Page 162 - JOURNAL OF LIBRARY SCIENCE IN CHINA 2018 Vol. 43

162
162 Journal of Library Science in China, Vol.9, 2017

Scientific data sharing governance: Model selection and scenario analysis

〇a*
ZHANG Lili〇
The rough road of data sharing well needs pattern-matching sharing models and operating
mechanisms. Based on the current state of scientific data sharing in big data era, this paper applies
compound methods of literature review, theoretical transplantation, and scenario analysis. The
progress of scientific data sharing model study has been summarized and research limitations have
been pointed out. Furthermore, reanalysis from the view of new institutional economics has been
suggested and the design of model abstraction combining with real case scenario analysis has been
proposed.
For literature review, summarization is carried out by a micro-level perspective regarding
research data themselves, a meso-level view focusing on operating organizations together with
macro-level insights into institution. Then research data sharing activities and sharing models have
been described and models in some specific disciplines as well as in other information resources
fields have also been mentioned.
Moreover, theories of new institutional economics have been introduced. Judging from the data
asset specificity and data trading frequency, different research data sharing activities tend to select
different organizational forms. Concerning those preferred organizational arrangements, there are
mainly five kinds of data sharing models, including intra-organization level data sharing model,
controlled data sharing model, intermediate-organization level data sharing model, individual data
exchange model, and free market data sharing model.
Upon the abstraction of five logical models, scenario analysis represents with mainstream data
sharing cases including data resources pool model, data publishing model and data market model.
Following the guidance of supply-demand chain within data sharing models, stakeholders and
their interactions tracing the data flow are reviewed. Meanwhile, comparisons about advantages,
disadvantages, opportunities and challenges within the three mainstream sharing models for open
data are fully analyzed and the prospect for the future development is also discussed.
Finally, we find out that data resources pool model is the most important way for scientific
data sharing and its predominance will prevail for quite a long time in the future. However, due
to the externality source of incentives and top-down pattern of data sharing path, data resources
pool model can’t help the data suppliers exert their subjective initiative to the utmost. Therefore,
the cost for supervision and evaluation of such model is high. Besides, the data publishing model
successfully facilitates the work of data sharing and helps data suppliers gain their scholarly
reputations as well. However, data publishing model still needs further development in many
aspects, such as the establishment of scholarly reputation and acknowledgement, sustainability of
business model, balance of open data and copyrights protection and etc. In a way, data publishing

* Correspondence should be addressed to ZHANG Lili, Email: zhll@cnic.cn, ORCID: 0000-0003-1847-6683