Raw and normalized X-ray fluorescence (XRF) scannings of IODP Expedition 321, Site U1338

We used X-ray fluorescence (XRF) scanning on Site U1338 sediments from Integrated Ocean Drilling Program Expedition 321 to measure sediment geochemical compositions at 2.5 cm resolution for the 450 m of the Site U1338 spliced sediment column. This spatial resolution is equivalent to ~2 k.y. age sampling in the 0-5 Ma section and ~1 k.y. resolution from 5 to 17 Ma. Here we report the data and describe data acquisition conditions to measure Al, Si, K, Ca, Ti, Fe, Mn, and Ba in the solid phase. We also describe a method to convert the data from volume-based raw XRF scan data to a normalized mass measurement ready for calibration by other geochemical methods. Both the raw and normalized data are reported along the Site U1338 splice.

Inventory of SINOPS project data sets

During the SINOPS project, an optimal state of the art simulation of the marine silicon cycle is attempted employing a biogeochemical ocean general circulation model (BOGCM) through three particular time steps relevant for global (paleo-) climate. In order to tune the model optimally, results of the simulations are compared to a comprehensive data set of 'real' observations. SINOPS' scientific data management ensures that data structure becomes homogeneous throughout the project. Practical work routine comprises systematic progress from data acquisition, through preparation, processing, quality check and archiving, up to the presentation of data to the scientific community. Meta-information and analytical data are mapped by an n-dimensional catalogue in order to itemize the analytical value and to serve as an unambiguous identifier. In practice, data management is carried out by means of the online-accessible information system PANGAEA, which offers a tool set comprising a data warehouse, Graphical Information System (GIS), 2-D plot, cross-section plot, etc. and whose multidimensional data model promotes scientific data mining. Besides scientific and technical aspects, this alliance between scientific project team and data management crew serves to integrate the participants and allows them to gain mutual respect and appreciation.