Goal
The current project aims to create a linked-data interface that allows users to query a database of scientific publications in order to get detailed metadata concerning publication patterns . Through the interface, it is particularly aimed to allow a data-driven investigation of interdisciplinary collaboration patterns. Some research questions, alongside other possible exploratory ones that may arise in future, are as following:
- Are there any collaboration patterns that are biased towards a certain disciplines? For instance, when medical researchers and computer scientists collaborate on research projects, do they tend to publish their research on journals that belong to one of their respective disciplines (i.e., a medical journal versus a computer science journal)?
- Does interdisciplinarity of a research project affect its impact (e.g., as measured with number of outgoing citations)?
- Are there fields of research that seem to yield higher-impact results when they collaborate?
- Does being an interdisciplinary researcher lead to more publications?
- Are there any publication patterns that can explain researcher career trajectories. For instance, do variables such as interdisciplinarity of an author's lifetime research, number of overall collaborations with other researchers (i.e., network size), and other similar variables affect career-related variables of researchers, such as influence (e.g., as measured by number of citation) or tenure attainment?
The project is part of the 10-month research project 'Knowledge Flows in Interdisciplinary Research' \citep{institute}, and as the investigation progresses over the next few months, the current linked-data interface is expected to shed light to these research questions, and also motivate new ones.
Methodology
In order to explore the effects of interdisciplinarity and discover scientific collaboration patterns, we aim to model the domain of of scientific publications using an ontology, and populate it using a bibliometric databases such as Elsevier's Pure \cite{pure}, RISIS \cite{20172017}, and Web Of Science \cite{analytics2017}.
After being parsed and integrated with an ontology, this data will be made available in a triple store, which will be connected to a linked data query engine and & interface, Linked Data Reactor (LD-R) \cite{besselaar2017}. Once this final stage is reached, the first prototype of the app will be considered completed.
Users
The intended initial user base for the linked data interface are the researchers involved in the Knowledge Flows in Interdisciplinary Research project: Dr. Ali Khalili, Dr. Sascha Friesike, Prof. Peter van den Besselaar; and Academy Assistants Frederik König and John Can Lokman. As this research trajectory continues in the following years, more researchers and students who are involved in proceeding —or similar— projects in both Vrije Universiteit Amsterdam and other universities can be expected to join the user base.
Design