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Being able to replicate research results is the hallmark of science. Replication of research findings using computational models should, in principle, be possible. In this manuscript, we assess code sharing and model documentation practices of 7500 publications about individual-based and agent-based models. The code availability increased over the years, up to 18% in 2018.
Model documentation does not include all the elements that could improve the transparency of the models, such as mathematical equations, flow charts, and pseudocode. We find that articles with equations and flow charts being cited more among other model papers, probably because the model documentation is more transparent.
The practices of code sharing improve slowly over time, partly due to the emergence of more public repositories and archives, and code availability requirements by journals and sponsors. However, a significant change in norms and habits need to happen before computational modeling becomes a reproducible science.
To evaluate the concern over the reproducibility of computational science, we reviewed 2367 journal articles on agent-based models published between 1990 and 2014 and documented the public availability of source code. The percentage of publications that make the model code available is about 10%. The percentages are similar for publications that are reportedly dependent on public funding. There are big differences among journals in the public availability of model code and software used. This suggests that the varying social norms and practical convenience around sharing code may explain some of the differences among different sectors of the scientific community.
While research-article impact is routinely judged by citation counts, there is recognition that a much broader view is needed to better judge the true value of citations. This paper applies a developing framework based on the application of network theory, where the network consists of journal articles on arid-systems research which are listed on ISI Web-of-Science. Keywords were used to identify articles related to arid-systems research. Linkages between articles were defined by citations, and we bound our analysis by focusing on how the Australian subsample contributes to the international arid-systems literature. The analysis showed that impact based on how articles contribute structurally to the flow of knowledge within the literature offers an alternative metric to citation counts. The analysis also presented a partitioned view of the Australian arid literature. This showed that there exists some citation-based structure within the literature, and we showed this structure better describes the literature than a partition based on which journal articles are published in.
Keywords: Bibliometrics; Dryland; Graph theory; Rangeland; Semiarid
In Janssen et al. (2006), we presented a bibliometric analysis of the resilience, vulnerability, and adaptation knowledge domains within the research activities on human dimensions of global environmental change. We have updated the analysis because 2 years have gone by since the original analysis, and 1113 more publications can now be added to the database. We analyzed how the resulting 3399 publications between 1967 and 2007 are related in terms of co-authorship and citations. The rapid increase in the number of publications in the three knowledge domains continued over the last 2 years, and we still see an overlap between the knowledge domains. We were also able to identify the “hot” publications of the last 2 years.
Keywords: adaptation; bibliometric analysis; citations; resilience; vulnerability
This paper presents the results of a bibliometric analysis of the knowledge domains resilience, vulnerability and adaptation within the research activities on human dimensions of global environmental change. We analyzed how 2286 publications between 1967 and 2005 are related in terms of co-authorship relations, and citation relations.
The number of publications in the three knowledge domains increased rapidly between 1995 and 2005. However, the resilience knowledge domain is only weakly connected with the other two domains in terms of co-authorships and citations. The resilience knowledge domain has a background in ecology and mathematics with a focus on theoretical models, while the vulnerability and adaptation knowledge domains have a background in geography and natural hazards research with a focus on case studies and climate change research. There is an increasing number of cross citations and papers classified in multiple knowledge domains. This seems to indicate an increasing integration of the different knowledge domains.
Keywords: Knowledge domains; Co-authorship networks; Resilience; Vulnerability; Adaptation; Citations; Publications