The Role of Climate in the Collapse of the Maya Civilization: A Bibliometric Analysis of the Scientific Discourse
The Role of Climate in the Collapse of the Maya Civilization: A Bibliometric Analysis of the Scientific Discourse is a dataset published in Climate (2017). On theSindex it has a DataRank of 0.690, placing it in the top 45.5% of the data-sharing corpus. It has been cited 27 times, with 24 citing works in its 1-hop citation network. Its calibrated FAIR score is 27/100.
Abstract
This bibliometric analysis deals with research on the collapse of the Maya civilization—a research topic with a long-lasting history, which has been boosted significantly by recent paleoclimatic research. The study is based on a publication set of 433 papers published between 1923 and 2016. The publications covered by the Web of Science (WoS) show a significant increase since 1990, reaching about 30 papers per year at present. The results show that the current discourse on the collapse of the Maya civilization is focused on the role of climate as a major factor for the demise of this ancient civilization. The bibliometric analyses also reveal that (1) paleoclimatic records become numerous and are increasingly better dated; (2) the explanatory power of the records has been significantly increased by analyzing samples from regions closer to the relevant Maya sites; and (3) interdisciplinary cooperation of the humanities (archeology, anthropology, history) with natural sciences disciplines (geoscience, ecology, paleoclimatology, meteorology) seems to be highly promising. The collapse of the Maya civilization is a good example of how natural sciences entered research in the humanities and social sciences (anthropology, archeology, history) and boosted research (and solutions) around long-discussed, but unsolved questions.
›Data sources & pipeline
FAIR Checklist
Context only (not used in score)- Has DOI
- Open Access
- Dataset classification
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →
DataRank Breakdown
Base Score Contribution
0.500
From this paper's citation signal
Citation Network Contribution
0.190
From 10 citing papers with measurable signal
Top 5 citers driving the network score
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
- A unified approach to mapping and clustering of bibliometric networksJournal of Informetrics20101,637 citationsDataRank 1.1
- Growth rates of modern science: A bibliometric analysis based on the number of publications and cited referencesJournal of the Association for Information Science and Technology20151,488 citationsDataRank 1.1
- Climate Change Research in View of BibliometricsPLOS ONE2016326 citationsDataRank 10.0Top 21%
- Introducing CitedReferencesExplorer (CRExplorer): A program for reference publication year spectroscopy with cited references standardizationJournal of Informetrics2016137 citationsDataRank 4.0
- The application of bibliometrics to research evaluation in the humanities and social sciences: An exploratory study using normalized <scp>G</scp>oogle <scp>S</scp>cholar data for the publications of a research instituteJournal of the Association for Information Science and Technology201673 citationsDataRank 4.2
Why this DataRank?
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 72% comes from its base citations and 28% from the citation network (10 citing papers contributed measurable signal).
- Base score B(p)
- log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
- Network N(p)
- Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
- Damping factor d = 0.85
- DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
- Self-citations excluded
- Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
Click a node to highlight its connections. Use scroll to zoom. Drag to pan.