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1. JIE ZHOU on 12 de June de 2026 at 09:12

   CommeMy Journey into Open Science

   The several-week course An Introduction to Open Science has now come to a successful end. For me, this is not merely the conclusion of a general education course, but a valuable opportunity to re-examine the essence of academic research and reshape my mindset as a doctoral student majoring in Library and Information Science. I am truly honoured to participate in this programme, and I would like to express my gratitude to all teachers and fellow students for the fruitful exchanges and discussions throughout the sessions. As a learner from China and also a university lecturer, my understanding of academic research has deepened considerably during this course.

   Coincidentally, while the course was ongoing, an incident in China sparked heated discussions across academic circles and public opinion: a student from Jilin University filed a public complaint against an academician’s team over research data fraud and irregularities in data processing. This is not an isolated case; it lays bare the widespread flaws in the current global research evaluation system. Nowadays, numerous universities and research institutions still take publication volume, journal rankings and impact factors as the core criteria to assess researchers’ competence and determine their career prospects. Under the paper-centric evaluation culture, many early-career researchers are forced to prioritise final publication results, leaving them little time to delve deeply into their research. The exploratory essence of academic work has gradually been overshadowed. This incident prompted me to reflect: how can we return to the true nature of research and establish a standardised academic order? It was with this question in mind that I embarked on the in-depth study of Open Science.

   Before taking this course, my understanding of Open Science was rather one-sided. I simply equated Open Science with Open Access (OA), believing that its sole purpose was to break down journal paywalls and make academic papers freely accessible to the public. Influenced by the traditional academic environment, I took it for granted that high-impact journal publications were mandatory requirements for academic assessments and professional title evaluations. I even mistakenly thought that the sharing philosophy of Open Science would conflict with the traditional journal-based evaluation system. At that time, I failed to realise that Open Science covers far more than just published articles. Research data, experimental codes, research workflows, academic evaluation and citizen science all fall within its scope. As a researcher focusing on user information behaviour, I initially regarded Open Science merely as a trending topic and did not explore its profound connections with my own research field.

   This course completely changed my preconceptions. We systematically learned core theories including UNESCO’s Eight Open Pillars of Open Science, the FAIR principles for research data, the European Open Science Cloud (EOS), a full range of OpenAIRE services, as well as persistent identifiers such as DOI and ORCID. Meanwhile, we completed a series of hands-on practices: drafting Data Management Plans (DMP), building research projects on the Open Science Framework (OSF), archiving research outputs on Zenodo, carrying out sensitive data anonymisation, sorting out open access guidelines, and reusing metadata from OpenAlex and OpenAIRE.

   Two parts of the curriculum impressed me the most. The first was the discussion on the Coalition for Advancing Research Assessment (CoARA) and research assessment reform. We analysed the drawbacks of over-reliance on impact factors, and recognised that the value of research cannot be judged solely by the number of publications or journal tiers. Research reproducibility, social impact and interdisciplinary collaboration are equally important criteria for evaluating academic achievements.

   The second was the discussion on the boundaries of data sharing. The core maxim — as open as possible, as closed as necessary — taught me to strike a balance between data sharing, privacy protection, intellectual property rights and patent interests. These theories and practical skills are no longer abstract textbook knowledge, but practical tools that can be applied to real research work.

   This learning experience has thoroughly transformed my views on academic publishing, data management and even my entire academic career. I used to believe that a single journal article represented the entirety of a research project, while raw data, analytical codes and experimental records were just supplementary attachments. Now I fully understand that research data, open-source tools and complete experimental workflows are all core academic outputs. Complying with the FAIR principles to standardise data management is the foundation of ensuring research reproducibility and upholding academic integrity. When it comes to publishing, I no longer blindly pursue high-impact journals, and have started to explore diversified publishing channels.

   My doctoral research focuses on user information behaviour, and I have found a strong intersection between this field and Open Science. The searching habits, resource access patterns and data sharing willingness of users on platforms like OpenAIRE, OSF and Zenodo are typical research objects for user information behaviour studies. The development of Open Science relies heavily on the support of Library and Information Science. In turn, my empirical research can help optimise open science platforms and improve public academic services. The two fields reinforce and empower each other.
   Nevertheless, I am clearly aware that Open Science still faces many practical challenges across the global academic community, and such difficulties are shared by scholars both in Europe and China. First of all, there is an inherent conflict between evaluation systems. Major European research funding bodies and universities, as well as domestic research institutions, still adopt journal-based metrics as core assessment criteria. Even though we embrace the philosophy of Open Science, we are constrained by academic and career pressures, resulting in a situation where we agree with the ideas but face limitations in practice.

   Secondly, data management poses practical challenges. I frequently reuse public metadata from OpenAlex and OpenAIRE in my research, and I also come into contact with datasets involving personal privacy and commercial confidentiality. How to realise open sharing in compliance with regulations while protecting intellectual property and avoiding patent risks is a common problem for all researchers.
   Thirdly, Open Science has relatively high barriers to adoption. Its functional platforms are complex to use, and researchers have long been accustomed to closed research models. Therefore, awareness of data sharing and transparent research practices still needs to be improved worldwide.
   Reflecting on the current academic environment, I have gained a deeper understanding of the essence of research. The original mission of academic research is to explore truth, solve practical problems and drive social progress — it should never be conducted merely for the sake of publishing papers. Nowadays, generative artificial intelligence is widely used, and some people take advantage of it to churn out large numbers of low-quality articles, which exacerbates academic bubbles and dilutes the true value of research. In this context, Open Science serves as an effective solution. The FAIR principles require full transparency and traceability of data, and research workflows are fully documented, which technically and institutionally restrict data fraud and academic irregularities. Furthermore, Open Science advocates a diversified research evaluation system. Even a research idea, an academic discussion or a set of experimental methods deserves to be disseminated and valued. It guides the academic community to move beyond the obsession with final results and fully demonstrate the multi-dimensional value of research.

   Combining what I have learned from the course with my work and research, I have formulated a set of phased implementation plans for Open Science: 1. Standardise the use of persistent research identifiers. I will register ORCID for myself and assign DOIs to all research outputs to ensure the traceability of my academic identity and achievements. 2. Comply with relevant requirements to write formal Data Management Plans. I will classify research data and conduct data anonymisation, and archive datasets and analytical codes on Zenodo or OSF within the scope of compliance. 3. Prioritise open access channels for academic publications, and standardise the citation of third-party metadata and datasets. 4. Incorporate user behaviour on open science platforms into my doctoral empirical research, so as to provide references for platform optimisation.

   Finally, based on my major in user information behaviour, I would like to share an in-depth insight: every human information behaviour is driven by internal motivation. A willingness to share and a spirit of collaboration are the most essential personal qualities for practising Open Science. Open Science is far more than a set of tools and rules; it represents a brand-new research culture. It calls on researchers to abandon the mindset of working in isolation, and actively share research data, academic ideas and phased findings. From the perspective of information behaviour research, fostering the willingness to share and the awareness of collaboration is the first step to make Open Science take root. Only when researchers genuinely aspire to communicate and share can a sound open research ecosystem be built.

   Open Science is not a passing academic trend, but an inevitable direction for global research in the future. It will not replace traditional journal publishing; instead, it acts as a powerful complement to build a more transparent, fair and robust academic ecosystem. This journey has turned me from an onlooker into an advocate, practitioner and researcher of Open Science. In the years ahead, I will keep practising Open Science in my doctoral studies and university teaching, and confront existing contradictions and challenges with a steadfast commitment to the original aspiration of academic research. I also hope to leverage my professional strengths in Library and Information Science to contribute to the popularisation of Open Science and the improvement of the academic atmosphere.nt *