while also monitoring researchers and practices to ensure everything meets ethical standards. 

Find peer reviewed articles on Zendy

In this blog, we covered the various aspects of peer review by explaining the purpose of the process and the factors it is designed to consider; we also dove into the different types of peer review and closed off with the benefits. To continue your research, you can log in to zendy.io and access millions of credible peer reviewed papers across all disciplines. 

Categories
Uncategorized

Our mission, Our AI

As a mission driven digital research library, Zendy is committed
to helping reduce inequality in access to academic literature for
audiences worldwide.

By working closely in partnership with publishers and data providers to create an affordable and accessible route to quality, peer reviewed content, we aim to even the playing field of global research, enabling students and researchers from underserved markets to participate in the global academic and policy dialogue and to contribute to
identifying solutions to our planet’s major challenges.

We believe that AI has an important role to play in fostering a fairer research and publishing ecosystem. By leveraging AI, we can offer a range of innovative solutions to facilitate access to content and to make the search journey quicker and more efficient, thereby supporting researchers’ needs irrespective of funding or location.

Whilst AI has the potential to transform research and education, Zendy acknowledges that it also raises ethical concerns around issues such as bias, privacy, and accountability. In response to these concerns and to the growing discussion around AI, we have formulated a list of AI imperatives to guide Zendy’s strategy for the development and integration of AI technologies into our products.


Zendy’s AI Imperatives:

  1. AI in service of a better world

In line with our mission to reduce inequality in research and publishing, we believe AI can help to positively impact society by facilitating access to and use of academic content. Our portfolio of AI solutions and our ongoing development work reflects this ethos, with a focus on solutions designed to support our users in their search for quality, reliable data. As a signatory to the UN’s Global Publishing Compact, and working hand in hand with our partners, we aim to offer a more enriched, personalised learning and discovery environment for all users globally, with AI very much in service of a better world.

  1. Openness, trust and transparency

We explain our use of AI tools, defining them in terms of their abilities and limitations. We clarify how they fit in to our platform’s ecosystem and how users can make the most of them. If the tool makes use of partner copyrighted data, as per licensed agreements, we put in place limitations and clear safeguards on that use. We recognise the need for openness, trust and transparency across all our activities, and we are open to feedback from all of our stakeholders.

  1. Personal privacy and data governance

Zendy is a committed advocate of personal privacy. As we continue to develop new solutions and acquire larger data sets, we safeguard the personal information which is shared with us through security policies and procedures to secure our systems. We also ensure that data is collected, reproduced, and protected in a compliant and appropriate manner in accordance with applicable privacy laws and regulations.

  1. Equity and unfair bias

Fairness and equity are at the heart of our mission to help create a better world. As we develop and implement new AI tools and solutions, we put in place procedures to ensure reliability, and carry out extensive review. We recognise that biases and hallucinations present challenges in machine learning models, similar to their presence in human cognition. Completely eliminating these issues may compromise the reasoning abilities of our models. Therefore, to minimise these challenges, we have implemented state-of-the-art techniques derived from recent research. These include prevention
and mitigation mechanisms like “chain-of-verification” and “counterfactual reasoning”, which are integrated into our models.

  1. Human oversight and accountability

We believe human oversight is key to the successful development and deployment of a useful and reliable AI-powered solution. We maintain human oversight of the development of our AI tools and their output from design to deployment to ensure reliability and quality. We routinely conduct evaluation benchmarks on our models to
assess their tendency to reproduce falsehoods and biases, as well as to measure their accuracy. This ongoing evaluation process enables us to continually enhance and refine our models.

Categories
en Uncategorized

Qualitative VS. Quantitative Research: How To Use Appropriately and Depict Research Results

What is qualitative and quantitative research? 

Before a researcher begins their research, they would need to establish whether their research results will be quantitative or qualitative. 

Qualitative research observes any subjective matter that can’t be measured with numbers or units, usually answering the questions “how” or “why”. This type of data is usually derived from exploratory sources like, journal entries, semi-structured interviews, videos, and photographs.

On the other hand, quantitative research is numeric and objective, which usually answers the questions “when” or “where”. This data is derived from controlled environments like surveys, structured interviews, and traditional experimental designs. Quantitative data is meant to find objective information.

What are the main differences between qualitative and quantitative research?

The main factor of differentiation between qualitative and quantitative data are the sources that the data is gathered from, as this effects the format of the results. 

Sources of Qualitative DataSources of Quantitative Data
Participants’ recollection of eventsPolls, surveys and experiments
Focus groupsDatabases of records and information
Observing ethnographic studiesAnalysis of other research to identify patterns
Semi-structured interviewsQuestionnaires with close-ended questions
Questionnaires with open-ended questionsStructured Interviews

When to use qualitative and quantitative research? 

When conducting a study, knowing how the results will be depicted drive the methodology and overall approach to the study. To understand whether qualitative or quantitative research results are best suited for your current project, we take a deeper dive at the several advantages and disadvantages of each. 

  1. Qualitative research

Advantages: 

  • Allows researchers to understand “human experience” that cannot be quantified
  • Has fewer limitations, out-of-the-box answers, opinions and beliefs are included in data gathering and analysis
  • Researchers can utilise personal instinct and subjective experience to identify and extract information
  • Easier to derive and conduct as researchers can adapt to any changes to optimise results 

Disadvantages:

  • Responses can be biased, as participants may opt for answers that are desirable. 
  • Qualitative studies usually have small sample sizes, this impacts the reliability of the study as it cannot be generalised to certain demographics.
  • Researchers and other’s who read the study can have interpretation bias as the information is subjective and open to interpretation
  1. Quantitative research

Advantages: 

  • Usually observes a large sample, ensuring a broad percentage is taken into consideration and reflected
  • Produces precise results that can be widely interpreted
  • Minimises any research bias through the collection and representation of objective information
  • Data driven research method that depicts effectiveness, comparisons and further analysis.

Disadvantages: 

  • Does not derive “meaningful” and in-depth responses, only precise figures are included in findings
  • Quantitative studies are expensive to conduct as they require a large sample 
  • When designing a quantitative study, it is important to pay extra attention to all factors within the study, as a small fault can largely impact all results.

How to effectively analyse qualitative and quantitative data?

Since the data collection method for qualitative and quantitative studies are different, so is the analysis and organisation of the gathered information. In this section, we dive into a step-by-step guide to effectively analyse both types of data and information to derive accurate findings and results. 

Analysing qualitative data

  1. Types of qualitative data analysis
Content analysisIdentifies patterns derived from text. This is done by categorising information into themes, concepts and keywords.
Narrative analysisObserves the manner in which people tell stories and the specific language they use to describe their narrative experience.
Discourse analysisUsed to understand political, cultural and power dynamics. This methos specifically focuses on the manner in which individuals express themselves in social contexts.
Thematic analysisThis method is used to understand the meaning behind the words participants use. This can be deduced by observing repeated themes in text.
Grounded theoryMostly used when very little information is known about a case or phenomenon. The grounded theory is an “origin” theory and other cases and experiences are examined in comparison to the grounded theory.
  1. Steps to analyse qualitative data
  1. Once your data has been collected, it is important to code and categorise the information to easily identify the source. 
  2. After organising the information, you will need to correlate the information logically and derive valuable insights.
  3. Once the correlations are solid, you will need to choose how to depict the information. In qualitative data, researchers usually provide transcripts from interviews and visual evidence from various sources. 

Analysing quantitative data

  1. Types of quantitative data analysis
Descriptive analysisThis method focuses on summarising the collected data and describing its attributes. This is when mean, median, mode, frequency or distribution is calculated.
Inferential analysisThis method allows researchers to draw conclusions from the gathered statistics. It allows researchers to analyse the relationship between variables and make predictions; this includes cross-tabulation, t-tests and factor analysis. 
  1. Steps to analyse quantitative data
  1. Once the data has been collected, you will need to “clean” the data. This essentially means that you’ll need to observe any duplications, errors or omissions and remove them. This ensures the data is accurate and clear before analysis. 
  2. You will now need to decide whether you will analyse the data using descriptive or inferential analysis, depending on the gathered data set and the findings you’d like to depict.
  3. Now, you’ll need to visualise the data using charts and graphs to easily communicate the information in your research paper. 

Conduct your research on Zendy todayThis blog thoroughly covered qualitative and quantitative data and took you through how to analyse, depict and utilise each type appropriately. Continue your research into different types of studies on Zendy today, search and read through millions of studies, research and experiments now.

Categories
en Uncategorized

A step-by-step guide to writing a research paper outline

A research outline guides the flow of the research paper, it is meant to ensure that the ideas, concepts and points are coherent and that the study and research has a well-defined point of focus. The outline sets guidelines for each section of the research paper, what it will address, explore and highlight. Working on a research paper outline is considered an important preliminary activity that improves the structure of the research paper, this is critical for categorising collected data. Think of it as a brainstorm session for your research paper that also implements effective time management.

Understanding research paper outline

A research paper ideally consists of 5 sections; abstract, introduction, body, conclusion and references. Each of these sections contributes to collating key information on the research design, in this section of the blog we dive into the purpose or each section.

AbstractThe abstract sits on the first page of the research paper. It’s main purpose is to provide a brief overview of the paper by highlighting key findings, describing methodology, and summarising conclusive points.
IntroductionThe introduction is crucial as it presents the research question, states the objectives or hypotheses, and outlines the scope and structure of the paper. 
BodyThe body of the research paper is where the content is discussed and highlighted. It can present detailed analysis, support arguments with evidence, address counterarguments and limitations, draw conclusions. 
ConclusionThe conclusion is a closing statement, it summarises the key findings, restates the aims and research question, reflects on the research process, discusses implications and contributions. 
ReferencesThe reference list is a crucial part of the paper, it ensures plagiarism is avoided, builds credibility, facilitates further reading to support claims and arguments. 

Step-by-step guide to conducting research outline

  1. Select a Topic:
    1. Choose a topic that aligns with your research requirements.
  2. Conduct Preliminary Research:
    1. Gather background information on your topic by reading through key scholarly articles, books, and credible online sources.
    2. Take notes on key ideas, findings, and arguments from reviewing the literature.
  3. Identify the Research Question or Thesis Statement:
    1. Formulate a focused research question or thesis statement that defines the purpose of your study.
  4. Create the Title:
    1. Write an informative title that accurately reflects the main topic and focus of your research paper.
  5. Write the Abstract:
    1. Summarize the objectives, methods, results, and conclusions of your research in a brief abstract.
  6. Develop the Introduction:
    1. Include background information to contextualize the research.
    2. Present the research question or thesis statement.
    3. Outline the scope and objectives of the study.
    4. Take the reader through the structure of the paper by mapping it out.
  7. Outline the Body:
    1. Organise and structure the main points and subpoints of your research.
    2. Ensure the content flows cohesively.
    3. Include supporting evidence, examples, data, or arguments.
  8. Craft the Conclusion:
    1. Summarise the key findings and insights.
    2. Highlight the thesis statement or research question.
    3. Discuss the implications of your findings and suggest methods for future research.
    4. End the conclusion by highlighting the significance of the study.
  9. Compile the References:
    1. Create a list of references following the appropriate citation style (e.g., Harvard, APA, MLA, Chicago).
    2. Ensure that all sources are accurately cited and formatted.
  10. Review and Revise:
    1. Review your research outline for coherence and clarity.
    2. Edit the outline as needed to improve organization, flow, and accuracy of information.
    3. Ensure the reference list follows the requirements of the correct format

Research outline formats

  1. Traditional outline – Where thesis statement is provided at the end of the introduction, body paragraphs support thesis with research and a conclusion is included to emphasise key concepts of research paper.
  2. Alphanumeric outline – Outline format uses letters and numbers in this order: A, I, II, III
  3. Decimal outline – This format requires each main point to be labeled with a whole number, and each sub-point 

Conduct your research on Zendy Today

As a thriving AI-powered academic research library, Zendy hosts a wide variety of academic research across various disciplines and branches of study. Draft your next or brush up your current research paper outline by skimming through the millions of credible resources Zendy offers!

Categories
en Uncategorized

Webinar Recap: Supporting the publishing and discovery journey of young and emerging scholars in the Global South

On the 25th of April, Zendy partnered with Bristol University Press to host an insightful joint webinar titled, supporting the publishing and discovery journey of young and emerging scholars in the Global South. 

The discussion panel was moderated by the Editorial Director of Bristol University Press, Victoria Pittman and featured the President of African Gong, Elizabeth Rasekoala, the Deputy Editorial Director at Bristol University Press, Stephen Wenham and the Partnerships Relations Manager at Zendy, Sara Crowley Vigneau. 

In this blog, we summarise the contributions of each speaker to the joint webinar. 

Elizabeth Rasekoala – President of African Gong

  • Addressed key systematic issues within publishing in the Global South 
  • Academic research is predominantly published in English, which is not the first language of many in the Global South, hence publishers should be open to accepting research in different languages. 
  • Discussed the concept of “helicopter research syndrome” wherein more established researchers allocate data collection tasks to locals in the Global South and monitor their work but don’t credit them in the final academic papers 
  • Highlighted the book published by Bristol University Press titled, Race and cultural inclusion: Innovation, decolonization, and transformation. The book had a total of 30 contributing writers. 10 young scholars, 10 seasoned scholars and 10 senior scholars to facilitate emerging scholars get published. 

Stephen Wenham – Deputy Editorial Director at Bristol University Press

  • Highlighted BUP’s international reach and efforts to work with young authors
  • Bristol University Press has publications that are available globally. In the global south, BUP tries to match the books to the local market. 
  • Local distributors receive a discount and local publishers assist in localising the publications and releasing local editions of books
  • Works with sales agents to ensure publications by local authors are highlighted in relevant regions

Sara Crowley Vigneau – Partnerships Relations Manager at Zendy

  • Highlighted the relationship between publishers and libraries in advancing access in developing regions
  • Zendy supports scholars in the Global South through offering an affordable global subscription, while also working with publishers to include research generated by researchers in the Global South. 
  • Most of Zendy’s global users are aged between 18-34 and 20% of Zendy’s userbase is situated in African countries and territories. 
  • Zendy is actively working on “countries in crisis’ initiative where in Zendy works with publishers to make research content free in developing regions 

Conduct your research on Zendy

As a growing AI-powered research library, Zendy is committed to hosting webinars that address important challenges and highlight key initiatives in the world of academia. Head to Zendy’s YouTube channel now to watch all our webinar recordings. Furthermore, take your research to the next level and head to Zendy now to try out our suite of AI tools including ZAIA! 

Categories
en Uncategorized

What is a DOI? Strengths, Limitations & Components

DOI is short for Digital Object Identifier. It is a unique alphanumeric sequence assigned to digital objects, it is used to identify intellectual property on the internet. DOI’s are usually assigned to scholarly articles, datasets, books, videos and even pieces of software. 

Understanding DOI’s

The digital object identifier is a unique number made up of a prefix and suffix, segregated by a forward slash. 

For example: 10.1000/182

The sequence always begins with a 10. The prefix is a unique 4 or more digit number assigned to establishments and the suffix is assigned by publisher as it is designed to be flexible with publisher identification standards.

Where can I find a DOI?

In most scholarly articles, the DOI should be on the cover page. If the DOI isn’t included in the article, you may search for it on CrossRef.org by using the “Search Metadata” function.

How can I use the digital object identifier to find the article it refers to?

  • If the DOI starts with http:// or https://, pasting it on your web browder will help you locate the article.
  • You can turn any DOI starting with 10 into a URL by adding http://doi.org/ before the DOI. For example, 10.3352/jeehp.2013.10.3 becomes https://doi.org/10.3352/jeehp.2013.10.3
  • If you’re off campus when you do this, you’ll need to use this URL prefix in front of the DOI to gain access to UIC’s full text journal subscriptions: https://proxy.cc.uic.edu/login?url=https://doi.org/ . For example: https://proxy.cc.uic.edu/login?url=http://doi.org/10.3352/jeehp.2013.10.3

Strengths of Digital Object Identifier

  • Permanent identification: Digital object identifier provides a permanent link to digital content, making sure it remains accessible even if URL or metadata is updated. 
  • Citations: It uniquely identifies research papers, which facilitates accurate referencing and citing.
  • Interoperability: DOIs are widely recognized as they can be utilised across different platforms, databases and systems.
  • Tracking and metrics: DOIs provide key information like publication date, authors, keywords and more. This can be used to track usage metrics, measuring impact and improving discoverability
  • Integration with services: DOIs are integrated with various tools like reference managers, academic search engines, and digital libraries. These mediums enhance the visibility and accessibility of research material with DOIs. 

Limitations of Digital Object Identifier 

  • Cost: Digital object identifiers are costly for smaller organisations or individual researchers. While some services offer free digital object identifier registration for certain content, there may be fees associated with others, particularly for maintenance and updates.
  • Accessibility: There may still be barriers to access for individual researchers or organisations in regions with limited resources. Ensuring equitable access to digital object identifier services and content remains a challenge.
  • Content Preservation: While the sequence provide persistent links to digital content, they do not guarantee the preservation or long-term accessibility of that content. Ensuring the preservation of digital objects linked to DOIs require additional efforts and infrastructure beyond the system itself.
  • Granularity: Sequences are assigned to individual digital objects, such as articles, datasets, or books. However, there may be cases where more granular identification is required, such as specific sections within a larger work or versions of a dataset. Addressing these granularity issues within the digital object identifier system can be complex.

Conduct your research on Zendy today

Now that you’ve gained a better understanding of how DOI works and impacts the world of research, you may begin your search and find your next academic discovery on Zendy! Our advanced search allows you to input DOI, ISSN, ISBN, publication, author, date, keyword and title. Give it a go on Zendy now.

Categories
en Uncategorized

Learn to use ZAIA – Zendy’s AI Research Assistant

What is ZAIA?

ZAIA – AI Assistant is a domain-specific LLM (Large Language Model) that has been fine tuned with research available on Zendy. ZAIA was designed to make the discoverability and accessibility of academic research simpler on Zendy, while also enhancing the efficiency and effectiveness of literature review. In our latest version release, ZAIA has seen significant improvements, these include: 

  • Ask ZAIA: Users and readers can now ask ZAIA specific paper-level questions, introducing a new way to conduct literature analysis.
  • PDF Analysis: ZAIA now has the capability to analyse any PDF. Upload or link a research paper with sections and ZAIA will extract, analyse and summarise each section. 
  • Reference validation and verification: using techniques such as chain of verification, all references go through a validation and verification process to increase accuracy. 
  • Conversation and analysis history: once you log in, you can now see a complete history of all conversations with ZAIA and a history of PDFs analysed.
  • An enhanced fine-tuned model for increased accuracy.
  • ZAIA is also now accessible without registration. 

In this blog, we run you through the various features on ZAIA to teach you to use it to its full potential! 

Ask ZAIA

Step 1: Access ZAIA – AI Assistant through the Zendy home page

Step 2: Once your prompt is solved by ZAIA, you may double check the references ZAIA provides through the “Reference Details” section on the right. 

PDF Analysis

Step 1: To access the PDF analysis feature on ZAIA, switch from “Conversation” to “PDF Analysis” 

Step 2: Enter a research paper of your choice and then click “Analyse document”

Step 3: ZAIA then provides a summary of each section within the research paper, including references so you can quickly grasp the key concepts. 

Conversation History

Step 1: You may access your conversation and analysis history on both pages from the left side bar, simply click on the session you’d like to revisit and ZAIA will load the entire conversation and analysis. 

In this blog, we’ve covered how to conduct PDF analysis on ZAIA, access your history and how to cross-check references. As we further build and improve ZAIA, we look forward to adding helpful functionalities that further accelerate the efficiency and effectiveness of literature review. 

Visit zendy.io and utilise ZAIA – AI Research Assistant to help you with your next research project.

Categories
en Uncategorized

Zendy Announces New Version Releases of ZAIA – AI Assistant

United Arab Emirates, 13th March 2024 – AI-powered research library Zendy has announced the launch of a significant version release for its domain-specific Large Language Model (LMM), ZAIA (Zendy AI Assistant). 

Developed by Zendy’s data science team and initially launched in December 2023, ZAIA is designed to enhance the efficiency and effectiveness of research discovery and literature review. In this new version, a host of new features have been introduced to support researchers: 

  • Ask ZAIA: You can now ask specific questions to ZAIA on a paper level, giving you a new way to conduct in-depth analysis during literature review.
  • PDF Analysis: ZAIA can now analyse any PDF. Upload or link a research paper with sections, and ZAIA will extract, analyse, and summarise each section, including the abstract, introduction, methods, results, discussion, and references. 
  • Reference validation and verification: using techniques such as chain of verification, all references go through a validation and verification process to increase accuracy. 
  • Conversation and analysis history: once you log in, you can now see a complete history of all conversations with ZAIA and a history of PDFs analysed.
  • An enhanced fine-tuned model for increased accuracy.
  • ZAIA is also now accessible without registration. 

ZAIA is not a general-purpose language model. It is fine-tuned with Zendy’s own data sources, allowing it to support higher-level abstractions for research-specific use cases.

“ZAIA 0.1 takes us closer to our vision of creating an ecosystem of research-centric AI tools using the latest development methods that increase efficiency and reliability. The future of research is intertwined with the vast capabilities of AI, and we are committed to leveraging the best of AI to provide solutions to the pressing issues researchers face in research discovery,” said Zendy’s Chief Technology Officer, Rodrigo Pinto. 

“We have a core focus on increasing collaboration with publishers and data providers to navigate the increasing potential of AI. We look forward to extending the vast capabilities of our LLM and all our learnings to institutions, publishers, and organisations looking to streamline information discovery and retrieval using AI,” said Zendy Co-founder Kamran Kardan. 

Committed to helping foster an ecosystem of collaborative partnerships rooted in responsible AI practices, Zendy believes AI is important in fostering an equitable research and publishing ecosystem, but only with ethical guidelines. In response to the growing discussion around AI, Zendy recently released a list of AI imperatives to guide strategic development and the integration of AI technologies. 

To find out more about Zendy’s AI solutions, email hello@zendy.io.

You can use ZAIA now on Zendy, visit www.zendy.io/zaia.

To read the Zendy AI Imperatives statement, click here. 

About Zendy

Zendy is a product of Knowledge E. Since its inception in 2019, Zendy has introduced over 500,000 users to a better way to research. Zendy’s intuitive AI-powered research library features millions of journals, articles, e-books, and more, allowing users to access unlimited content for an affordable monthly subscription. Zendy also offers a free open-access plan. 

Press contact: 

Monica Chinsami

Head of Marketing

Categories
en Uncategorized

Decolonising and diversifying academia: Interview with Nahil Nasr, the Community Engagement Manager at F.O.R.M.

This January, the Forum of Open Reseach MENA hosted its first community development activity of 2024. The “Decolonising Open Science Symposium: Dismantling Global Heirarchies of Knowledge” addressed the influence of western prominence on knowledge distribution and research, highlighting how these ideologies and standards impact the Arab region.

Within the landscape of research, conversations and collaborations not only address inequalities but also break barriers to accessibility. In this blog, we interviewed Nahil Nassar who is the community engagement manager at the Forum of Open Research MENA. At the symposium, Nahil touched on the work that open science has in building stronger foundations for diverse research consumption and the biases that exist in the research landscape. We take a deeper dive into this conversation. 

  1. How does F.O.R.M. facilitate conversations around decolonising academia?

FORM is a community based organisation that centers its attention on the Arab region. That means prioritising Arab voices in academia to develop a regionally and culturally relevant model of Open Science to implement across the board.

While we do, of course, work with organisations that are based in the Global North, we try to be transparent when it comes to power dynamics, and recognise that we are only as strong as our community. 

  1. What role does open science play in escalating research outside western europe?

Open Science has the potential to really build an even playing field for researchers in the Global South because of its financially and digitally accessible model. In its best form, Open Science should allow researchers from the Global South to publish their work without limitations in cost or geography.

The problem is that Open Science publishing is not always functioning in its most optimum form, and things like APCs, metric frameworks, and language hierarchies (English being a dominant language across the research landscape) can still limit researchers in the same ways that traditional academic publishing models do.

  1. What are some biases that exist in the open science landscape?

A major bias that comes out of the Open Science landscape, especially when it comes to the Global South, is that Open Science research is bad research. There’s this assumption that if research isn’t published in perfect English, or focuses on a very niche subject that’s really only relevant to specific local contexts, then that means the research is either low quality or irrelevant. 

This is especially because of how research is prioritised in its value these days, and this is one of the many places where commodification enters the conversation as a major issue. Often times, major funding is only allocated to research that is deemed important by multinational corporations or prestigous research institutions in the Global North who sort of set the agenda of what is necessary to study and what isn’t – and these topics are usually prioritised based on the needs of these entities and their contexts, and completely ignore the localised needs of researchers in the Global South, who then don’t have access to that same funding. 

  1. Please explain how absolute objectivity is colonial ideology

This is a really interesting ideology to ponder on in decolonial discourse, because it seems very out there to say that there’s no such thing as objective truth, especially in a world that is run by scientific innovation. The idea of objectivity may seem to be clear and cut, but it goes back to the idea of intellectual dominance and colonialism. There was an ideological hierarchy set by colonial powers that placed their “truth” as the only “truth”, and took objectivity to mean that their truth is the only one with any substance or value. 

Many indigenous knowledge systems question this idea of absolute objectivity, because it is often rooted in inherently colonial, patriarchal, and violent understandings of nature, human experience, and society. I was first introduced to this philosophy through postcolonial gender theory, where researchers like Vandana Shiva questioned the very idea of scientific knowledge as we know it today as something that was forced on us as the only virtuous fact, but is sometimes actually the most harmful opinion. 

  1. What is the direct impact of colonisation on knowledge production today?

The impact of colonisation on knowledge production today can be found in a plethora of arenas. While colonisation as we once knew it is not nearly as prominent as it was in the 19th and 20th centuries, neo-imperial and neo-colonial ideologies are still very much strong holding the majority of the world’s systems. You can see legacies of it in how we think about scientific studies, methodologies, or even the metrics that we use to classify ‘good’ and ‘bad’ research. 

It informs how we think about credibility, and determines who gets to speak the loudest and whose voice gets silenced. It marginalises researchers who use indigenous knowledge methodologies (often rooted in intuition and connection to land and spirit) and prioritises the voices of liberal scientists who believe in objective fact rooted in numbers and rationality. 

Overall, it prioritises knowledge produced and disseminated by Western organisations and researchers that then have an impact on Western communities, and leave the global majority out of the conversation.

Watch the webinar here

Categories
en Uncategorized

Webinar Recap: Research in the age of AI – Tools, Trends & Innovations

In a pivotal time where AI-powered tools shape efficiency in research processes, the world of academia is witnessing a significant transformation. This calls for a thorough discussion to define ethical AI usage in order to leverage the technology to improve the landscape of academia. 

We recently hosted a webinar to address and discuss the usage of AI in research. The webinar titled, “Research in the age of AI – Tools, Trends & Innovations” was moderated by Knowledge E’s chief academic officer, Dr. Emily Choynowski; and featured Zendy co-founder Kamran Kardan, Zendy Chief Technology Officer, Rodrigo Pinto, and Professor Leo Lo from the University of New Mexico.

Kamran Kardan – CEO of Knowledge E and Zendy

  • Driving an AI-powered research library [Zendy], ethical usage of AI is a core value. 
  • AI benefits and facilitates interdisciplinary research by allowing researchers to quickly learn about areas of study they are not specialised in, which creates productivity and efficiency in research processes. The technology also allows researchers to analyse citations and determine its relevance to their current projects. 
  • To tackle the ethical challenges AI presents, Zendy released an AI imperatives statement that guides the direction and intention behind developing AI products. 

Professor Leo Lo – Professor at University of New Mexico

  • Governments and businesses should invest in developing AI literacy in current education landscape
  • Conducted a survey in April 2023 amongst US academic library employees when Chat GPT was new and found that AI training was required, the employees presented a limited understanding of AI concepts, and that generative AI is not frequently used. 
  • Conducted follow-up surveys in December 2023 and found that there was a shift in attitude towards AI. Libraries had implemented AI solutions and applications while actively developing AI literacy initiatives. 
  • Developed AI competencies for librarians that tackles the comprehensive understanding, training and analysis required to confidently use AI to streamline library operations and transform services. 

Rodrigo Pinto – CTO of Zendy

  • Introduction to LLMs: a LLM (Large Language Model) is a type of AI designed to understand and generate human language. This technology has reasoning capabilities, understands questions and reads from external knowledge to respond with insights. 
  • Introduction to ZAIA – AI Assistant for research: ZAIA is an LLM developed by Zendy. It was designed to expedite the research process by analysing study results and providing credible responses backed by references.
  • Challenges of AI: bias, reliability, and data privacy. The mitigation strategies deployed by Zendy are safeguards and chains of verification and thought to minimise bias. 

As AI advances and creates efficiency across different industries, there has been a significant requirement to regulate the use of AI. In our efforts to make research accessible we launched a suite of AI tools on Zendy last year, to ensure ethical usage of our AI technology, we also established a comprehensive list of AI imperatives to guide the development and implementation of AI within our products. 

Discover academic research and easily consume papers with comprehensive AI tools now on Zendy