The LILY Database: Linking Lithology to IODP Physical, Chemical, and Magnetic Properties Data

During each expedition of the International Ocean Discovery Program and its precursor, the Integrated Ocean Drilling Program (jointly referred to as IODP), vast arrays of data are collected from drill cores. These data, which are accessible from the IODP LIMS (Laboratory Information Management System) database, include physical, chemical, and magnetic properties collected semi-continuously along cores using automated track systems, as well as a variety of analyses conducted on discrete subsamples taken from the cores. In addition, the lithology of all cores is described based on visual characteristics of the surface of split cores, visual examination of smear slides and thin sections, and compositional or mineralogical information derived from geochemical analyses. We extract basic lithologic information from this complex array of descriptive information and then tie that information to all other measurements. This new database is referred to as LIMS with Lithology (LILY). LILY currently contains over 34 million data from 89 km of core recovered on 42 expeditions conducted 2009-2019. Some uses of LILY include identifying the abundance of different lithologies, finding data from core intervals with a specific lithology, assessing the efficacy of coring systems in different lithologies, or characterizing and analyzing physical, chemical, and magnetic properties based on lithology. We illustrate the use of LILY by computing the grain density by lithology from over 24,000 moisture and density measurements and then use those grain densities, along with the large IODP bulk density dataset, to compute a new high-resolution porosity dataset with over 3.7 million new porosity estimates. CONTENT DESCRIPTION: The main LILY database is stored in the files with the suffix DataLITH.csv. Each file contains IODP LIMS data with lithology and other metadata added. The file prefix gives the type of data. For example, AVS_DataLITH.csv contains the Automated Vane Shear (AVS) shear strength data paired with lithology and other metadata. A list of all data types is given in Supporting Information Table S1 of Childress et al. (2024, https://doi.org/10.1029/2023GC011287). There are a total of 23 DataLITH files. AVS_DataLITH.csv: automated vane shear; shear strength measurements. CARB_DataLITH.csv: total carbon, hydrogen, nitrogen, and sulfur, inorganic carbon (carbonate), and organic carbon measured on discrete samples. GE_DataLITH.csv: gas elements from gas chromatography. GRA_DataLITH.csv: gamma ray attenuation bulk density from the Whole-Round Multisensor Logger (WRMSL). ICP_DataLITH.csv: Inductively-coupled plasma data. IW_DataLITH.csv: interstitial water chemistry. JR6A_DataLITH.csv: discrete magnetic measurements from the JR6A spinner magnetometer. KAPPA_DataLITH.csv: Kappabridge susceptibility meter measurements. MAD_DataLITH.csv: moisture and density from discrete samples. MS_DataLITH.csv: magnetic susceptibility from the WRMSL. MSP_DataLITH.csv: point magnetic susceptibility from the Section Half Multisensor Core Logger (SHMSL). NGR_DataLITH.csv: natural gamma radiation from the Natural Gamma Radiation Logger (NGRL). PEN_DataLITH.csv: pocket penetrometer compressional strength measurements. PWB_DataLITH.csv: P-wave velocity from the bayonet system. PWC_DataLITH.csv: P-wave velocity from the caliper system. PWL_DataLITH.csv: P-wave velocity from the WRMSL. RGB_DataLITH.csv: Red-Green-Blue color from the Section Half Imaging Logger (SHIL). RSC_DataLITH.csv: reflectance spectroscopy from the SHMSL. SRA_DataLITH.csv: source rock analyzer measurements. SRM_DataLITH.csv: Superconducting Rock Magnetometer (SRM) measurements of split-core sections. SRMD_DataLITH.csv: SRM measurements of discrete samples. TCON_DataLITH.csv: thermal conductivity measured with the Teka Berlin TK04 probe. TOR_DataLITH.csv: Torvane shear strength measurements. Other compressed data folders contain multiple files used in creating the LILY database: RawDESC.zip: Contains 7,940 .csv files derived from the raw text content of the DESClogik Excel worksheets that was extracted, converted to comma separated value (.csv) format, and put into files with a consistent naming convention, without applying any corrections or conversions to the original text. Each file is the direct extraction of a tab from the DESC workbooks, available at https://web.iodp.tamu.edu/DESCReport/ CoreSUMM.zip: Contains one file with Core Summary information, which includes the expedition, site, hole, core, coring type, top and bottom depths drilled, advances and recoveries, time and date of recovery, and the number of sections. These data are further paired with additional metadata (expanded core type, latitude, longitude, and water depth). Coordinates and water depth for each hole are derived from LIMS (and the JANUS database at http://www-odp.tamu.edu/database/ for older expeditions). RawDATA.zip: Contains the raw track/discrete dataset downloaded by expedition from IODP LIMS database and placed in folders for each type of data (AVS, CARB, SRM, etc.) RawLITH.zip: Contains 42 .csv files, with one file for each expedition. Each file contains all lithologic description (prefix, principal and suffix, etc.) information for an entire expedition, as it was originally described. These have been transformed to a consistent format and paired with consistent identification information and additional metadata. Headers are normalized across all expeditions and SampleID information is standardized. CleanLITH: Contains 42 .csv files. Each file contains all lithologic description (prefix, principal and suffix) information for an entire expedition. The lithologic descriptions have been standardized to a consistent nomenclature using the dictionary given in Support Information Table S4 of Childress et al. (2024, https://doi.org/10.1029/2023GC011287). These data are further paired with additional metadata (e.g., degree of consolidation, expanded core type, latitude, longitude, and water depth). GitHub Repository: Contains a few notebooks to demonstrate how to work with the LILY database IODP LILY GitHub Repository