The Research Space: using the career paths of scholars to predict the evolution of the research output of individuals, institutions, and nations

In recent years scholars have built maps of science by connecting the academic fields that cite each other, are cited together, or that cite a similar literature. But since scholars cannot always publish in the fields they cite, or that cite them, these science maps are only rough proxies for the potential of a scholar, organization, or country, to enter a new academic field. Here we use a large dataset of scholarly publications disambiguated at the individual level to create a map of science-or research space-where links connect pairs of fields based on the probability that an individual has published in both of them. We find that the research space is a significantly more accurate predictor of the fields that individuals and organizations will enter in the future than citation based science maps. At the country level, however, the research space and citations based science maps are equally accurate. These findings show that data on career trajectories-the set of fields that individuals have previously published in-provide more accurate predictors of future research output for more focalized units-such as individuals or organizations-than citation based science maps

Avoiding obscure topics and generalising findings produces higher impact research

Much academic research is never cited and may be rarely read, indicating wasted effort from the authors, referees and publishers. One reason that an article could be ignored is that its topic is, or appears to be, too obscure to be of wide interest, even if excellent scholarship produced it. This paper reports a word frequency analysis of 874,411 English article titles from 18 different Scopus natural, formal, life and health sciences categories 2009-2015 to assess the likelihood that research on obscure (rarely researched) topics is less cited. In all categories examined, unusual words in article titles associate with below average citation impact research. Thus, researchers considering obscure topics may wish to reconsider, generalise their study, or to choose a title that reflects the wider lessons that can be drawn. Authors should also consider including multiple concepts and purposes within their titles in order to attract a wider audience

Large-Scale Analysis of the Accuracy of the Journal Classification Systems of Web of Science and Scopus

Journal classification systems play an important role in bibliometric analyses. The two most important bibliographic databases, Web of Science and Scopus, each provide a journal classification system. However, no study has systematically investigated the accuracy of these classification systems. To examine and compare the accuracy of journal classification systems, we define two criteria on the basis of direct citation relations between journals and categories. We use Criterion I to select journals that have weak connections with their assigned categories, and we use Criterion II to identify journals that are not assigned to categories with which they have strong connections. If a journal satisfies either of the two criteria, we conclude that its assignment to categories may be questionable. Accordingly, we identify all journals with questionable classifications in Web of Science and Scopus. Furthermore, we perform a more in-depth analysis for the field of Library and Information Science to assess whether our proposed criteria are appropriate and whether they yield meaningful results. It turns out that according to our citation-based criteria Web of Science performs significantly better than Scopus in terms of the accuracy of its journal classification system

The green view dataset for the capital of Finland, Helsinki

Recent studies have incorporated human perspective methods like making use of street view images and measuring green view in addition to more traditional ways of mapping city greenery [1]. Green view describes the relative amount of green vegetation visible at street level and is often measured with the green view index (GVI), which describes the percentage of green vegetation in a street view image or images of a certain location [2]. The green view dataset of Helsinki was created as part of the master's thesis of Akseli Toikka at the University of Helsinki [3]. We calculated the GVI values for a set of locations on the streets of Helsinki using Google Street View (GSV) 360° panorama images from summer months (May through September) between 2009 and 2017. From the available images, a total of 94 454 matched the selection criteria. These were downloaded using the Google application programming interface (API). We calculated the GVI values from the panoramas based on the spectral characteristics of green vegetation in RGB images. The result was a set of points along the street network with GVI values. By combining the point data with the street network data of the area, we generated a dataset for GVI values along the street centre lines. Streets with GVI points within a threshold distance of 30 meters were given the average of the GVI values of the points. For the streets with no points in the vicinity (∼67%), the land cover data from the area was used to estimate the GVI, as suggested in the thesis [3]. The point and street-wise data are stored in georeferenced tables that can be utilized for further analyses with geographical information systems.Peer reviewe

S&T Publications Output of India: A Scientometric Analyses of Publications Output, 1996-2011

The study analyses India’s performance in science and technology (S&T), using publications data and different quantitative and qualitative measures. Its focuses on India’s global publication share, growth rate, citation quality, international collaborative publications share, its publication share and distribution in various broad and narrow subjects using 15 years data from the Scopus international multidisciplinary database. The study suggests the need to increase the pace of Indian scientific research and also improve its quality compared with other developed and developing countries. It also suggests the need for India to build up its scientific capacity, competence and knowledge base to help bridging the scientific and technological gap with leading countries