Dataset and analysis of editorial board composition of 165 Hindawi journals indexed and abstracted in PubMed based on affiliations

This article explores the editorial board composition (across the six continents) of Hindawi journals indexed in PubMed. The dataset used is the official affiliation of the board members available at the various webpages of Hindawi journal website and not the countries of origin of the editorial board members. Summary statistics were presented and the raw dataset was provided for further analysis by interested scholars. The percentage of the editorial board composition across the continents was presented, the dataset of Hindawi journals indexed in both Hindawi and Scopus were also presented and measured in terms of Citescore and percentiles. The dataset can be used in journal evaluation, auditing, bibliometric analysis, management of smart campus; ranking and the analysis can be extended to other journal indexations.


a b s t r a c t
This article explores the editorial board composition (across the six continents) of Hindawi journals indexed in PubMed. The dataset used is the official affiliation of the board members available at the various webpages of Hindawi journal website and not the countries of origin of the editorial board members. Summary statistics were presented and the raw dataset was provided for further analysis by interested scholars. The percentage of the editorial board composition across the continents was presented, the dataset of Hindawi journals indexed in both Hindawi and Scopus were also presented and measured in terms of Citescore and percentiles. The dataset can be used in journal evaluation, auditing, bibliometric analysis, management of smart campus; ranking and the analysis can be extended to other journal indexations. &

Value of the data
The dataset could be helpful in the evaluation of the impact of journal indexing on medical and other scientific publications.
The data analysis can be extended to other reputable publishers. The dataset can be helpful in research output evaluation and auditing and in bibliometric analysis. The dataset can provide insight on the research volume of different continents and as such can be a criterion for ranking of journals and management of smart campuses.
The research can be extended to include gender, population, education and development level gaps.
The data analysis can be extended to capture the distribution of citations from the six continents and how it affects the editorial composition, manuscript acceptance and rejection.

Data
The dataset provided in this research relates to the editorial board composition of 165 Hindawi journals indexed in PubMed. It involves the official stated affiliations of the editorial board members grouped according to the continents namely; North America (NAM), Europe (EURO), Asia (ASIA), South America (SAM), Australia (AUST) and Africa (AFR). The grouping into continents was necessary because the data is large and highly skewed (some countries are not represented in the editorial board composition at all). The dataset was explored and the detailed summary is shown in Table 1. Also presented in this article are the impact of the journals indexed in both Scopus and PubMed measured in terms of their Citescore and percentiles.
The raw dataset can be assessed as Supplementary data 1.
PubMed is a citation and abstract database and digital repository that archives and manages scholarly peer reviewed articles in the medical, biological, life and biochemical sciences. It is a bibliographic search engine used to access the Medical Literature Analysis and Retrieval System Online (MEDLINE). PubMed was released in 1996 and currently managed by the National Institute of Health (NIH) of the United States. It is closely related to PubMed Central managed by the National Center for Biotechnology Information (NCBI).
On the average, the editorial board composition across the continents can be interpreted using the inequality AFR o SAM o AUST o ASIA o NAM o EURO. Almost all Hindawi journals indexed in PubMed does not have editorial board members with affiliations in Africa, South America and Australia. The large variance for NAM, EURO and ASIA implies large deviation of the observations from the mean and consequently a high possibility that the editorial board composition may rise or fall below the mean. The high positive values of the skewness suggest that the data is highly right skewed; that is, there is high probability of observing low values. This is because there is uneven editorial composition across the 165 journals. It can also be seen that the high positive values of the Kurtosis implies that the probability of obtaining extreme values or values outside the range is high. All the journals have at least an editor whose affiliation is Europe or North America. Coefficient of variation can also be used to further explain the data.
The percentage of editorial board composition across the continents is presented in Table 2.

Experimental design, materials and methods
The dataset is freely available at the various webpages of the publisher's website. The affiliations of the editorial board members were copied to Microsoft Excel, the countries of affiliations were matched with United Nations list of approved countries [1] and consequently classified according to their respective continents. Thereafter, statistical analyses were performed on the dataset.
The detailed statistical analysis of similar dataset can be found in . Chi-square test of goodness of fit was performed and shown in Table 3.
The p-values indicated that the observed values differ greatly from the expected. This is to check if the expected number of editorial board composition is equivalent to the observed values. This is a kind of quality assurance.
Some of the journals are indexed in both PubMed and Scopus. In order to explore the relationship between the two indexations, the performance of the journals was explored using the Citescore and percentiles (performance metrics exclusive to Scopus). The journals indexed in Scopus without a Citescore and percentile were excluded and marked as missing values. The summary is shown in Table 4.