On 6 and 7 October 2026, I attended two DBpia webinars. The first was “First Steps in Understanding Papers for Students Unfamiliar with Academic Literature”, followed by “The Most Reliable Way to Find Papers: A Guide to Using DBpia”. The webinars moved from understanding how a paper is organised to finding and managing the literature I need.
The September library workshop covered research questions and prior-research searches, while the Elsevier webinar explored manuscript preparation and peer review. These webinars addressed the work I will repeat between those stages: reading one paper and finding the next.
Read the claim alongside its evidence
The first presentation began with the importance of checking sources when collecting information. A paper shows what a researcher wanted to find out, how they investigated it and how they explain the results. Reading it means following that process as well as taking note of the conclusion.
The presentation presented research methods, data and peer review as foundations for confidence in a paper. When using a study in my own research, I want to examine its subjects, conditions, methods and limitations together. In security and AI research, the data and evaluation conditions behind a result are particularly relevant.
It also distinguished journal articles from theses. Journal articles report research through academic journals and similar venues; theses present research submitted towards a degree. Understanding that distinction can help me choose a source with the depth of explanation and research context I need.
What to look for in each part
The role of each part of a paper is one point I want to revisit from the first presentation. The presentation introduced a way of reading that establishes the overall question and result before returning to difficult passages, rather than stopping at every unfamiliar sentence or statistical symbol.
| Part of the paper | What to look for |
|---|---|
| Abstract and keywords | Topic, subjects, outline of the method and main findings |
| Introduction and rationale | The problem, why the study is needed and what it asks |
| Theoretical background | Definitions of central concepts and the prior work supporting them |
| Methods | Subjects and conditions, data collection and analysis |
| Results | Answers to the research questions, supported by tables, figures and values |
| Discussion, conclusions and recommendations | Meaning, scope, limitations and further work |
| References | Sources cited in the text and candidates for further reading |
The abstract provides a first view of the question and findings. An unfamiliar concept can lead me back to the theoretical background; the discussion and conclusion can help make sense of a difficult result. I can use this approach to find my way into a paper, then return to its research conditions and analysis before citing a result or applying a method.
In the introduction, I want to follow the connection between the current situation, the problem, the need for research and the research questions. In the results, I can check whether those questions were answered; in the conclusion, I can examine the scope of those answers. Reading these connections should also help me check that the questions and results in my own manuscript remain aligned.
Follow citations back to the original study
Author names and years, reference numbers and notes connect a passage to its source. The first presentation introduced author–date references, numbered references such as IEEE, and footnotes and endnotes. I will check the required style for a submission, but when reading, my first task is to connect each claim to the material supporting it.
The presentation particularly emphasised finding the original source when a paper quotes a definition from another study. If I use that concept in my own explanation, I need to check its original meaning and scope. If I have not yet read the source, I should not record it as something I have checked directly.
References also provide a starting point for another search. The presentation introduced backward searching through a paper’s references and forward searching for later studies that cite it. This gives me a way to connect the citation tracing covered in the library workshop to reading an individual paper.
Separate search conditions from full-text access
The second day focused on DBpia access and search functions. Institutional authentication and personal account login serve different purposes. The presentation described authentication through a campus network or library website, personal login and app-based authentication. I need to distinguish access rights from personal collections and reading history, and check the available access against my university’s subscriptions and authentication status.
The search guidance covered entering keywords, narrowing results by publication year, material type or journal, and combining conditions in advanced search. AND combines required concepts, OR accommodates alternative or broader expressions, and NOT excludes a concept. I will review results as I adjust exclusions, since they may also remove relevant material.
Filters distinguished theses, journal articles and conference materials. Full-text only helps locate material available to read directly through DBpia. When selecting literature for a research question, I also want to examine results that link to other sites. It helps to distinguish material found in a search from material whose full text I can access immediately.
Organise material so that I can return to it
The presentation continued beyond searching with downloads, My Library, folders, journal subscriptions and new-content alerts. Its examples organised papers by course or semester, concept or topic, and research method or data, depending on the purpose of reading. I would like to begin with topic-based groups and add method and data classifications as they become useful.
When saving a paper, I intend to leave a short note explaining why I need to read it: a definition to check, a method to compare or evaluation conditions to examine. This should help me find the relevant part when I return. I also want to retain the query and filter conditions so that I can revisit the scope of the search.
The presentation also introduced reading the paper as text on its detail page. Full-text AI is produced by recognising the letters in images of the paper’s pages and converting them into text. Full-text XML is built from the publisher’s supplied text data. XML is a data format that distinguishes structures such as paragraphs and sections. The two labels identify the source and process used to produce the displayed text.
In particular, when using text recognised from page images, I need to compare equations, tables, symbols and passages I intend to cite with the original paper.
Which tasks can the AI features support?
Both webinars included DBpia’s AI features. Separating their roles makes it easier to decide which task to use each one for.
| Feature | Use introduced in the webinars |
|---|---|
| AI Idea | Develop topics and outlines from keywords and find candidate references |
| AI Viewer | Read summaries and key concepts, and ask questions about a paper being viewed |
| AI Reader | Summarise or translate an uploaded PDF and ask questions about its contents |
| AI Agent | Ask questions based on academic material and inspect sources linked to the answer |
| DeepResearch | Review a proposed investigation plan before proceeding with research and report generation |
The accuracy indicator beside recommended references deserves careful interpretation. The handout defined it as similarity between an outline and a reference: an indication of topic relevance. I can use it to select reading candidates, then assess the quality of the research and its relevance to my question by reading the paper.
AI Viewer summaries and questions may help me understand the structure of an unfamiliar paper. AI Agent was presented as showing the sources and annotations used in an answer. I still intend to review the titles and abstracts of citation candidates and check the original text to see whether they support the claim I need.
AI Reader was introduced as a way to upload a PDF, summarise or translate it, and read alongside the original. The handout stated a limit of 20MB and 300 pages per file at the time, and warned that scanned PDFs without selectable text might not be recognised. DeepResearch was presented as a Beta feature. I am recording these as conditions described at the time of the webinars and will check them again when using the service.
Both webinars emphasised the importance of finding and reading material independently. For my research, I intend to use AI to shortlist papers or explain unfamiliar concepts, then check methods and results in the original text and write my own account. The next task is to record which question the evidence answers, rather than ending with a saved summary.
What I want to record from the next paper
Together, the webinars connect searching, reading, checking citations and finding further material. I intend to begin with the question and findings in the abstract, then read the methods and limitations of relevant papers. Definitions that need checking and subsequent studies can join the reading list along the way.
For each paper, I would like to record the research question, subjects or data, method, main findings and limitations, and its connection to my own work. Adding these reading criteria to the comparison matrix from the September workshop should help me move from collecting papers to preparing a meaningful comparison.
This Note draws on the two webinars and Nurimedia’s teaching handouts. I have focused on the parts I want to revisit while finding and reading papers, rather than reproducing every feature demonstration.