Online Research Tools You Need to Know About in 2025
Nov 19, 2024 |
22 Mins ReadIf you’re just starting your research or unsure where to begin, these research tools for researchers can help you get started and make your work easier.
Brainstorming Tools
Defining a clear scientific topic has always been the challenging part of the research process. Even with a deep understanding of the field, researchers cannot stop asking themselves, “Do I provide a real solution?” That’s why brainstorming is such an important step, as it helps you go from Zero to One. Here’s a list of research tools used in brainstorming to help you set up your topics and make sure it’s unique and relevant.
Miro is an online platform for you and your colleagues to gather every idea in one place. It gives you plenty of templates such as mind maps, bubble maps, or even tree maps with sticky notes that will help you pull out your thoughts from your mind right in front of your eyes. This easy and simple online tool used in research will save you hours of thinking inside your head.
What makes MindMeister unique and suitable for research tools is that it has the user interface of what a researcher's mind needs, especially in the phase of choosing a topic. You and your team can use MindMeister on the go with a native mobile application for both Android and iOS. Benefits?
| Tool | Free Plan Features |
| Miro | 3 editable boards, templates, 100+ integrations |
| MindMeister | Up to 3 mind maps, unlimited collaborators and mobile apps. |
Literature Search & Access Tools
Now, after a long day of brainstorming, you finally have your next research topic in hand. It’s time to conduct and structure a literature review to set the stage for your research question.
In the past, researchers would travel to universities and libraries to access academic resources. With the arrival of the internet, they began to search online across many websites. Now, there are millions of research papers available online. Despite the increased accessibility, the need for a one-stop shop for peer-reviewed academic papers has become essential. These research tools have been designed to provide access to millions of articles in one place, while also offering features to help you organise them efficiently.
With over 48 million research papers on a wide range of topics used by over 751,000 researchers worldwide, Zendy is one of the top 10 open access library databases that offer much more than just an online database for academic resources. Its simple, easy-to-use interface and powerful search filters make it one of the most efficient research tools available. This allows you to quickly find the articles you need, organise your sources and build a solid foundation for your research, saving you both time and money during the literature review stage.
With Zendy, you have three options:
- Zendy Open – The free plan gives access to open-access articles.
- Zend Plan gives you unlimited AI research tools, including ZAIA, AI Summarise, Insights, PDF Analysis, and Keyphrase Highlight.
- Zendy Plus – Full access to paywalled articles along with unlimited usage of AI tools.
Google Scholar is one of the most widely used research tools today. It’s a free tool that allows researchers to easily search through millions of academic articles, theses, books, and conference papers across various disciplines. In 2025, it continues to be an essential tool for students, professionals and researchers who need quick access to high-quality, peer-reviewed materials.
While Google Scholar may not have the same in-depth organisational tools as other research tools, its ability to provide access to a vast amount of information with minimal effort makes it a go-to option for many researchers.
Reference and Citation Management Tools
Organising large amounts of data, sharing findings with colleagues, managing complex citations and references, and, of course, keeping up with deadlines, these tasks can be time-consuming and feel overwhelming. However, tools used in research like Zotero and Paperpile can help take care of all these details. These research tools make managing your project a lot easier, allowing you to focus on what really matters without getting weighed down by the small stuff.
Instead of having documents and notes scattered all over the place, tools used in research like Zotero and Paperpile keep everything in one spot, so it’s easy to find what you need, saving time and reducing mistakes.
Zotero is one of the great research tools for organising your project. It automatically grabs citation details from websites and academic databases, and you can attach PDFs, notes and other files to each reference, so everything stays in one place. Zotero allows you to organise your research into collections and tags, making it easier to find what you need later. It also integrates with Word and Google Docs to add citations and create bibliographies while you write. Plus, it syncs across devices, so you can access your research anytime, anywhere. It's a simple way to stay organised and keep everything in one spot.
If you’re looking for research tools that integrate easily with Google’s ecosystem, Paperpile is the best choice. It’s specifically built for Google apps! You can organise, find and collect, download and sync, annotate, share, and cite in Google Docs. With its clean interface and integration with Google, Paperpile is a great choice for anyone looking to simplify research management. It’s straightforward, user-friendly and saves lots of hours.
Data Collection and Survey Tools
Not so long ago, researchers often gathered data based on assumptions and possibilities within a small circle of interest, which wasn’t always accurate. Today, with the help of advanced research tools, you can collect and analyse data more precisely from a broader range of samples online.
I’ve tried Jotform, and in just 1:57 minutes, I created an account and built a form with basic questions (name, age, location, background, etc.) using its drag-and-drop feature. It’s incredibly easy and fast to use. In addition, Jotform offers many features, such as adding collaboration and integration with various project management software. It is a great tool used in research to simplify data collection.
You may have noticed what makes Google's tools on top is their straightforward, fast, free and most of all, their simplicity. This simplicity is what makes Google stand out. Google Forms, for example, allows you to create extensive questionnaires and surveys that are easy for your target audience to use and comprehend. Its integration with other Google tools, like Google Sheets, makes it easy to manage and analyse responses all in one place. For researchers looking for research tools to gather data, Google Forms offers an effortless option for collecting valuable data.
Project Management and Collaboration
The right project management and collaboration research tools can make it much easier to stay on top of everything. Notion and Trello are two popular choices among researchers, and they are reliable options that can help you bring structure to your research management with less effort.
Notion is a one-stop workspace, combining notes, project management, and databases in one place. You can set up a hub for your research, keep notes, track references, and collaborate with others in real time, adapting it to fit the specific needs of your project.
Sometimes, seeing tasks laid out visually makes organising projects a lot easier. Trello is a simple research tool that does just that. It allows you to arrange tasks on boards and lists and view them in either calendar or timeline formats. With Trello, you can sort out to-do lists, create channels for different topics, assign tasks to team members, set deadlines and check your project’s overall progress, all while working together with your colleagues in real time. You will find Trello helpful for managing literature reviews, tracking data collection, and collaborating on research tasks.
Academic Writing and Editing
While these research tools are helpful, they shouldn’t do all the work for you. They’re best used as a way to clean up your writing, not to create it. The main ideas and structure of your research should come from you, with the tools stepping in to help with the fine details. Let’s take a look at some of the best writing tools used in research that can help you improve your academic writing and make your research easier to read and understand.
A very practical writing assistant tool offers more than 400 features, including grammar checks, vocabulary improvement suggestions, plagiarism detection, citation recommendations and more.
What makes Grammarly really useful is how easy it is to use. You can install it as an extension on your browser or use it in its standalone app, and it works across different platforms, from your computer to your phone.
Academic writing isn’t just about getting the facts right, it’s about presenting ideas clearly so they’re easy to understand. Most research tools, like spelling and grammar checkers, can help fix basic mistakes, but they’re often not designed for research-level writing. This is where Paperpal really shines.
Paperpal is built to support the unique needs of researchers and students. It doesn’t just spot typos; it helps you refine your language, follow academic standards, and structure your paper for better readability. For example, when writing a research paper, Paperpal can suggest improvements that make complex ideas easier to follow and help you use the right tone for a professional audience.
With Paperpal, your research writing will meet the standards journals are looking for. This makes it a valuable addition to the tools used in research.
In Conclusion
2025 is proving to be an exciting time for the academic industry. Today, researchers have access to an impressive range of research tools, starting with brainstorming platforms to citation managers, academic writing assistants and project management software that make every stage of research more efficient and effective. The right tools used in research can help you focus on what matters most.
From Curator to Digital Navigator: Evolving Roles for Modern Librarians
With the growing integration of digital technologies in academia, librarians are becoming facilitators of discovery. They play a vital role in helping students and researchers find credible information, use digital tools effectively, and develop essential research skills. At Zendy, we believe this shift represents a new chapter for librarians, one where they act as mentors, digital strategists, and AI collaborators. Zendy’s AI-powered research assistant, ZAIA, is one example of how librarians can enhance their work using technology. Librarians can utilise ZAIA to assist users in clarifying research questions, discovering relevant papers more efficiently, and understanding complex academic concepts in simpler terms. This partnership between human expertise and AI efficiency allows librarians to focus more on supporting critical thinking, rather than manual searching. According to our latest survey, AI in Education for Students and Researchers: 2025 Trends and Statistics, over 70% of students now rely on AI for research. Librarians are adapting to this shift by integrating these technologies into their services, offering guidance on ethical AI use, research accuracy, and digital literacy. However, this evolution also comes with challenges. Librarians must ensure users understand how to evaluate AI-generated content, check for biases, and verify sources. The focus is moving beyond access to information, it’s now about ensuring that information is used responsibly and critically. To support this changing role, here are some tools and practices modern librarians can integrate into their workflows: AI-Enhanced DiscoveryUsing tools like ZAIA to help researchers refine queries and find relevant studies faster. Research Data Management Organising, preserving, and curating datasets for long-term academic use. Ethical AI and Digital Literacy Training Teaching researchers how to verify AI outputs, evaluate bias, and maintain academic integrity. Collaborative Digital Spaces Facilitating research communication through online repositories and discussion platforms. In conclusion, librarians today are more than curators, they are digital navigators shaping how knowledge is accessed, evaluated, and shared. As technology continues to evolve, so will its role in guiding researchers and students through the expanding world of digital information. .wp-block-image img { max-width: 65% !important; margin-left: auto !important; margin-right: auto !important; }
Strategic AI Skills Every Librarian Must Develop
In 2026, librarians who understand how AI works will be better equipped to support students and researchers, organise collections, and help patrons find reliable information faster. Developing a few key AI skills can make everyday tasks easier and open up new ways to serve your community. Why AI Skills Matter for Librarians AI tools that recommend books, manage citations, or answer basic questions are becoming more common. Learning how these tools work helps librarians: Offer smarter, faster search results. Improve cataloguing accuracy. Provide better guidance to researchers and students. Remember, AI isn’t replacing professional judgment; it’s supporting it. Core AI Literacy Foundations Before diving into specific tools, it helps to understand some basic ideas behind AI. Machine Learning Basics:Machine learning means teaching a computer to recognise patterns in data. In a library setting, this could mean analysing borrowing habits to suggest new titles or resources. Natural Language Processing (NLP):NLP is what allows a chatbot or search tool to understand and respond to human language. It’s how virtual assistants can answer questions like “What are some journals about public health policy?” Quick Terms to Know: Algorithm: A set of steps an AI follows to make a decision. Training Data: The information used to “teach” an AI system. Neural Network: A type of computer model inspired by how the brain processes information. Bias: When data or systems produce unfair or unbalanced results. Metadata Enrichment With AI Cataloguing is one of the areas where AI makes a noticeable difference. Automated Tagging: AI tools can read through titles and abstracts to suggest keywords or subject headings. Knowledge Graphs: These connect related materials, for example, linking a book on climate change with recent journal articles on the same topic. Bias Checking: Some systems can flag outdated or biased terminology in subject classifications. Generative Prompt Skills Knowing how to “talk” to AI tools is a skill in itself. The clearer your request, the better the result. Try experimenting with prompts like these: Research Prompt: “List three recent studies on community reading programs and summarise their findings.” Teaching Prompt: “Write a short activity plan for a workshop on evaluating online information sources.” Summary Prompt: “Give me a brief overview of this article’s key arguments and methods.” Adjusting tone or adding detail can change the outcome. It’s about learning how to guide the tool rather than letting it guess. Ethical Data Practices AI tools can be useful, but they also raise questions about privacy and fairness. Librarians have always cared deeply about protecting patron information, and that remains true with AI. Keep personal data anonymous wherever possible. Review AI outputs for signs of bias or misinformation. Encourage clear policies around how data is stored and used. Ethical AI is part of a librarian’s duty to maintain trust and fairness. Automating Everyday Tasks AI can take over some of the small, routine jobs that fill up a librarian’s day. Circulation: Systems can send overdue reminders automatically or manage renewals. Chatbots: Basic questions like “What are the library hours?” can be handled instantly. Collection Management: AI can spot patterns in borrowing data to suggest which books to keep, reorder, or retire. Building Your Learning Path Getting comfortable with AI doesn’t have to mean earning a new degree. Start small: Take short online courses or micro-certifications in AI literacy. Join librarian groups or online forums where people share practical tips. Block out one hour a week to try out a new tool or attend a webinar. A little consistent learning goes a long way. Making AI Affordable Many smaller libraries worry about cost, but not every tool is expensive. Free Tools: Some open-access AI platforms, like Zendy, offer affordable access to research databases and AI-powered features. Shared Purchases: Partnering with other libraries to share licenses can cut costs. Cloud Services: Pay-as-you-go plans mean you only pay for what you actually use. There’s usually a way to experiment with AI without stretching the budget. Showing Impact Once AI tools are in use, it’s important to show their value. Track things like: Time saved on cataloguing or circulation tasks. Patron feedback on new services. How often are AI tools used compared to manual systems? Numbers matter, but so do stories. Sharing examples, like a student who found research faster thanks to a new search feature, can make your case even stronger. And remember, the future of librarianship is about using AI tools in libraries thoughtfully to keep libraries relevant, reliable, and welcoming spaces for everyone. .wp-block-image img { max-width: 75% !important; margin-left: auto !important; margin-right: auto !important; }
Key Considerations for Training Library Teams on New Research Technologies
The integration of Generative AI into academic life appears to be a significant moment for university libraries. As trusted guides in the information ecosystem, librarians are positioned to help researchers explore this new terrain, but this transition requires developing a fresh set of skills. Training your library team on AI-powered research tools could move beyond technical instruction to focus on critical thinking, ethical understanding, and human judgment. Here is a proposed framework for a training program, organised by the new competencies your team might need to explore. Foundational: Understanding Access and Use This initial module establishes a baseline understanding of the technology itself. Accessing the Platform: Teach the technical steps for using the institution's approved AI tools, including authentication, subscription models, and any specific interfaces (e.g., vendor-integrated AI features in academic databases, institutional LLMs, etc.). Core Mechanics: Explain what a Generative AI platform (like a Large Language Model) is and, crucially, what it is not. Cover foundational concepts like: Training Data: Familiarise staff with how to access the institution’s chosen AI tools, noting any specific authentication requirements or limitations tied to vendor-integrated AI features in academic databases. Prompting Basics: Introduce basic prompt engineering, the art of crafting effective, clear queries to get useful outputs. Hallucinations: Directly address the concept of "hallucinations," or factually incorrect/fabricated outputs and citations, and emphasise the need for human verification. Conceptual: Critical Evaluation and Information Management This module focuses on the librarian's core competency: evaluating information in a new context. Locating and Organising: Train staff on how to use AI tools for practical, time-saving tasks, such as: Generating keywords for better traditional database searches. Summarising long articles to quickly grasp the core argument. Identifying common themes across a set of resources. Evaluating Information: This is perhaps the most critical skill. Teach a new layer of critical information literacy: Source Verification: Always cross-check AI-generated citations, summaries, and facts against reliable, academic sources (library databases, peer-reviewed journals). Bias Identification: Examine AI outputs for subtle biases, especially those related to algorithmic bias in the training data, and discuss how to mitigate this when consulting with researchers. Using and Repurposing: Demonstrate how AI-generated material should be treated—as a raw output that must be heavily edited, critiqued, and cited, not as a final product. Social: Communicating with AI as an Interlocutor The quality of AI output is often dependent on the user’s conversational ability. This module suggests treating the AI platform as a possible partner in a dialogue. Advanced Prompt Engineering: Move beyond basic queries to teach techniques for generating nuanced, high-quality results: Assigning the AI a role (such as a 'sceptical editor' or 'historical analyst') to potentially shape a more nuanced response. Practising iterative conversation, where librarians refine an output by providing feedback and further instructions, treating the interaction as an ongoing intellectual exchange. Shared Understanding: Practise using the platform to help users frame their research questions more effectively. Librarians can guide researchers in using the AI to clarify a vague topic or map out a conceptual framework, turning the tool into a catalyst for deeper thought rather than a final answer generator. Socio-Emotional Awareness: Recognising Impact and Building Confidence This module addresses the human factor, building resilience and confidence Recognising the Impact of Emotions: Acknowledge the possibility of emotional responses, such as uncertainty about shifting professional roles or discomfort with rapid technological change, and facilitate a safe space for dialogue. Knowing Strengths and Weaknesses: Reinforce the unique, human-centric value of the librarian: critical thinking, contextualising information, ethical judgment, and deep disciplinary knowledge, skills that AI cannot replicate. The AI could be seen as a means to automate lower-level tasks, allowing librarians to focus on high-value consultation. Developing Confidence: Implement hands-on, low-stakes practice sessions using real-world research scenarios. Confidence grows from successful interaction, not just theoretical knowledge. Encourage experimentation and a "fail-forward" mentality. Ethical: Acting Ethically as a Digital Citizen Ethical use is the cornerstone of responsible AI adoption in academia. Librarians must be the primary educators on responsible usage. Transparency and Disclosure: Discuss the importance of transparency when utilizing AI. Review institutional and journal guidelines that may require students and faculty to disclose how and when AI was used in their work, and offer guidance on how to properly cite these tools. Data Privacy and Security: Review the potential risks associated with uploading unpublished, proprietary, or personally identifiable information (PII) to public AI services. Establish and enforce clear library policies on what data should never be shared with external tools. Copyright and Intellectual Property (IP): Discuss the murky legal landscape of AI-generated content and IP. Emphasise that AI models are often trained on copyrighted material and that users are responsible for ensuring their outputs do not infringe on existing copyrights. Advocate for using library-licensed, trusted-source AI tools whenever possible. Combating Misinformation: Position the librarian as the essential arbiter against the spread of AI-generated misinformation. Training should include spotting common AI red flags, teaching users how to think sceptically, and promoting the library’s curated, authoritative resources as the gold standard. .wp-block-image img { max-width: 65% !important; margin-left: auto !important; margin-right: auto !important; }
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom