Publishers of journals that do not offer open access argue that the costs of producing journals needs to be met by charging for the journal (and such journals do not typically require researchers to pay for the right to publish). On the other hand, it is argued that open access enables the commercialization of the results of scientific research by increasing the visibility of the work.
Consequently, this encourages an exchange of ideas and experience within the scientific community, both academic and commercial. It can also be reasoned that progress in research benefits from the sharing of results and collaboration. Open access is not straightforward and there are different types of open access.
Different forms of open access are often color coded, for example ‘gold open access’ is one based on an ‘author pays’ model. In return, the publisher makes all articles and related content available for free immediately on the journal’s website. Green open access refers to a system whereby self-archiving by authors is permitted, which is undertaken independently from publication by a publisher. Bronze open access is where articles are free to read on the publisher page, but they cannot be downloaded or stored in any format.
Researchers take different views on the subject of open access; one issue that some researchers aim to keep in mind is the journal’s Impact Factor (which is calculated through things like journal citations). It is often the paid for journals that carry the highest Impact Factors. For example, Nature (which has a paywall) has an impact factor of 42 whereas Public Library of Science, which is free to access, has an impact factor of 3.5. In parts of academia, only journals with an Impact Factor of 5 and above are considered ‘worthy’.
FAIR data?
In scientific research there is a body of movement that maintains that it is important that clear and unambiguous rules are established in terms of data sharing. A commonly accepted framework in life sciences is the FAIR framework, which was established primarily as more data became available about the human genome. In terms of what these elements of FAIR mean:
Findability: Datasets should be described, identified, and registered or indexed in a clear and unequivocal manner.
Accessibility: Datasets should be accessible through a clearly defined access procedure, ideally using automated means. Metadata should always remain accessible (metadata is an umbrella term for information and attributes applying to datasets and the data contained therein; this is sometimes abbreviated to ‘data about data’).
Interoperability: Data and metadata are conceptualized, expressed, and structured using common, published standards.
Reusability: Characteristics of data and their provenance are described in detail according to domain- relevant community standards, with clear and accessible conditions for use.
The FAIR principles establish preconditions for data sharing, urging researchers to take the possibility of subsequent data sharing and reuse into account from the outset and this is a worthwhile venture to support.
Looking to the digital future
In time it is likely that open access will become the norm. We live in an increasingly digitalized world and one the grows ever-more Internet-centric. This has created waves in the way we communicate, connect, share, and do collaborate with each other. This trajectory will continue to affect scientific research and associated academic publishing.
