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6,782 results for “project”
PROGRAMS project. Machine tool data from Aurrenak S. Coop. on 2020 Week 21
<p>These data were collected from FIDIA machine tool controller during milling operation.</p>
PROGRAMS project. Machine tool data from Aurrenak S. Coop. on 2020 Week 17
<p>These data were collected from FIDIA machine tool controller during milling operation.</p>
PROGRAMS project. Machine tool data from Aurrenak S. Coop. on 2020 Week 20
<p>These data were collected from FIDIA machine tool controller during milling operation.</p>
PROGRAMS project. Machine tool data from Aurrenak S. Coop. on 2020 Week 19
<p>These data were collected from FIDIA machine tool controller during milling operation.</p>
PROGRAMS project. Machine tool data from Aurrenak S. Coop. on 2020 Week 15
<p>These data were collected from FIDIA machine tool controller during milling operation.</p>
PROGRAMS project. Machine tool data from Aurrenak S. Coop. on 2020 Week 14
<p>These data were collected from FIDIA machine tool controller during milling operation.</p>
PROGRAMS project. Machine tool data from Aurrenak S. Coop. on 2020 Week 16
<p>These data were collected from FIDIA machine tool controller during milling operation.</p>
Pseudo-observational datasets for testing projection calibration methods (EUCP WP2)
<p>Pseudo-observational datasets, produced by standardising and anonymising output from climate model data from the CMIP6 archive. </p> <p>Each folder "PSEUDOobs_*.tar.gz" contains the data required for the different EUCP Work Package 2 methods to calibrate projections (see, e.g., initial comparison of methods presented in Brunner et al., Journal of Climate, 2020, <em>in revision</em>).</p> <p>All data is in netcdf format.</p> <p> </p> <p><em>References:</em></p> <p>Brunner, L., et al., "Comparing methods to constrain future European climate projections using a consistent framework", Journal of Climate, <em>in revision.</em></p>
Stevison Lab dataset and code for peak plasticity project
<p>Github repository containing data files and scripts to reproduce the analysis for the manuscript titled: <strong>"refining the peak time point for recombination rate plasticity in <em>Drosophila pseudoobscura</em>"</strong></p>
Data and code for project on maternal age and recombination rate in Drosophila pseudoobscura
<p>Github repository containing data files and scripts to reproduce the analysis for the manuscript titled: <strong>"Maternal age alters recombination rate in <em>Drosophila pseudoobscura</em>"</strong>. </p>
STILNOVO project (Sub.measure 16.2 RDP Tuscany Region 2014-2020)
<p>Dataset of pasture production and quality and milk production and quality of a rotational grazing trial carried out in 2018 in south Tuscany.</p>
SPARC Reanalysis Intercomparison Project (S-RIP) reanalysis common grid files
<p>This is the reanalysis common grid data set produced as part of the SPARC (Stratosphere-troposphere Processes and their Role in Climate) Reanalysis Intercomparison Project (<a href="https://s-rip.ees.hokudai.ac.jp/">S-RIP</a>). These data have been used in several chapters in the S-RIP report, including Chapter 4 (Overview of Ozone and Water Vapou<strong>r</strong> - See <a href="http://doi.org/10.5194/acp-17-12743-2017">Davis et al., ACP, 2017</a>) and Chapter 8 (Tropical Tropopause Layer - See <a href="https://www.atmos-chem-phys.net/20/753/2020/">Tegtmeier et al., ACP, 2020</a>).</p> <p>Notes about this data set:</p> <p> - Data set size: ~26 GB<br> - Reanalyses included are CFSR, ERA-I, JRA-25, JRA-55, MERRA, MERRA-2<br> - Variables include T (variable name ta), u (ua), v (va), O3 (tro3), WV (hus), and GPH (zg)<br> - Data are based off of the ana4mips data set<br> - Data are on a 2.5° x 2.5° grid<br> - All values are monthly means<br> - Pressure levels are (1000, 925, 850, 700, 600, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30, 20, 10, 7, 5, 3, 2, 1, .7, .5, .3, .1 hPa)<br> - 3 time periods are provided:<br> - The “full” time period (different for each reanalysis)<br> - The “S-RIP base period” (i.e., 197901-201312)<br> - The “climatology” period (198101-201012)<br> - Both 3D (lon,lat,level) and zonal mean 2D (lat, level) files are provided<br> - Both timeseries and climatology data are provided. Files with “ltm” in the name are climatologies<br> - Reanalysis “Ensemble” files are located in the /ensemble directory (See note below*)</p> <p><br> *Regarding the “ensemble” data — I highly recommend using the “ensemble” files in the “ensemble” folder for climatological intercomparisons.<br> You can use a single file (e.g., hus_Amon_reanalysis_ENS_198101-201012.cg.ltm.nc for water vapor) that contains the climatologies for each reanalysis.<br> The data in these files are of dimension (lon, lat, level,time(==12 months ), “record”), where record 0 = CFSR, 1=ERA-I, 2=JRA-25, 3=JRA-55, 4=MERRA, 5=MERRA2.</p> <p>There is also a corresponding “ensemble mean” file (e.g., hus_Amon_reanalysis_ENS_198101-201012.cg.ltm.ensmean.nc) that is simply the ensemble mean climatology from the 4 core reanalyses (CFSR, ERA-I, JRA-55, MERRA — EXCLUDING JRA-25 & MERRA2).</p>
Ecosystem process rates across SAFE project forest quality gradient
<b>Description: </b><p>Examining rates at which vertebrate and invertebrate functional groups carry out 3 key ecosystem functions (seed removal, invertebrate predation and scavenging) and whether this changes across the SAFE project forest quality gradient. At second order sites (tree plots) within the SAFE project landscape, bait stations to test these three processes were set up. These consisted of 10 seeds (to test seed removal), live mealworm (to test invertebrate predation) or dead mealworm (to test scavenging). 3 bait stations for each ecosystem process set up in a triangle at the third order point (insect point). These consisted of baits attached to a plastic leaf. Each of these bait stations was assigned vertebrate exclusion treatment (wire cage), invertebrate exclusion (insect glue) or control (no exclusion). Data obtained from LIDAR used as a proxy for forest quality. This should help unravel how ecosystem process rates and the dominant functional group carrying out these processes may change as forests are degraded.</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/152"><b>MRes Tropical Forest Ecology Field Course</b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3908118">here</a></p><p><b>Files: </b>This consists of 1 file: Ecosystem_Process_Rates.xlsx</p><p><b>Ecosystem_Process_Rates.xlsx</b></p><p>This file contains dataset metadata and 1 data tables:</p><ol><li><p><b>Rates of Ecosystem Processes</b> (described in worksheet Ecosystem-Process-Rates)</p><p>Description: Results from ecosystem process rates experiments (described above)</p><p>Number of fields: 29</p><p>Number of data rows: 2039</p><p>Fields: </p><ul><li><b>ID</b>: Location of sampling point (Field type: location)</li><li><b>ec5_uuid</b>: Entry code on epicollect (Field type: id)</li><li><b>created_at</b>: Date and Time (Field type: datetime)</li><li><b>created_by</b>: Author email (Field type: id)</li><li><b>title</b>: Title of entry on epicollect (Field type: id)</li><li><b>X2_Block</b>: Site ID (Field type: id)</li><li><b>X3_Tree_plot_ID</b>: Tree plot number (Field type: id)</li><li><b>X4_Picture_of_tree_pl</b>: Photo of tree plot tag (Field type: id)</li><li><b>X5_Insect_point_ID</b>: Insect point number (Field type: id)</li><li><b>X6_Picture_of_insect_</b>: Photo of insect point tag (Field type: id)</li><li><b>X7_Repeat</b>: Repeat (Field type: replicate)</li><li><b>X8_Treatment</b>: Treatment categories (Field type: categorical)</li><li><b>X9_Date</b>: Date (Field type: date)</li><li><b>X10_Time</b>: Time (Field type: time)</li><li><b>X11_Ecosystem_Process</b>: Ecosystem process (Field type: categorical)</li><li><b>X13_Seeds_removed</b>: Number of seeds removed (Field type: numeric)</li><li><b>X14_Seeds_partially_e</b>: Number of seeds partially eaten (Field type: numeric)</li><li><b>X15_Seeds_untouched</b>: Number of seeds untouched (Field type: numeric)</li><li><b>X17_Live_mealworm</b>: Level of consumption of live mealworm (Field type: categorical)</li><li><b>X19_Dead_mealworm</b>: Level of consumption of dead mealworm (Field type: categorical)</li><li><b>X20_Condition_of_trap</b>: Condition of trap (Field type: categorical)</li><li><b>lat_22_GPS</b>: NA (Field type: latitude)</li><li><b>long_22_GPS</b>: NA (Field type: longitude)</li><li><b>accuracy_22_GPS</b>: GPS accuracy level (Field type: numeric)</li><li><b>X23_Observer_initials</b>: Observer identity (Field type: id)</li><li><b>X24_Photo_of_plastic_</b>: Photo of bait station - photos stored online at Epicollect5 (Field type: id)</li><li><b>X25_Comments</b>: Any additional comments (Field type: comments)</li><li><b>Dead_mealworm_binary</b>: Dead mealworm presence (Field type: categorical)</li><li><b>Live_mealworm_binary</b>: Live mealworm presence (Field type: categorical)</li></ul></li></ol><p><b>Date range: </b>2019-02-04 to 2019-02-21</p><p><b>Latitudinal extent: </b>4.6876 to 4.7494</p><p><b>Longitudinal extent: </b>116.9558 to 117.6197</p>
Life Sciences dataset used in INFORE project, part 1
<p>Life Sciences dataset used in INFORE project, part 1</p> <p>The dataset comprises the output of several simulations of a model of tumor growth with different parameter values. The model is a multi-scale agent-based model of a tumor spheroid that is treated with periodic pulses of the cytokine tumor necrosis factor (TNF). The multi-scale model simulates processes including i) the diffusion, uptake, and secretion of molecular entities such as oxygen, or TNF; ii) the mechanical interaction between cells; and iii) cellular processes including cell life cycle, cell death models, signal transduction.</p> <p>The multi-scale model was implemented and simulated using the PhysiBoSS framework (Letort et al. 2019). The dataset corresponds to different examples of parameters combinations of our use case that correspond to the different panels of Figure 4 in Documentation folder. This figure comes from the paper in the same folder.<br> You can find a broad discussion of our use case in the Biological Use Case Documentation file. Also,<br> The results of the cell simulations can be found in example_XXX/run0/outputs. The results of the microenvironment simulations can be found in example_XXX/run0/microutputs.<br> Details on how these files are built can be found in Biological Use Case output format file (which is a snippet of the broad documentation file that I detached for your convenience). Briefly: each time step defined, the software writes an output and microutput file. For instance, ecm_t00030.txt correspond to time step 30. Each line of these files corresponds to a cell or microenvironment entity (oxygen, TNF, etc). Columns are defined by the first row for output folder. For the microutputs, the first three columns correspond to spatial coordinates and the fourth to the value of the density.</p> <p>The examples are:<br> - example_spheroid_TNF_nopulse: corresponds to Figure 4 A.<br> - example_spheroid_TNF_onepulse: corresponds to Figure 4 C.<br> - example_spheroid_TNF_pulse150: corresponds to Figure 4 D left. This is the simulation outcome desired: proliferative cells die out with increasing number of pulses of TNF.<br> - example_spheroid_TNF_pulse600: corresponds to Figure 4 D right.<br> - example_spheroid_TNF_pulsecont: corresponds to Figure 4 B.<br> - example_cells_with_ECM_mutants: does NOT correspond to Figure 4. This is an example in which microutput folder is full of two entities: oxygen and ECM. Also, in this example you can find a folder (ECM_mut) with the kind of visualisation that we perform to showcase results.<br> - example_spheroid_TNF_pulsecont_oxy: 21 simulations with slightly different oxygen tolerance conditions using as a base the simulation with one continuous pulse (Figure 4 B from the presentation).<br> The only difference among parameters file is the "oxygen_necrotic" value, which controls the threshold above which cells commit to necrosis due to lack of oxygen. In the original simulation this value was zero and the maximum available oxygen is 40 fg/µm^3. Here, we have studied the parameter value from 0 to 40 in steps of 5.</p>
Life Sciences dataset used in INFORE project, part 2
<p>Life Sciences dataset used in INFORE project, part 2</p> <p>The dataset comprises the output of several simulations of a model of tumor growth with different parameter values. The model is a multi-scale agent-based model of a tumor spheroid that is treated with periodic pulses of the cytokine tumor necrosis factor (TNF). The multi-scale model simulates processes including i) the diffusion, uptake, and secretion of molecular entities such as oxygen, or TNF; ii) the mechanical interaction between cells; and iii) cellular processes including cell life cycle, cell death models, signal transduction.</p> <p>The multi-scale model was implemented and simulated using the PhysiBoSS framework (Letort et al. 2019). The dataset corresponds to different examples of parameters combinations of our use case that correspond to the different panels of Figure 4 in Documentation folder. This figure comes from the paper in the same folder.<br> You can find a broad discussion of our use case in the Biological Use Case Documentation file. Also,<br> The results of the cell simulations can be found in example_XXX/run0/outputs. The results of the microenvironment simulations can be found in example_XXX/run0/microutputs.<br> Details on how these files are built can be found in Biological Use Case output format file (which is a snippet of the broad documentation file that I detached for your convenience). Briefly: each time step defined, the software writes an output and microutput file. For instance, ecm_t00030.txt correspond to time step 30. Each line of these files corresponds to a cell or microenvironment entity (oxygen, TNF, etc). Columns are defined by the first row for output folder. For the microutputs, the first three columns correspond to spatial coordinates and the fourth to the value of the density.</p> <p>The examples are:<br> - example_spheroid_TNF_nopulse: corresponds to Figure 4 A.<br> - example_spheroid_TNF_onepulse: corresponds to Figure 4 C.<br> - example_spheroid_TNF_pulse150: corresponds to Figure 4 D left. This is the simulation outcome desired: proliferative cells die out with increasing number of pulses of TNF.<br> - example_spheroid_TNF_pulse600: corresponds to Figure 4 D right.<br> - example_spheroid_TNF_pulsecont: corresponds to Figure 4 B.<br> - example_cells_with_ECM_mutants: does NOT correspond to Figure 4. This is an example in which microutput folder is full of two entities: oxygen and ECM. Also, in this example you can find a folder (ECM_mut) with the kind of visualisation that we perform to showcase results.<br> - example_spheroid_TNF_pulsecont_oxy: 21 simulations with slightly different oxygen tolerance conditions using as a base the simulation with one continuous pulse (Figure 4 B from the presentation).<br> The only difference among parameters file is the "oxygen_necrotic" value, which controls the threshold above which cells commit to necrosis due to lack of oxygen. In the original simulation this value was zero and the maximum available oxygen is 40 fg/µm^3. Here, we have studied the parameter value from 0 to 40 in steps of 5.</p>
Introduction to CESSDA's Metadata Office Project
<p>This video presents the CESSDA Metadata Office Project.</p> <p> </p> <p>The video is also available for <a href="https://youtu.be/k-1yaH18h8g">viewing on Youtube</a>.</p>
Core SAFE project small mammal trapping data
<b>Description: </b><p>This is the combined dataset for the SAFE project's core small mammal trapping programme, which was run from 2011-2014 by O.R. Wearn, from 2015-2017 by P. M. Chapman, and from 2018-2019 by S. Heon. In total, trapping grids have been run at 30 sites across the SAFE landscape and control areas, covering blocks D, E, F, OG1, OG2, OG3 and OP2. However, since 2014 trapping has been limited to 12 standard permanent grids which are resampled annually: two in D (the 100ha fragment site), six in E (two each in the 1, 10 and 100ha sites), two in OG2 at the Maliau Basin Conservation area and two in OP2 at the Selangan Batu Oil Palm estate. In 2018, 2 new mammal grids were added : Dmatrix-1 and Ematrix-1 grid. The following grids were dropped E1-1, E10-1, E100-1 and D100-1, while D1-2 and D10-2 were sampled. In 2019, OG2-N, trap lines 1-8 were not accessible due to a massive landslide. In replacement, lines 47-56 were added to the trap grid for OG2-N. trapping grids Dmatrix-2 and Ematrix-2 were also added. All the new grids are reflected on the locations sheet. One standard annual sampling session comprises 96 traps run for seven nights, and the first sheet in the dataset ("Deployment") records this as 672 rows detailing the basic outcome of each trap night in the sampling session. There are several grids which form exceptions to this trapping pattern; details of these are recorded in the metadata. The subsequent two sheets (Corrected_Trapping_Data and Raw_Trapping_Data) form a more detailed record of captured animals. These sheets have the non-capture rows removed, along with most of the basic trap location and state data; however they can easily be linked back to the relevant rows in "Deployment" by the date and the unique trap identifier. At first capture, all possible details of captured animals are recorded, including age, sex, biometric measurements, crude estimates of parasite load, and the ID of any associated samples. All animals captured in good health were fitted with a Passive Integrated Transponder (PIT) Tag so the unique 10-digit alphanumeric number associated with each PIT tag is also recorded. Upon recapture, the animals are merely weighed and the PIT tag number and trap location recorded; this is partly to save time and partly to avoid unneccessary repeat anaesthesia. In 2018, Prevost's squirrel with the species code PVSQ was added into the species list. <br>The entire dataset from 2011-2017 was extensively error-checked by PMC in 2018, then from 2018-2019 by SH with many errors identified, recorded, and where possible, rectified. These errors are most frequently duplications or typos in the PIT tag string. Where these errors are unresolvable, the true unique ID of the individual is no longer certain, and its independence from other individuals cannot be guaranteed. These records will require omitting from most analyses. The detailed dataset with capture data is therefore presented in both its raw and corrected forms. ("Raw_Trapping_Data" and "Corrected_Trapping_Data", respectively). In the corrected datasheet, all the resolvable errors have been corrected, with a brief note made of what was done and why. Notes have also been added to irresolvable errors briefly explaining the problem, and recommending omission from analyses where appropriate. We strongly recommend that all users rely on the corrected version; however we also include the raw data for completeness. In 2018, an additional sheet - general site information details was added</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/140"><b>The impacts of tropical forest fragmentation on dispersal behaviour of mammal communities</b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3955050">here</a></p><p><b>Files: </b>This consists of 1 file: SAFE_Core_Small_Mammal_Data_V3_2019_ROB_SUI.xlsx</p><p><b>SAFE_Core_Small_Mammal_Data_V3_2019_ROB_SUI.xlsx</b></p><p>This file contains dataset metadata and 4 data tables:</p><ol><li><p><b>Basic trap outcome data</b> (described in worksheet Deployment)</p><p>Description: This is the basic trapping data covering the outcome of every trap night since the start of the study in 2011. It comprises merely the location and date information for the trap, the person who was responsible for baiting it, the state of the trap and bait on checking, any invertebrates captured, the number of small mammal captures (generally 0 or 1, but occasionally 2) and any notes pertaining to the trap itself.</p><p>Number of fields: 15</p><p>Number of data rows: 71123</p><p>Fields: </p><ul><li><b>Grid-Session-Occasion</b>: An identifier for the individual trapping day ("occasion") within a sampling year ("session"). This nomenclature originates from applying Spatially Explicit Capture-Recapture models to this data, however experience suggests this is the most concise, intuitive way of referring to a particular day of trapping (rather than using the actual date). This is applied to all grids which were trapped in the standard pattern of 96 traps run for seven consecutive days. There are five exceptions: OG2-E in 2011, D100-2 in 2011, D100-1 in 2012, F100-1 in 2012, and F100-2 in 2012. These were all trapped in a non-standard pattern (either total trapping effort ≠ 96 traps and 7 days, or there were gaps etween days such that the total trapped duration > 7 days). These exceptions are given NA (Field type: id)</li><li><b>Date</b>: The calendar date of trapping (Field type: date)</li><li><b>Block</b>: The SAFE sampling block (Field type: categorical)</li><li><b>Fragment</b>: The fragment (SAFE landscape; 1, 10, or 100ha) or sub-block (control sites; e.g. OP2, OG1, etc) of the sampling session. (Field type: id)</li><li><b>Grid</b>: The grid of the sampling session. There are two grids (1 and 2, numered outwards from the centre of the lock) in each fragment in the SAFE design, and three in each su-block in the control sites (North, East and West). (Field type: id)</li><li><b>Point</b>: The camera trap/small mammal sampling point where the trap was located. (Field type: id)</li><li><b>Trap</b>: The trap identifier (two traps, A and B, are located within a 5m radius of each sampling point) (Field type: id)</li><li><b>Unique_Point_ID</b>: Unique identifier for the sampling point (corresponds to the Locations sheet, and the locations in the Gazeteer) (Field type: location)</li><li><b>Unique_Trap_ID</b>: Unique identifier for the individual trap. (Field type: id)</li><li><b>State</b>: The state of the trap when checked. (Field type: categorical)</li><li><b>Bait</b>: The state of the bait when checked. (Field type: categorical)</li><li><b>Invertebrates</b>: Comments on any invertebrates found; in particular the presence of ants is frequently recorded, as these can be a severe danger to small mammals. (Field type: comments)</li><li><b>Capture_N</b>: Number of small mammals caught. This is almost invarialy zero or one, however very occasionally two are caught together. Models such as Spatially Explicit Capture Recapture treat small mammal traps as "single-catch" traps, and the model is violated y these occasions - so they are worth flagging up. (Field type: numeric)</li><li><b>Who_baited</b>: Person who baited the trap (Field type: comments)</li><li><b>Other_Notes</b>: Original supplementary field notes on the trap outcome or the animal captured. On the "Deployment" sheet this column has Been trimmed to only include notes covering the placement and condition of the traps - with notes pertaining to captured animals removed. (Field type: comments)</li></ul></li><li><p><b>Corrected trapping data</b> (described in worksheet Corrected_Trapping_Data)</p><p>Description: This is the modified, corrected version of the detailed trapping data covering all the small mammal captures from 2011 (i.e. blank rows are removed). It is directly based on the raw trapping data, however it has been fully verified, with all rectifiable errors corrected. Extra columns are included to: 1.) display any corrections to species ID and PIT tag ID of an individual record, 2.) explain the reason for corrections applied, or any unresolvable errors, and 3.) recommend a record for omission from analyses, where appropriate.</p><p>Number of fields: 36</p><p>Number of data rows: 8101</p><p>Fields: </p><ul><li><b>Grid-Session-Occasion</b>: An identifier for the individual trapping day ("occasion") within a sampling year ("session"). This nomenclature originates from applying Spatially Explicit Capture-Recapture models to this data, however experience suggests this is the most concise, intuitive way of referring to a particular day of trapping (rather than using the actual date). This is applied to all grids which were trapped in the standard pattern of 96 traps run for seven consecutive days. There are five exceptions: OG2-E in 2011, D100-2 in 2011, D100-1 in 2012, F100-1 in 2012, and F100-2 in 2012. These were all trapped in a non-standard pattern (either total trapping effort ≠ 96 traps and 7 days, or there were gaps between days such that the total trapped duration > 7 days). These exceptions are given NA (Field type: id)</li><li><b>Date</b>: The calendar date of trapping (Field type: date)</li><li><b>Unique_Point_ID</b>: Unique identifier for the sampling point (corresponds to the Locations sheet, and the locations in the Gazeteer) (Field type: location)</li><li><b>Unique_Trap_ID</b>: Unique identifier for the individual trap. (Field type: id)</li><li><b>Species</b>: Raw species ID for the captured animal. All "target" small mammals receive an identifying code for brevity (see the Taxa sheet) while occasional caputures of "non-target" taxa (larger mammals, other vertebrates) are referred to in full. Fully unknown small mammal species are referred to as "Unknown". (Field type: taxa)</li><li><b>Species_Validated</b>: Corrected, verified species ID for the captured animal. This should be used in preference to "Species" as any misidentifications have been amended. Codes follow those in the "Raw Taxon" column (Field type: taxa)</li><li><b>Species_Uncertainty</b>: Indicates uncertainty around the species identification (after correction). Species IDs are not alwaysCERtain, especially in the case of aberrant individuals, cryptic species or complexes such as Rattus, or heavily scavenged dead indivuduals. (Field type: categorical)</li><li><b>New/Recapture</b>: Indicates whether the individual is a new record or a recapture. NB: Biometric data (apart from weight) is not collected for recaptures for reasons of time and ethics (unnecessary anaesthesia). (Field type: categorical)</li><li><b>PIT_Tag/ID</b>: Raw individual ID for the captured animal. This is usually a 10-digit numeric or alphanumeric string, the number of the fitted Passive Integrated Transponder (PIT) tag. All zeros in PIT strings are replaced with capital Os due to persistent problems with Excel irreversibly modifying particular string formats (these errors are included in this raw data). Various other "generic" individual IDs have been applied to occasional animals which were untagged but somehow deemed to be otherwise identifiable. The format and use of these varies between fieldworkers and has not been standardised here in this raw verson. (Field type: id)</li><li><b>PIT_Tag/ID_Validated</b>: Corrected, validated individual ID for the captured small mammal. This should be used in preference to "PIT_Tag/ID" as resolvable errors have been amended. In some occasional cases this ID does not correspond to the (corrected) PIT tag string. In these cases a standardised generic ID was applied, generally under two possible conditions: 1.) The individual was released alive without tagging but there is effectively no chance of recapture (such as an animal on the last day of trapping in an isolated block which was not trapped subsequently). 2.) The animal was a new, untagged individual found dead in the trap. Case 1: individuals recieve an identifier comprised of the species code and a unique three-digit number e.g. "WH001". Case 2: Individuals recieve a unique two-digit number preceded by "NewDead". (Field type: id)</li><li><b>Age</b>: Age of the individual captured. Uncertain ages are given with question marks. Completely unknown or unrecorded age are given as NA. (Field type: categorical trait)</li><li><b>Sex</b>: Sex of the individual captured. Uncertain sexes are given with question marks. Completely unknown or unrecorded sexes are given as NA. (Field type: categorical trait)</li><li><b>Sexing_Notes</b>: Notes on criteria used for sexing. (Field type: comments)</li><li><b>HF</b>: (Left) Hind foot measurement (Field type: numeric trait)</li><li><b>E</b>: (Left) Ear length measurement (only rats) (Field type: numeric trait)</li><li><b>AGD</b>: Ano-genital distance measurement (only rats) (Field type: numeric trait)</li><li><b>HB</b>: Head-body length measurement (only treeshrews, squirrels and some rat species where ID is uncertain) (Field type: numeric trait)</li><li><b>T</b>: Tail length measurement (only treeshrews, squirrels and some rat species where ID is uncertain) (Field type: numeric trait)</li><li><b>T_%_of_HB</b>: Tail length as a percentage of body head-body length (Field type: numeric trait)</li><li><b>MZ</b>: Muzzle length measurement (only treeshrews) (Field type: numeric trait)</li><li><b>Bag_W</b>: Mass of the polythene weighing bag (Field type: numeric)</li><li><b>Gross_W</b>: Mass of the polythene weighing bag including animal (Field type: numeric)</li><li><b>Net_W</b>: Mass of the animal (Field type: numeric)</li><li><b>Parasite_Count</b>: Approximate ectoparasite load: rough visual count of the number of fur mites and other ectoparasites shed within the anaesthesia pot during anaesthesia (Field type: numeric trait)</li><li><b>Body_Fat</b>: Body fat score: a nine-level categorical score. Only applied from 2017 onwards. (Field type: categorical trait)</li><li><b>Injuries</b>: Description of any injuries or visible signs of diease to the captured small mammal. (Field type: comments)</li><li><b>Dead</b>: Was the individual found dead, or euthanised in the course of processing? (Field type: categorical trait)</li><li><b>Tissue_Sample_ID</b>: Identifier for any tissue samples taken (rats only, from the right ear) (Field type: id)</li><li><b>Parasite_Sample_ID</b>: Identifier for any parasite samples taken (Field type: id)</li><li><b>Fur_sample_ID</b>: Identifier for any fur samples taken (Field type: id)</li><li><b>Faecal_Sample_1_ID</b>: Identifier for any faecal samples taken (for first investigator) (Field type: id)</li><li><b>Faecal_Sample_2_ID</b>: Identifier for any faecal samples taken (for second investigator) (Field type: id)</li><li><b>Processor</b>: Person who processed the animal (Field type: comments)</li><li><b>Omit</b>: Identifies individuals which should be omitted from all analyses ("Y") or some analyses ("SA") due to data errors (Field type: categorical)</li><li><b>Correction_Notes</b>: Comments on any corrections made or reasoning for suggesting omissions in "Omit". Omissions are usually due to the individual ID or species ID of a capture being uncertain. Several common omission reasons are recorded with standard prhases in capitals for clarity: these include escapes, animals released untagged for various reasons (including non-target captures), and dead individuals where species identification was impossible or where it was uncertain if the individual was new or a recapture. More complex cases are discussed individually. (Field type: comments)</li><li><b>Other_Notes</b>: Original supplementary field notes on the trap outcome or the animal captured. This column includes supporting notes for ID, descriptions of the circumstances of a death, admissions of missing data, etc etc. These have not been error-checked or modified. (Field type: comments)</li></ul></li><li><p><b>Raw trapping data</b> (described in worksheet Raw_Trapping_Data)</p><p>Description: This is the unmodified, raw version of the detailed trapping data, covering all the small mammal sampling from 2011 (i.e. blank rows are removed). It is included for information only and we do not recommend that it is used.</p><p>Number of fields: 32</p><p>Number of data rows: 8101</p><p>Fields: </p><ul><li><b>Grid-Session-Occasion</b>: An identifier for the individual trapping day ("occasion") within a sampling year ("session"). This nomenclature originates from applying Spatially Explicit Capture-Recapture models to this data, however experience suggests this is the most concise, intuitive way of referring to a particular day of trapping (rather than using the actual date). This is applied to all grids which were trapped in the standard pattern of 96 traps run for seven consecutive days. There are five exceptions: OG2-E in 2011, D100-2 in 2011, D100-1 in 2012, F100-1 in 2012, and F100-2 in 2012. These were all trapped in a non-standard pattern (either total trapping effort ≠ 96 traps and 7 days, or there were gaps between days such that the total trapped duration > 7 days). These exceptions are given NA (Field type: id)</li><li><b>Date</b>: The calendar date of trapping (Field type: date)</li><li><b>Unique_Point_ID</b>: Unique identifier for the sampling point (corresponds to the Locations sheet, and the locations in the Gazeteer) (Field type: location)</li><li><b>Unique Trap ID</b>: Unique identifier for the individual trap. (Field type: id)</li><li><b>Species</b>: Raw species ID for the captured animal. All "target" small mammals receive an identifying code for brevity (see the Taxa sheet) while occasional captures of "non-target" taxa (larger mammals, other vertebrates) are referred to in full. Fully unknown small mammal species are referred to as "Unknown". (Field type: taxa)</li><li><b>Species Uncertainty</b>: Indicates uncertainty around the species identification. Species IDs are not always certain, especially in the case of aberrant individuals, cryptic species or complexes such as Rattus, or heavily scavenged dead indivuduals. (Field type: categorical)</li><li><b>New/Recapture</b>: Indicates whether the individual is a new record or a recapture. NB: Biometric data (apart from weight) is not collected for recaptures for reasons of time and ethics (unnecessary anaesthesia). (Field type: categorical)</li><li><b>PIT_Tag/ID</b>: Raw individual ID for the captured animal. This is usually a 10-digit numeric or alphanumeric string, the number of the fitted Passive Integrated Transponder (PIT) tag. All zeros in PIT strings are replaced with capital Os due to persistent problems with Excel irreversibly modifying particular string formats (these errors are included in this raw data). Various other "generic" individual IDs have been applied to occasional animals which were untagged but somehow deemed to be otherwise identifiable. The format and use of these varies between fieldworkers and has not been standardised here in this raw dataset. (Field type: id)</li><li><b>Age</b>: Age of the individual captured. Uncertain ages are given with question marks. Completely unknown or unrecorded age are given as NA. (Field type: categorical trait)</li><li><b>Sex</b>: Sex of the individual captured. Uncertain sexes are given with question marks. Completely unknown or unrecorded sexes are given as NA. (Field type: categorical trait)</li><li><b>Sexing Notes</b>: Notes on criteria used for sexing. (Field type: comments)</li><li><b>HF</b>: (Left) Hind foot measurement (Field type: numeric trait)</li><li><b>E</b>: (Left) Ear length measurement (only rats) (Field type: numeric trait)</li><li><b>AGD</b>: Ano-genital distance measurement (only rats) (Field type: numeric trait)</li><li><b>HB</b>: Head-body length measurement (only treeshrews, squirrels and some rat species where ID is uncertain) (Field type: numeric trait)</li><li><b>T</b>: Tail length measurement (only treeshrews, squirrels and some rat species where ID is uncertain) (Field type: numeric trait)</li><li><b>T % of HB</b>: Tail length as a percentage of body head-body length (Field type: numeric trait)</li><li><b>MZ</b>: Muzzle length measurement (only treeshrews) (Field type: numeric trait)</li><li><b>Bag W</b>: Mass of the polythene weighing bag (Field type: numeric)</li><li><b>Gross W</b>: Mass of the polythene weighing bag including animal (Field type: numeric)</li><li><b>Net W</b>: Mass of the animal (Field type: numeric)</li><li><b>Parasite Count</b>: Approximate ectoparasite load: rough visual count of the number of fur mites and other ectoparasites shed within the anaesthesia pot during anaesthesia (Field type: numeric trait)</li><li><b>Body Fat</b>: Body fat score: a nine-level categorical score. Only applied from 2017 onwards. (Field type: categorical trait)</li><li><b>Injuries</b>: Description of any injuries or visible signs of diease to the captured small mammal. (Field type: comments)</li><li><b>Dead</b>: Was the individual found dead, or euthanised in the course of processing? (Field type: categorical trait)</li><li><b>Tissue Sample ID</b>: Identifier for any tissue samples taken (rats only, from the right ear) (Field type: id)</li><li><b>Parasite Sample ID</b>: Identifier for any parasite samples taken (Field type: id)</li><li><b>Fur sample ID</b>: Identifier for any fur samples taken (Field type: id)</li><li><b>Faecal Sample 1 ID</b>: Identifier for any faecal samples taken (for first investigator) (Field type: id)</li><li><b>Faecal Sample 2 ID</b>: Identifier for any faecal samples taken (for second investigator) (Field type: id)</li><li><b>Processor</b>: Person who processed the animal (Field type: comments)</li><li><b>Other Notes</b>: Original supplementary field notes on the trap outcome or the animal captured. This column includes supporting notes for ID, descriptions of the circumstances of a death, admissions of missing data, etc etc. These have not been error-checked or modified. (Field type: comments)</li></ul></li><li><p><b>Site deployment information</b> (described in worksheet Site_Deployment_Info)</p><p>Description: This sheet contains information about the weather condition, animal occurrences or human disturbances which may influence the live mammal trapping outcome during the course of the live trapping. It contains the grid information, trapping day, data, observers and the weather condition and if any general observations made about the grid on the trapping days. </p><p>Number of fields: 6</p><p>Number of data rows: 154</p><p>Fields: </p><ul><li><b>Location</b>: Grid-Session-Occasion (Field type: id)</li><li><b>Day</b>: Trapping day number (Field type: id)</li><li><b>Date</b>: Date of trap collection (Field type: date)</li><li><b>Observer</b>: Observer (Field type: comments)</li><li><b>Weather condition</b>: Weather notes (Field type: comments)</li><li><b>General Notes</b>: Other notes (Field type: comments)</li></ul></li></ol><p><b>Date range: </b>2011-05-12 to 2019-11-22</p><p><b>Latitudinal extent: </b>4.6429 to 4.7539</p><p><b>Longitudinal extent: </b>116.9471 to 117.5938</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Chordata <br> -  -  -  Aves <br> -  -  -  -  Cuculiformes <br> -  -  -  -  -  Cuculidae <br> -  -  -  -  -  -  <i>Centropus</i> <br> -  -  -  -  Passeriformes <br> -  -  -  -  -  Timaliidae <br> -  -  -  -  -  -  <i>Macronus</i> <br> -  -  -  -  -  -  -  <i>Macronus bornensis</i> <br> -  -  -  -  -  Pellorneidae <br> -  -  -  -  -  -  <i>Malacocincla</i> <br> -  -  -  -  -  -  -  <i>Malacocincla malaccensis</i> <br> -  -  -  -  -  Pittidae <br> -  -  -  -  -  -  <i>Pitta</i> <br> -  -  -  -  -  -  -  <i>Pitta arquata</i> <br> -  -  -  Mammalia <br> -  -  -  -  Rodentia <br> -  -  -  -  -  Sciuridae <br> -  -  -  -  -  -  <i>Callosciurus</i> <br> -  -  -  -  -  -  -  <i>Callosciurus adamsi</i> <br> -  -  -  -  -  -  -  <i>Callosciurus notatus</i> <br> -  -  -  -  -  -  -  <i>Callosciurus prevostii</i> <br> -  -  -  -  -  -  <i>Lariscus</i> <br> -  -  -  -  -  -  -  <i>Lariscus hosei</i> <br> -  -  -  -  -  -  <i>Sundasciurus</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus brookei</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus hippurus</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus lowii</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus tenuis</i> <br> -  -  -  -  -  Muridae <br> -  -  -  -  -  -  <i>Maxomys</i> <br> -  -  -  -  -  -  -  <i>Maxomys rajah</i> <br> -  -  -  -  -  -  -  <i>Maxomys ochraceiventer</i> <br> -  -  -  -  -  -  -  <i>Maxomys surifer</i> <br> -  -  -  -  -  -  -  <i>Maxomys baeodon</i> <br> -  -  -  -  -  -  <i>Rattus</i> <br> -  -  -  -  -  -  -  <i>Rattus tiomanicus</i> <br> -  -  -  -  -  -  -  <i>Rattus exulans</i> <br> -  -  -  -  -  -  -  <i>Rattus rattus</i> <br> -  -  -  -  -  -  <i>Sundamys</i> <br> -  -  -  -  -  -  -  <i>Sundamys muelleri</i> <br> -  -  -  -  -  -  <i>Niviventer</i> <br> -  -  -  -  -  -  -  <i>Niviventer cremoriventer</i> <br> -  -  -  -  -  -  <i>Chrotomys</i> <br> -  -  -  -  -  -  -  <i>Chrotomys whiteheadi</i> (as homotypic_synonym: <i>Maxomys whiteheadi</i>)<br> -  -  -  -  -  -  <i>Leopoldamys</i> <br> -  -  -  -  -  -  -  <i>Leopoldamys sabanus</i> <br> -  -  -  -  Carnivora <br> -  -  -  -  -  Viverridae <br> -  -  -  -  -  -  <i>Viverra</i> <br> -  -  -  -  -  -  -  <i>Viverra tangalunga</i> <br> -  -  -  -  -  Mustelidae <br> -  -  -  -  -  -  <i>Martes</i> <br> -  -  -  -  -  -  -  <i>Martes flavigula</i> <br> -  -  -  -  Erinaceomorpha <br> -  -  -  -  -  Erinaceidae <br> -  -  -  -  -  -  <i>Echinosorex</i> <br> -  -  -  -  -  -  -  <i>Echinosorex gymnura</i> <br> -  -  -  -  Scandentia <br> -  -  -  -  -  Tupaiidae <br> -  -  -  -  -  -  <i>Tupaia</i> <br> -  -  -  -  -  -  -  <i>Tupaia longipes</i> <br> -  -  -  -  -  -  -  <i>Tupaia minor</i> <br> -  -  -  -  -  -  -  <i>Tupaia tana</i> <br> -  -  -  -  -  -  -  <i>Tupaia gracilis</i> <br> -  -  -  -  -  -  -  <i>Tupaia dorsalis</i> <br> -  -  -  Reptilia <br> -  -  -  -  Squamata <br> -  -  -  -  -  Gekkonidae <br> -  -  -  -  -  Scincidae <br> -  -  -  -  -  Varanidae <br> -  -  -  -  -  -  <i>Varanus</i> <br></div><p></p>
DoeDat Camera Trap Project 1015223 (Meise Botanic Garden)
A project on the <a href="https://www.doedat.be">DoeDat platform</a> of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>. Footage of camera traps is offered to volunteers for identification of the animals visible, if any. This deposition is an archive of the images in this project as well as the transcription results formatted in Darwin Core.
DoeDat Camera Trap Project 3740971 (Meise Botanic Garden)
A project on the <a href="https://www.doedat.be">DoeDat platform</a> of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>. Footage of camera traps is offered to volunteers for identification of the animals visible, if any. This deposition is an archive of the images in this project as well as the transcription results formatted in Darwin Core.
DoeDat Camera Trap Project 1358915 (Meise Botanic Garden)
A project on the <a href="https://www.doedat.be">DoeDat platform</a> of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>. Footage of camera traps is offered to volunteers for identification of the animals visible, if any. This deposition is an archive of the images in this project as well as the transcription results formatted in Darwin Core.
ScienceDex guides
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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