Are HKU Researchers Sharing Research Data Openly?
— by Fanny Liu
Introduction
Publishing research data in open access is a global trend to accelerate science progress and enhance integrity by enabling others to verify research findings. Researchers can enjoy higher visibility of the research findings associated with the shared data. Many journals also mandate data sharing as a condition of publication.
For tips on sharing research data as open as possible, as closed as necessary, check out: Balancing Openness and Privacy in Research Data Sharing
Using OpenAlex records, the situation of open data by the University of Hong Kong (HKU) authors can be analysed. Data includes only dataset (work type) linked to HKU-affiliated authors published from 2021 to 2025. The date of data retrieval is 28 August 2026.
Open or Closed
Among the 6,169 records meeting the criteria, 99.79% is open access while 0.21% is closed.
However, this should not be interpreted as showing that nearly all datasets produced by the institution are openly shared. OpenAlex can only identify datasets that are recorded in the scholarly sources it indexes. Datasets created or used within research projects but not deposited in a repository will not appear in the OpenAlex results.
In addition, an open licence does not necessarily mean immediate access. A dataset may be assigned an open licence but remain unavailable during a temporary, or even permanent, embargo period.
Licence
Among the 4084 datasets with an open access licence recorded, the majority are under CC BY licence (54.73%) and CC BY-NC licence (36.56%). While most of the open access datasets are under Creative Commons licences, a notable number (3.67%) are in public domain (CC0), which means the authors pose no restrictions on re-use.
Figure 1 Licences of open access datasets
For tips on selecting a suitable licence, check out: Access, Author Rights, and Agreements 1: Which Creative Commons License Works the Best for an Author?
Repository
Among the 6156 open access datasets by HKU authors with a location recorded, most of them are deposited in Figshare (54.37%), HKU DataHub (28.78%) and Zenodo (CERN European Organization for Nuclear Research) (8.37%).
For tips on selecting a suitable repository, check out: Selecting a Repository for Data Sharing
Most cited
Among the open access datasets, those related to medicine, environmental sciences, and social sciences received the highest citations. The five most cited datasets are shown in table 1.
However, datasets are sometimes re-used without formal citation. Researchers may acknowledge a dataset in the text of the main body, supplementary materials, or data availability statements without citing dataset record.
| DOI | Title | Publication year | Citation count |
| https://doi.org/10.5281/zenodo.5525846 | Banking on the Confucian Clan: Why China Developed Financial Markets So Late | 2021 | 44 |
| https://doi.org/10.6084/m9.figshare.12853661.v3 | SARS-CoV-2 nsp13, nsp14, nsp15 and orf6 function as potent interferon antagonists | 2021 | 10 |
| https://doi.org/10.5281/zenodo.8048363 | Programming correlated magnetic states with gate-controlled moiré geometry | 2023 | 8 |
| https://doi.org/10.5281/zenodo.4773513 | Quantifying the extent of the Paleo-Asian Ocean during the Late Carboniferous to Early Permian | 2021 | 8 |
| https://doi.org/10.5281/zenodo.5105689 | A 1 km global cropland dataset from 10000 BCE to 2100 CE | 2021 | 7 |
Table 1 Five most cited open access datasets by HKU authors
Topics
Among the datasets in the scope, 2814 are assigned with a primary topic. HKU’s open datasets show a strong representation in health and life sciences. The primary topic fields with highest proportion are Medicine (18.76%), Biochemistry, Genetics and Molecular Biology (16.13%), Agricultural and Biological Sciences (14.07%), and Environmental Science (11.94%).
Compared with the worldwide open dataset distribution, HKU has a higher proportional concentration in several fields:
- Medicine,
- Biochemistry, Genetics and Molecular Biology,
- Agricultural and Biological Sciences,
- Environmental Science,
- Immunology and Microbiology,
- Nursing, and
- Chemical Engineering.
In particular, HKU’s share of Medicine (18.76%) is almost twice that of the worldwide open datasets (10.48%), while Immunology and Microbiology (2.67%) is more than three times the worldwide proportion (0.83%). This suggests that HKU’s contribution to open data is particularly associated with health, biology, and environmental sciences, as compared with worldwide distribution.
Figure 2 Primary topic fields of open data by HKU authors
Figure 3 Open data primary topic fields (ranked) by authors at HKU and worldwide
OpenAlex’s primary topic is a machine-generated label intended to represent the most likely main subject of a work, based on its title, abstract, citations, and journal name. Labels may be inaccurate.
Sustainable Development Goals (SDGs)
The Sustainable Development Goals (SDGs) are the 17 global goals the United Nations adopted in 2015 to address challenges.
In total, 2944 SDG tags are assigned to HKU’s open datasets. Contribution centres on SDG 3: Good Health and Well-being (27.04%), SDG 2: Zero Hunger (12.47%), and SDG 4: Quality Education (10.94%). Together with SDG 15: Life on land, and SDG 14: Life below water, they account for 67.67% of HKU’s contribution through open datasets to SDGs.
HKU’s SDG profile of open datasets differs substantially from the worldwide open datasets. While world activity is overwhelmingly concentrated in SDG 7: Affordable and Clean Energy (77.28%), only 3.36% HKU’s open datasets contribution is relevant to this goal. HKU contribution is much more diversified, led by health, hunger, education, and environmental topics.
Figure 4 Open data contribution to SDGs by HKU authors
Figure 5 Open data contribution to SDGs (ranked) by authors at HKU and worldwide
The SDG classifications are generated automatically by OpenAlex’s Aurora text classifier using only publication titles and abstracts. A designation only indicates textual relevance to an SDG. One dataset can be associated with more than one SDGs.
Conclusion
This analysis identifies 6,169 dataset-type works associated with HKU-affiliated authors between 2021 and 2025. The open access datasets are mainly deposited in Figshare, HKU DataHub, and Zenodo, and under CC BY and CC BY-NC licences. HKU’s profile is particularly strong in medicine, life sciences, and environmental science. Similarly, topics are concentrated in the SDGs of Good Health and Well-being, Zero Hunger, and Quality Education.
These results provide an indicative picture of HKU-associated datasets. Going forward, continued support for HKU DataHub and strengthened data-sharing in comparatively less-represented disciplines will help make research data more findable, accessible, and reusable.
Extended Readings
- Balancing Openness and Privacy in Research Data Sharing
- Access, Author Rights, and Agreements 1: Which Creative Commons License Works the Best for an Author?
- Selecting a Repository for Data Sharing
Declaration of Generative AI Use
I acknowledge the use of Generative AI tools in writing this post.
I used:
- GPT-5.6 Terra to assist with brainstorming, data analysis, and language refinement.
I declare that I reviewed and edited the contents as needed, and take full responsibility for the contents of the post; And the information provided is complete and accurate.
