Publications are of high value in the academic field and contribute to the visibility of a scientist's research. Researchers have various options to draw attention to their research and related publications, such as selecting a journal that is widely recognized in the scientific community, publishing in open access, using academic networks or scientific blogs and publishing research data in a (subject specific) repository. Furthermore, universities are also interested in the findability and visibility of the institution's research output.
The visibility of a publication is often associated with a specific publication channel. Therefore, journal-related indicators such as the Journal Impact Factor, the CiteScore or the SCImago Journal Rank Indicator (see Journal Impact) are sometimes also considered when selecting a suitable journal for publishing. Additionally, it is important that publications are discoverable – a crucial aspect from the searcher's point of view considering the amount of information available, dissemination via various media channels and different search options in the digital era. Findability also plays an essential role for research data: "Findability" is one of the four FAIR principles for handling and publishing research data (FAIR Guiding Principles = Findable, Accessible, Interoperable, Reusable, see Wilkinson et al., 2016).
Academic Search Engine Optimization (ASEO) focuses on the findability of scientific publications.
Academic Search Engine Optimization (ASEO)
What is ASEO and what is not?
ASEO includes measures to facilitate the findability of scientific publications in discovery systems and thus improve their visibility.
The aim of ASEO is to improve the identification of relevant documents for a specific search query in discovery systems such as library catalogues, scientific literature databases or search engines like Google Scholar. This can be supported by various measures: Putting yourself into the perspective of the searching person, choosing a suitable title, selecting meaningful author keywords, optimizing the abstract and providing comprehensive metadata, which are evaluated in search systems.
ASEO does not aim to achieve better ranking results by manipulating these search systems. Optimization approaches must only be performed within the framework of good scientific practice and ethical guidelines and must not compromise scientific integrity in any way.
The aim of ASEO is to improve the identification of relevant documents for a specific search query in discovery systems such as library catalogues, scientific literature databases or search engines like Google Scholar. This can be supported by various measures: Putting yourself into the perspective of the searching person, choosing a suitable title, selecting meaningful author keywords, optimizing the abstract and providing comprehensive metadata, which are evaluated in search systems.
ASEO does not aim to achieve better ranking results by manipulating these search systems. Optimization approaches must only be performed within the framework of good scientific practice and ethical guidelines and must not compromise scientific integrity in any way.
Where are elements of ASEO applied?
- Journals and Publishers
The findability of publications appearing in their journals is also relevant for publishers, as better findability and visibility of publications can lead to a better reception of their journals in the scientific community. This, in turn, can impact journals metrics via citation numbers and thus contribute to the visibility and reputation of the publisher's journal portfolio. The Journal Historical Social Research (HSR) for example, published by GESIS, Leibniz Institute for the Social Sciences in Cologne, offers tips on Academic Search Engine Optimization (ASEO) for authors. - Projects in context of the United Nations Sustainable Development Goals (SDGs)
Dimensions
The comprehensive database for searching research output classifies publications based on research associated with the 17 SDGs. For the automated mapping of publications to the corresponding SDGs, Dimensions uses supervised machine learning based on curated keyword searches and training datasets.
SDG Keywords Dictionary Project
The SDG Keywords Dictionary Project at the University of Auckland (New Zealand) deals with the identification of research related to the SDGs. Based on work by Elsevier, the Sustainable Development Solutions Network (SDSN) and the UN, the project has created a list of SDG-related keywords from Scopus (Elsevier). Aim of the project is to identify SDG-related research output and to support researchers in making their contribution to the SDGs more visible. A first version (V 1.1.) of the keyword list is available on the project website.
THE Impact Ranking
The THE Impact Ranking measures the success of universities in implementing the SDGs. One category for the evaluation are research metrics based on data supplied by Scopus (Elsevier). Based on SDG associated keywords/key phrases, Elsevier has developed search queries to identify research output related to the 17 SDGs in the Scopus database (see SDG Initiative Scival Elsevier). Additional SDG-related publications were identified using machine learning techniques and added to the dataset (short overview on methodology 2023; the datasets containing the search queries and keywords/key phrases for SDG mapping 2021 are available via DOI: 10.17632/9sxdykm8s4.4 and for 2022 via DOI: 10.17632/6bjy52jkm9.1).
QS World University Rankings: Sustainability
The QS World University Ranking: Sustainability 2023, which analyses the social and environmental sustainability of institutions, also uses the Elsevier 2022 SDG mapping approach to determine research output and impact.
(QS World University Rankings: Methodology SDG)
Where to find more information?
- Jöran Beel, Bela Gipp, Erik Wilde: Academic Search Engine Optimization (ASEO). Optimizing Scholarly Literature for Google Scholar & Co. In: Journal of Scholarly Publishing 41, No. 2 (2010), p. 176-190. DOI: 10.3138/jsp.41.2.176,
- Lisa Schilhahn: Sichtbarkeit und Auffindbarkeit wissenschaftlicher Publikationen. In: Karin Lackner, Lisa Schil-hahn, Christian Kaier (Eds.): Publikationsberatung an Universitäten. Ein Praxisleitfaden zum Aufbau publikationsunterstützender Services. Bielefeld 2020, p. 237-258. DOI: 10.14361/9783839450727-013
Please contact us if you have any questions:
Merle-Marie.Schuette@uni-bayreuth.de