Dataset of Element Compositions and Mean Zircon Hafnium Isotopes of Igneous Rocks underlying the research: A test of the hypothesis that syn-collisional felsic magmatism contributes to continental crustal growth

The dataset contains the ages, thirty-five element compositions, and mean zircon ε_Hf(t) compositions of igneous rocks. The data is extracted from the database GEOROC and Tibetan Magmatism Database. The lithology in the dataset includes andesitic, anorthositic, basaltic, dacitic, dioritic, gabbroic, granitic, monzonitic, rhyolitic, and ultramafic rocks. The proportion of acidic, intermediate, mafic, and ultramafic rocks are 55%, 35%, 9%, and 1%, respectively. The data are temporally concentrated in Jurassic and early Cretaceous (n = 384), then in Precambrian (n = 344), late Cretaceous (n = 330), Trassic (n = 235), Cenozoic (n = 230), Permian (n = 206), Carboniferous (n = 152), and Silurian and Ordovician (n = 133). The elements include SiO₂, TiO₂, Al₂O₃, MnO, MgO, CaO, Na₂O, K₂O, P₂O₅, V, Ni, Rb, Sr, Y, Zr, Nb, Ba, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, Hf, Ta, Th, and U. The sample ages span from Proterozoic to Cenozoic, and the mean zircon ε_Hf(t) values range from −30 to 30.The dataset is anticipated to help generate and test hypotheses particularly about the evolution of Earth's crust.It is the dataset underlying the research/article: A test of the hypothesis that syn-collisional felsic magmatism contributes to continental crustal growth via deep learning modeling and principal component analysis of big geochemical datasets.In addition to direct utilization of raw data, advanced data science such as supervised/unsupervised machine learning algorithms can be applied to extract implicit geologic information.

本数据集收录了火成岩的年龄、35种元素组成以及锆石ε_Hf(t)平均值。数据源自GEOROC数据库与西藏岩浆作用数据库（Tibetan Magmatism Database）。数据集涵盖的岩性包括安山质、斜长岩质、玄武质、英安质、闪长质、辉长质、花岗质、二长质、流纹质以及超镁铁质岩石。其中酸性、中性、镁铁质与超镁铁质岩石的占比分别为55%、35%、9%与1%。数据的时间分布主要集中于侏罗纪与早白垩世（n=384），其次依次为前寒武纪（n=344）、晚白垩世（n=330）、三叠纪（n=235）、新生代（n=230）、二叠纪（n=206）、石炭纪（n=152）以及志留纪与奥陶纪（n=133）。涉及的分析元素包括SiO₂、TiO₂、Al₂O₃、MnO、MgO、CaO、Na₂O、K₂O、P₂O₅、V、Ni、Rb、Sr、Y、Zr、Nb、Ba、La、Ce、Pr、Nd、Sm、Eu、Gd、Tb、Dy、Ho、Er、Tm、Yb、Lu、Hf、Ta、Th及U。样本年龄跨度从元古宙至新生代，锆石ε_Hf(t)平均值的范围为-30至30。本数据集可用于构建并验证相关假说，尤其适用于围绕地球地壳演化开展的研究。本数据集为下述研究论文提供了数据支撑：《通过深度学习建模与大型地球化学数据集主成分分析验证同碰撞长英质岩浆作用促进大陆地壳生长的假说》。除直接使用原始数据外，还可应用监督/无监督机器学习算法等先进数据科学方法，挖掘其中隐含的地质信息。