Abstract (en): This study contains biographical data on the 92 Supreme Court justices appointed between 1789 and 1958. Potter C. Stewart, appointed in 1958, was the last justice to be included in the study. The study recorded personal data such as place of birth, education, political as well as nonpolitical occupation, legal and judicial experience, age at the time of Supreme Court appointment, ethnic background, and religious affiliation. Other background information on each justice includes party identification, reputation as a frequent dissenter, and the state from which he was appointed. Various aspects of family background such as social and economic status, paternal occupation, and familial traditions of judicial service were also explored. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Standardized missing values.; Checked for undocumented or out-of-range codes.. United States Supreme Court justices appointed between 1789 and 1958. The sample in this study consists of the entire population.

This is a cleaned and merged version of the OECD's Programme for the International Assessment of Adult Competencies. The data contains individual person-measures of several basic skills including literacy, numeracy and critical thinking, along with extensive biographical details about each subject. PIAAC is essentially a standardized test taken by a representative sample of all OECD countries (approximately 200K individuals in total). We have found this data useful in studies of predictive algorithms and human capital, in part because of its high quality, size, number and quality of biographical features per subject and representativeness of the population at large.

Abstract copyright UK Data Service and data collection copyright owner.

The purpose of the project was to make accessible for historical analysis the biographical information contained in Emden's Biographical Registers of the Universities of Oxford to 1540 and Cambridge to 1500. It was not intended to eliminate the need to consult the printed volumes, but rather to facilitate access to the different categories of material contained in them. For example, one could extract the names of those meeting certain predetermined criteria such as members of Merton College between 1320 and 1339 (dates were encoded as belonging to 20 year 'generations') who were authors. For fuller details the printed volumes would have to be consulted.
Main Topics:
The datasets consist of a series of indexes to the entries in Emden's Biographical Registers of the Universities of Oxford to 1540 and Cambridge to 1500, arranged by various categories of biographical information. The categories include: membership of faculties, colleges and religious orders; place of origin; ownership, authorship and donations of books; tenure of legal and official posts; and association with royal, noble and episcopal households.

Biodata items and domains to which they belong.

This dataset consists of 51 randomly selected entries from the Slovenian Biographical Lexicon (1925–1991). The text of each entry has been manually tokenised and sentence segmented, marked with named entities and the words lemmatised. It has also been automatically annotated with PoS tags (MULTEXT-East morphosyntactic descriptions) and Universal Dependencies PoS tags, morphological features and dependency parses.

Crucially for the envisaged use of the corpus, the abbreviations in the corpus (of which there are 2,041) have been manually expanded so that the expanded abbreviations are also in the correct inflected form, given their context.

The corpus is available in the canonical TEI encoding, and derived plain text and CoNLL-U files. The plain-text file has abbreviations and their expansions marked up with [...]. There are two CoNLL-U files, one with the text stream with abbreviations, and one with the text stream with expansions. Note that only the one with expansions has syntactic parses. Both CoNLL-U files have the expansions / abbreviations and named entities marked up in IOB format in the last column.

Regression analysis of job performance using rational biodata.

This Excel file lists the samples uploaded in PRIDE. The table “Table Sorted PP and Replicates” in the Excel file has all the relevant annotation.

There are more than the expected 168 samples in the PRIDE upload for the following reasons:

First, all of the measurements from the experiment had been uploaded, including files for measurements that were repeated because of problems during the MS run. These samples are not annotated in the table. Second, we had included 4 Gold Standard samples (2 replicates on each of the two large gels used to process all samples). These 4 gold standard samples in 7 fractions explain 28 extra samples. Third, we did not have 168 but 166 samples in the photoperiod set. Fractions 1 and 2 of sample 43 (Photoperiod 2, bio replicate 1, tech. replicate 2) were lost during sample preparation. While the remaining fractions were measured and are included in the PRIDE upload and the table, this sample was not used in the data analysis. Photoperiod 2 bio rep. 1 was only used with one technical replicate in the calculations.

This is a collection of data consisting of pigment concentration and composition, particulate and dissolved absorption co-efficients and total suspended matter concentration. The data relates to samples collected in Chilean coastal waters where aquaculture is present. The data will be used to develop a local algorithm for retrieved satellite estimates of bio-optical parameters in the water column. Lineage: Water samples were taken on-board the vessel and stored under cool and dark conditions until filtering took place on land. Samples were analysed and QC procedures were carried out in the Bio-Analytical facility, CSIRO Marine Labs, Hobart. For pigment analysis, 4 litres of sample water was filtered through a 47 mm glass fibre filter (Whatman GF/F) and then stored in liquid nitrogen until analysis. To extract the pigments, the filters were cut into small pieces and covered with 100% acetone (3 mls) in a 10 ml centrifuge tube. The samples were vortexed for about 30 seconds and then sonicated for 15 minutes in the dark. The samples were then kept in the dark at 4 °C for approximately 15 hours. After this time 200 µL water was added to the acetone such that the extract mixture was 90:10 acetone:water (vol:vol) and sonicated once more for 15 minutes. The extracts were centrifuged to remove the filter paper and then filtered through a 0.2 µm membrane filter (Whatman, anatope) prior to analysis by HPLC using a Waters Alliance high performance liquid chromatography system, comprising a 2695XE separations module with column heater and refrigerated autosampler and a 2996 photo-diode array detector. Immediately prior to injection the sample extract was mixed with a buffer solution (90:10 28 mM tetrabutyl ammonium acetate, pH 6.5 : methanol) within the sample loop. Pigments were separated using a Zorbax Eclipse XDB-C8 stainless steel 150 mm x 4.6 mm ID column with 3.5 µm particle size (Agilent Technologies) with gradient elution as described in Van Heukelem and Thomas (2001). The separated pigments were detected at 436 nm and identified against standard spectra using Waters Empower software. Concentrations of chlorophyll a, chlorophyll b, b,b-carotene and b,e-carotene in sample chromatograms were determined from standards (Sigma, USA or DHI, Denmark). For Absorption coefficients: 4 litres of sample water was filtered through a 25 mm glass fibre filter (Whatman GF/F) and the filter was then stored flat in liquid nitrogen until analysis. Optical density spectra for total particulate matter were obtained using a Cintra 404 UV/VIS dual beam spectrophotometer equipped with an integrating sphere. For CDOM: water filtered through a 0.22 Durapore filter on an all glass filter unit. Optical density spectra was obtained using 10 cm cells in a Cintra 404 UV/vis spectrophotometer with Milli-q water as a reference. For TSM: determined by drying the filter at 60°C to constant weight; the filter may then be muffled at 450°C to burn off the organic fraction. The inorganic fraction is weighed ad the organic fraction is determined as the difference between the SPM and the inorganic fraction.

Abstract copyright UK Data Service and data collection copyright owner.

To collect psychometric and biographical data which may enhance counselling and selection of students. A similar study of high school pupils is held as SN: 996.
Main Topics:

Variables
A. Psychometric
(1) Occupational interests: Connolly Occupational Questionnaire and the IBD Interest Inventory.
(2) Occupational attitudes.
(3) Value systems: Rokeach Value Survey.
B. Biographic
Age, sex, socio-economic variables, work and educational history, educational expectations.

Abstract copyright UK Data Service and data collection copyright owner.

The aim of Deaddocs: a bibliographical index is to provide information and references for medical and other historians, as well as for researchers in local and family history of medical practitioners who died between 1750 and 1850. Deaddocs was originally planned to be one of the research publications of the Wellcome Unit for the History of Medicine at the University of Oxford. The aim of the Unit's research publications was "to make available in an inexpensive form, bibliographical, documentary and research aids in fields relating to the history of medicine". The resulting index was so large that paper publication became out of the question. Its aim was to provide brief biographical details in a standardized form. There is space for up to seven references which are coded to give some indication of their length and importance. The index is more fully described in the study's documentation.

Because there was no compulsory Medical Register before 1858, and until 1845 only an occasional medical directory, the aim was to identify as many medical practitioners, and others in related medical occupations, as possible, using obituaries and posthumous accounts appearing in British medical journals and related sources between 1750 and 1850. The Gentleman's Magazine, rather than any medical journal, turned out to be the major source for the years 1750-1773. W.R. LeFanu's British Periodicals of Medicine 1640-1899 was the main source for the titles of the medical journals. He lists over two hundred medical journals between 1750 and 1850, though not quite all of them could be found, and a small number when found were incomplete.

Main Topics:

The index is more fully described in the study documentation. It consists of 10,341 numbered entries. Some individuals are cross-referenced - those who worked under two names, and those with the prefix De or Von for example. The individual records give surname and up to four forenames, as well as the title[s] by which the subject was known. The record has space for dates of birth and death, year of death, place of birth, up to five places of residence, place of death, father's name and occupation, subject's profession, army, navy and East India Company service, whether the subject was a woman (there are several nurses and midwives), professional work, cause of death, and degree[s]. Entries in the Dictionary of National Biography, Commissioned Officers in the Medical Service of the British Army 1660-1960, and the Roll of the Indian Medical Service are noted but not copied. There is space for up to seven journal references, coded for their importance. Under the heading "SEE ALSO", "MORE" means that there were more than seven references found, and cross references to other family members are also entered. There are two "NOTES" sections for additional information.

The study documentation, as well as describing the database, includes a complete list of the journals searched, and the name of the person searching each journal. The works consulted and the abbreviations used are listed, together with acknowledgements and references.

Bio Banking Human Samples Market Outlook

The global biobanking human samples market size was valued at USD 2.8 billion in 2023 and is projected to reach USD 6.4 billion by 2032, growing at a CAGR of 9.2% during the forecast period. The significant growth factor driving the market is the increasing demand for personalized medicine and advancements in genomics and proteomics technologies. This market is pivotal in supporting biomedical research, clinical trials, and therapeutic applications, which are essential for the development and implementation of personalized treatment plans and innovative therapies.

One of the primary growth drivers of the biobanking human samples market is the advancement in precision medicine, which requires extensive biological sample repositories to tailor treatments based on individual genetic profiles. The increasing prevalence of chronic diseases such as cancer, diabetes, and cardiovascular disorders has also necessitated the use of biobanks to support the identification of disease biomarkers, leading to earlier diagnosis and more effective treatments. Additionally, the integration of next-generation sequencing (NGS) technologies with biobanking processes has revolutionized the way genetic data is analyzed, further fueling market growth.

Government and private sector investments in biobanking infrastructure have also significantly contributed to market expansion. Several governments worldwide are recognizing the importance of biobanks in advancing healthcare and are providing substantial funding for biobank establishment and maintenance. Additionally, private sector entities, including pharmaceutical and biotechnology companies, are increasingly investing in biobanks to accelerate drug discovery and development processes. These investments are not only expanding the capacity of existing biobanks but are also facilitating the establishment of new biobank facilities across the globe.

The increasing trend of collaborations and partnerships among research institutes, healthcare providers, and biobanking organizations is another crucial factor driving market growth. These collaborations aim to standardize biobanking practices, enhance the quality and accessibility of biological samples, and facilitate data sharing among researchers. Such cooperative efforts are essential for the advancement of biomedical research and the development of novel therapies. By pooling resources and expertise, these partnerships help overcome challenges related to sample collection, storage, and utilization, ultimately contributing to market growth.

The role of Biobank Equipment is becoming increasingly vital as the demand for high-quality biological samples grows. These specialized tools and technologies are essential for the proper collection, processing, and storage of diverse sample types, ensuring their integrity and usability for research and clinical applications. Advanced biobank equipment, such as automated storage systems and cryogenic freezers, provide precise environmental controls and efficient sample management, reducing the risk of contamination and degradation. As biobanks expand their operations and scale up their sample repositories, investing in state-of-the-art equipment is crucial to meet the stringent quality standards required for biomedical research and personalized medicine. The integration of innovative technologies in biobank equipment is also enhancing the efficiency of sample retrieval and data management, facilitating seamless collaboration among researchers and healthcare providers.

Regionally, North America dominates the biobanking human samples market, accounting for the largest market share. This dominance is attributed to the well-established healthcare infrastructure, significant government funding, and the presence of major biobanking players in the region. Europe is the second-largest market, driven by the increasing focus on personalized medicine and extensive research activities. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, mainly due to the rising investments in healthcare infrastructure, growing prevalence of chronic diseases, and increasing government initiatives to support biobanking activities.

Sample Type Analysis

In the biobanking human samples market, the sample type segment includes blood, tissue, cell lines, nucleic acids, and others. Blood samples hold the largest market share due to their widespread use in various research and clinical applicat

Project WARLUX - Soldiers and their communities in WWII: The impact and legacy of war experiences in Luxembourg is a research project based at the Luxembourg Centre for Contemporary and Digital History (C²DH) (University of Luxembourg). The projects focuses on the war experiences of male Luxembourgers born between 1920 and 1927 who were recruited and conscripted into Nazi German services (Reichsarbeitsdienst (RAD) and Wehrmacht) under the Nazi occupation in Luxembourg during the Second World War.

Data Sample

While over 12,000 men and women were affected by the conscription, Project WARLUX focuses on a case study of 304 recruits from Schifflange and their families. In total, the data sample includes around 1200 persons, recruits and their family members.

Origin of the data

The dataset primarily consists of compiled archival documentation, including organizational and official documents, statistics, and standardized fiches and cards. These sources are primarily sourced from the Luxembourgish National Archives and other relevant repositories.

In addition to basic information such as name, birth date, and residence, the (internal) dataset also incorporates military records sourced from German archives. Furthermore, supplementary information related to captivity, repatriation, and compensation was collected in the post-war period. The surveys and statistics conducted by the Luxembourgish state provide valuable insights into the experiences and trajectories of the war-affected generation.

It is important to note that the dataset is a composite of multiple heterogeneous sources, reflecting its diverse origins.

Database

The researchers involved in the WARLUX project opted for the utilization of a relational database, nodegoat.

The WARLUX project adheres to an object-oriented approach, which is reflected in the core functionalities provided by nodegoat. Given the project's specific focus on the war experiences of recruited Luxembourgers within Nazi services such as the Wehrmacht and RAD, the included data model (warlux data model file) represents only a partial depiction of the comprehensive nodegoat environment employed in the WARLUX project. Within this data model, the interconnected objects and their respective sub-objects are presented, with particular emphasis placed on the individual profiles of recruits and their involvement in military service.

As the data can not be published due to restriction, the team provides a pseudonymized dataset as an example of the data structure.

The provided dataset shows the male recruits (and conscripts) of the Case Study Schifflange (born between 1920 and 1927). It includes

• nodegoat ID
• their birthdate
• information on death if it occurred during the war
• whereabout after the war (unknown, missing, KIA, returned etc.)

The dataset also includes references to their recruitment into

• the Wehrmacht and/or the RAD as well as their subsequent activities such as
• being captured as a Prisoner of War (POW)
• serving for the Allied Forces
• desertion, or
• draft evasion (réfractaire).

The access to the WARLUX nodegoat database, on recruits of Schifflange/Luxembourg is restricted due to sensitive data. For further questions please contact warlux@uni.lu

The project is funded by the Fond National de la Recherche Luxembourg (FNR).

This record is an overview entry for biological data collected on Soela cruise SO 1/83. This cruise took place in the North West Shelf during 20 January - 2 March 1983, under the leadership of Tim Davis and Keith Sainsbury. Biological data collected on this cruise include composition and abundance data of demersal fish. Fish samples for biological studies (growth, reproduction and mortality). Zooplankton abundance data and larval fish samples. Carangid larvae for ageing studies. Lobster samples from six exploratory trawls. Lutjanus vitta and L. russelli for assessment of lunar periodicity of spawning. Prey availability and diet of Nemipterus peronii, N. tambuloides and Saurida undosquamis were examined in 6 areas. Fish specimens were obtained for stomach analysis, and benthic and epibenthic samples from the area. Dive observation data from an area adjacent to Bedout Island for experimental manipulation of epibenthos.(derived from the cruise report) - Biological data is available via Data Trawler. - Biological Field Data Sheets recorded during this voyage have been scanned to PDF, and are available on-line at http://www.marine.csiro.au/datacentre/process/data_files/BioData/log_sheet_scans/BOX_AB2009_550/BOX_AB2009_550_index.htm and http://www.marine.csiro.au/datacentre/process/data_files/BioData/log_sheet_scans/BOX_AB2009_551/BOX_AB2009_551_index.htm

This study began by comparing a group of children with high intelligence quotients with groups of children typical of the general population, to discover similarities and differences. Research was continued from the initial collection date of 1922 through the present, with follow-ups at approximately 5-year intervals, to explore long-term development of these children. Through a process of teacher nomination and intelligence testing, 1,470 children in California with an IQ of 135 or above, were selected. In 1927-28, 58 siblings of the participants were added as a comparison group. Of the 1,528 participants in the study, 856 were male and 672 were female. The average date of birth for the sample was 1910. In 1922, parents filled out an extensive questionnaire describing the child's birth and previous health, educational and social experiences, interests, and conduct. The children's teachers filled out a similar questionnaire. The children took a battery of intelligence, achievement, and personality tests and answered questionnaires about their interests in and knowledge of many matters. Several of these procedures were repeated in 1928. In 1936, the primary source of data was questionnaires filled out by the participants and their spouses. The 1940 follow-up covered development of personality and temperament, and included an elaborate study of marital relationships. In 1950, a similar follow-up added a lengthy biographical data questionnaire. The 1945, 1955, and 1960 follow-ups were more modest, with the 1945 follow-up focusing on the effects of the WWII military effort on the participants. In 1972, 1977, and 1982, the follow-ups were oriented to problems of aging, such as life satisfactions, retirement, living arrangements, and health and vitality. The data collected in 1986 included questions about changes in well-being, time use, importance of religion, perspectives on life accomplishments, changes in family relationships, concerns and goals. The Murray Archive holds additional analogue materials for this study (microfiche copies of original record paper questionnaires from waves one through 12). Researchers seeking to access this material must apply to use the data.

This record is an overview entry for biological data collected on Soela cruise SO 5/82. This cruise took place in the North West Shelf during 25 September - 27 October 1982, under the leadership of Keith Sainsbury and R. Lindholm. Biological data collected on this cruise include length frequency of 47 species and biological samples (for growth, reproduction and mortality studies) from 32 species. Larval fish and zooplankton samples from shallow waters and out past the shelf break. Benthic fauna and some epibenthos specimens. Data from healthy fish tagging. Biological data on 63 sharks and squid samples from trawls when caught. Lethrinid gonads were collected for sex inversion studies.(derived from the cruise report) - Biological data is available via Data Trawler. - Biological Field Data Sheets recorded during this voyage have been scanned to PDF, and are available on-line at http://www.marine.csiro.au/datacentre/process/data_files/BioData/log_sheet_scans/BOX_AB2009_544/BOX_AB2009_544_index.htm and http://www.marine.csiro.au/datacentre/process/data_files/BioData/log_sheet_scans/BOX_AB2009_548/BOX_AB2009_548_index.htm

Abstract (en): This dataset was produced by Darrett B. and Anita H. Rutman while researching their book A Place in Time: Middlesex County Virginia, 1650-1750 and the companion volume, A Place in Time: Explicatus (both New York: Norton, 1984). Together, these works were intended as an ethnography of the English settlers of colonial Middlesex County, which lies on the Chesapeake Bay. The Rutmans created this dataset by consulting documentary records from Middlesex and Lancaster Counties (Middlesex was split from Lancaster in the late 1660s) and material artifacts, including gravestones and house lots. The documentary records include information about birth, marriage, death, migration, land patents and conveyances, probate, church matters, and government matters. The Rutmans organized this material by person involved in the recorded events, producing over 12,000 individual biographical sheets. The biographical sheets contain as much information as could be found for each individual, including dates of birth, marriage, and death; children's names and dates of birth and death; names of parents and spouses; appearance in wills, transaction receipts, and court proceedings; occupation and employers; and public service. This process is described in detail in Chapter 1 of A Place in Time: Middlesex County Virginia, 1650-1750. The Rutmans' biographical sheets have been archived at the Virginia Historical Society in Richmond, Virginia. To produce this dataset, most of the sheets were photographed (those with minimal information -- usually only a name and one date -- were omitted). Information from the sheets was then hand-keyed and organized into two data tables: one containing information about the individuals who were the main subjects of each sheet, and one containing information about children listed on those sheets. Because individuals appear several times, data for the same person frequently appears in both tables and in more than one row in each table. For example, a woman who lived all her life in Middlesex and married once would have two rows in the children's table -- one for her appearance on her mother's sheet and one for her appearance on her father's sheet -- and two rows in the individual table -- one for the sheet with her maiden name and one for the sheet with her married name. After entry, records were linked in order to associate all appearances of the same individual and to associate individuals with spouses, parents, children, siblings, and other relatives. Sheets with minimal information were not included in the dataset. The data includes information on 6586 unique individuals. There are 4893 observations in the individual file, and 7552 in the kids file. The purpose of the data collection was to develop an ethnography of the English settlers of colonial Middlesex County, Virginia, which lies in the Chesapeake Bay. The Rutmans created this dataset by consulting documentary records from Middlesex and Lancaster Counties (Middlesex was split from Lancaster in the late 1660s) and material artifacts, including gravestones and house lots. The documentary records include information about birth, marriage, death, migration, land patents and conveyances, probate, church matters, and government matters. The Rutmans organized this material by person involved in recorded events, producing over 12,000 individual biographical sheets. The biographical sheets contain as much information as could be found for each individual, including dates of birth, marriage, and death; children's names and dates of birth and death; names of parents and spouses; appearance in wills, transaction receipts, and court proceedings; occupation and employers; and public service. This process is described in detail in Chapter 1 of A Place in Time: Middlesex County Virginia, 1650-1750 (New York: Norton, 1984). The data are not weighted. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes.. English settlers of colonial Middlesex County, Virginia. Smallest Geographic Unit: county The original data collection was not sampled. However, in computerizing this resource, biographical shee...

Abstract

The Quarterly Labour Force Survey (QLFS) is a household-based sample survey conducted by Statistics South Africa (Stats SA). It collects data on the labour market activities of individuals aged 15 years or older who live in South Africa.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

The QLFS sample covers the non-institutional population of South Africa with one exception. The only institutional subpopulation included in the QLFS sample are individuals in worker's hostels. Persons living in private dwelling units within institutions are also enumerated. For example, within a school compound, one would enumerate the schoolmaster's house and teachers' accommodation because these are private dwellings. Students living in a dormitory on the school compound would, however, be excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

The QLFS uses a master sampling frame that is used by several household surveys conducted by Statistics South Africa. This wave of the QLFS is based on the 2013 master frame, which was created based on the 2011 census. There are 3324 PSUs in the master frame and roughly 33000 dwelling units.

The sample for the QLFS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.

For each quarter of the QLFS, a quarter of the sampled dwellings are rotated out of the sample. These dwellings are replaced by new dwellings from the same PSU or the next PSU on the list. For more information see the statistical release.

Mode of data collection

Face-to-Face and Computer Assisted Personal and Telephone Interview

Research instrument

The survey questionnaire consists of the following sections: - Biographical information (marital status, education, etc.) - Economic activities for persons aged 15 years and older

This record is an overview entry for biological data collected on Soela cruise SO 6/82. This cruise took place in the North West Shelf during 15 November - 16 December 1982, under the leadership of Tim Davis and A. Heron. Biological data collected on this cruise include demersal fish and shark samples. Lutjanus vitta samples to investigate lunar periodicity in spawning activity. Stomach samples of Nemipterus peronii, Saurida undosquamis, Abalistes stellaris, Parapeneus pleurospilus, Nemipterus tambuloides and Lethrinus choerorhynchus from diel feeding experiment and 4812 stomach samples from 52 trawls. Zooplankton abundance data, larval fish and benthic samples. Phytoplankton, bacteria and zooplankton productivity data. Storage trial data on Epinephalus areolatus and Glaucosoma burgeri for the food technology studies. Trial data on healthy fish tagging. EK 400 acoustic data at four stations for John Penrose, W.A.I.T.(derived from the cruise report) - Biological data is available via Data Trawler. - Biological Field Data Sheets recorded during this voyage have been scanned to PDF, and are available on-line at http://www.marine.csiro.au/datacentre/process/data_files/BioData/log_sheet_scans/BOX_AB2009_549/BOX_AB2009_549_index.htm and http://www.marine.csiro.au/datacentre/process/data_files/BioData/log_sheet_scans/BOX_AB2009_550/BOX_AB2009_550_index.htm

Complete data and metadata of modern and archaeological samples. The table summarizes samples metadata regarding the time period (archaeological or modern); tooth type (following FDI identification system); dental pathologies; smoking habits; and real age of the samples (Real_Age and Real_Age_1 – the latter has been added for the archaeological samples, whose age was estimated and whose age range was averaged for the purpose of this study). The table also shows the outcome of the analyses carried out in this study (occurrence of the smoking damage; the total count of the increments counted (IL_Count); the measurement of cementum width (Width); and prediction of age (Predicted_Age)). “Occlusion_Age” refers to the standardised age at which teeth come into occlusion, according to AlQahtani et al., 2010 [38]. (XLSX)

Analyses on the smoking damage for prediction of individual’s smoking timeline. Data on sample VP_H_026 (shown in Fig 2C), indicating: type of tooth (FDI); Sex; Smoking status; Real age; Tooth-specific occlusion age; total count of the increments (IL Count); count of the increments up to the damage (smoking damage start) and from external border of the tissue (smoking damage end); prediction of age range at which the smoking damage occurred; and prediction of age of the individual.