# HG changeset patch # User ecology # Date 1725972627 0 # Node ID c65dd54f9807c14197f9ba84e5b9b8414b1c486c # Parent 559744b4c50c136aa5bf7e70d0013e0f9223b026 planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/EMLassemblyline commit 2d36dc964f548b5acbc43ffd78e51e6fc7dc80bb diff -r 559744b4c50c -r c65dd54f9807 annotations_template.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/annotations_template.R Tue Sep 10 12:50:27 2024 +0000 @@ -0,0 +1,81 @@ +#17/07/2024 +#Seguineau Pauline + +#Make annotation template +#Load packages + +library(EMLassemblyline) + +#Load arguments + +args = commandArgs(trailingOnly=TRUE) + +if(length(args)>0){ + prod <- args[1] + if (prod == "fr_scratch"){ + select <- args[2] + data_table <- args[3] + if(select == "data_table"){ + data_table <- args[3] + }else if(select == "other_entities"){ + other_entities <- args[3] + }else if(select == "both"){ + data_table <- args[3] + other_entities <- args[4]} + }else{ + eml <- args[2] + } +} + +#Transform arguments + +if(prod =="fr_scratch" && select == "both"){ + table = strsplit(data_table," ") + other = strsplit(other_entities," ") + +#Make templates to add annotations from scratch + + template_annotations( + path ="data_files/", + data.table = table[[1]], + other.entity = other[[1]]) + +}else if (prod == "fr_scratch" && select == "data_table"){ + + table = strsplit(data_table," ") + template_annotations( + path ="data_files/", + data.table = table[[1]]) + +}else if (prod == "fr_scratch" && select == "other_entities"){ + + other = strsplit(other_entities," ") + template_annotations( + path ="data_files/", + other.entity = other[[1]]) + +#Make templates to add annotations from EML file + +}else{ + template_annotations( + path= "data_files/", + eml = eml)} + + + + + + + + + + + + + + + + + + + diff -r 559744b4c50c -r c65dd54f9807 test-data/annotemp/abstract.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/annotemp/abstract.txt Tue Sep 10 12:50:27 2024 +0000 @@ -0,0 +1,1 @@ +The Dumont D’Urville sea located off George V and Adélie Land, is one of the better known East-Antarctic marine areas displaying a diversity of abiotic and physical parameters that have been shown to drive the distribution of marine organisms. The dataset presented here contributes to our understanding of these interactions, providing essential information for ongoing research and conservation efforts in this Antarctic ecosystem. This dataset presents a table containing abiotic and physical parameters specific to the Dumont D’Urville Sea and a Jupyter notebook to execute a R script in the ecoregionalization Galaxy workflow. The abiotic and physical parameters were first presented in the research article 'Predicting habitat preferences for Anthometrina adriani (Echinodermata) on the East Antarctic continental shelf' by Hemery et al. (2011). The jupyter notebook is dedicated to the pivot_wider function from the tidyr R package. 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+/ceamarc_env.tsv/Rugosity /dataTable/attribute ceamarc_env.tsv Rugosity contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Sand /dataTable/attribute ceamarc_env.tsv Sand contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Seaice_prod /dataTable/attribute ceamarc_env.tsv Seaice_prod contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Sili /dataTable/attribute ceamarc_env.tsv Sili contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Slope /dataTable/attribute ceamarc_env.tsv Slope contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Standcurmag /dataTable/attribute ceamarc_env.tsv Standcurmag contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Standsal /dataTable/attribute ceamarc_env.tsv Standsal contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Standtheta /dataTable/attribute ceamarc_env.tsv Standtheta contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/pivot_wider_jupytool_notebook.ipynb /otherEntity dataset pivot_wider_jupytool_notebook.ipynb is about http://purl.obolibrary.org/obo/IAO_0000136 +/Marc Eléaume /ResponsibleParty dataset Marc Eléaume is a http://www.w3.org/1999/02/22-rdf-syntax-ns#type Person https://schema.org/Person +/Marc Eléaume /ResponsibleParty dataset Marc Eléaume member of https://schema.org/memberOf +/Lenaïg G. Hemery /ResponsibleParty dataset Lenaïg G. Hemery is a http://www.w3.org/1999/02/22-rdf-syntax-ns#type Person https://schema.org/Person +/Lenaïg G. Hemery /ResponsibleParty dataset Lenaïg G. Hemery member of https://schema.org/memberOf +/Ben Galton-Fenzi /ResponsibleParty dataset Ben Galton-Fenzi is a http://www.w3.org/1999/02/22-rdf-syntax-ns#type Person https://schema.org/Person +/Ben Galton-Fenzi /ResponsibleParty dataset Ben Galton-Fenzi member of https://schema.org/memberOf +/Pauline Seguineau /ResponsibleParty dataset Pauline Seguineau is a http://www.w3.org/1999/02/22-rdf-syntax-ns#type Person https://schema.org/Person +/Pauline Seguineau /ResponsibleParty dataset Pauline Seguineau member of https://schema.org/memberOf +/Yvan Le Bras /ResponsibleParty dataset Yvan Le Bras is a http://www.w3.org/1999/02/22-rdf-syntax-ns#type Person https://schema.org/Person +/Yvan Le Bras /ResponsibleParty dataset Yvan Le Bras member of https://schema.org/memberOf diff -r 559744b4c50c -r c65dd54f9807 test-data/annotemp/annotations_template_3.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/annotemp/annotations_template_3.txt Tue Sep 10 12:50:27 2024 +0000 @@ -0,0 +1,32 @@ +id element context subject predicate_label predicate_uri object_label object_uri +/dataset /dataset eml dataset is about http://purl.obolibrary.org/obo/IAO_0000136 +/ceamarc_env.tsv /dataTable dataset ceamarc_env.tsv is about http://purl.obolibrary.org/obo/IAO_0000136 +/ceamarc_env.tsv/long /dataTable/attribute ceamarc_env.tsv long contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/lat /dataTable/attribute ceamarc_env.tsv lat contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Carbo /dataTable/attribute ceamarc_env.tsv Carbo contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Grav /dataTable/attribute ceamarc_env.tsv Grav contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Maxbearing /dataTable/attribute ceamarc_env.tsv Maxbearing contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Maxmagnit /dataTable/attribute ceamarc_env.tsv Maxmagnit contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Meancurmag /dataTable/attribute ceamarc_env.tsv Meancurmag contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Meansal /dataTable/attribute ceamarc_env.tsv Meansal contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Meantheta /dataTable/attribute ceamarc_env.tsv Meantheta contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Mud /dataTable/attribute ceamarc_env.tsv Mud contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Prof /dataTable/attribute ceamarc_env.tsv Prof contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Rugosity /dataTable/attribute ceamarc_env.tsv Rugosity contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Sand /dataTable/attribute ceamarc_env.tsv Sand contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Seaice_prod /dataTable/attribute ceamarc_env.tsv Seaice_prod contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Sili /dataTable/attribute ceamarc_env.tsv Sili contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Slope /dataTable/attribute ceamarc_env.tsv Slope contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Standcurmag /dataTable/attribute ceamarc_env.tsv Standcurmag contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Standsal /dataTable/attribute ceamarc_env.tsv Standsal contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/ceamarc_env.tsv/Standtheta /dataTable/attribute ceamarc_env.tsv Standtheta contains measurements of type http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType +/Marc Eléaume /ResponsibleParty dataset Marc Eléaume is a http://www.w3.org/1999/02/22-rdf-syntax-ns#type Person https://schema.org/Person +/Marc Eléaume /ResponsibleParty dataset Marc Eléaume member of https://schema.org/memberOf +/Lenaïg G. Hemery /ResponsibleParty dataset Lenaïg G. Hemery is a http://www.w3.org/1999/02/22-rdf-syntax-ns#type Person https://schema.org/Person +/Lenaïg G. Hemery /ResponsibleParty dataset Lenaïg G. Hemery member of https://schema.org/memberOf +/Ben Galton-Fenzi /ResponsibleParty dataset Ben Galton-Fenzi is a http://www.w3.org/1999/02/22-rdf-syntax-ns#type Person https://schema.org/Person +/Ben Galton-Fenzi /ResponsibleParty dataset Ben Galton-Fenzi member of https://schema.org/memberOf +/Pauline Seguineau /ResponsibleParty dataset Pauline Seguineau is a http://www.w3.org/1999/02/22-rdf-syntax-ns#type Person https://schema.org/Person +/Pauline Seguineau /ResponsibleParty dataset Pauline Seguineau member of https://schema.org/memberOf +/Yvan Le Bras /ResponsibleParty dataset Yvan Le Bras is a http://www.w3.org/1999/02/22-rdf-syntax-ns#type Person https://schema.org/Person +/Yvan Le Bras /ResponsibleParty dataset Yvan Le Bras member of https://schema.org/memberOf diff -r 559744b4c50c -r c65dd54f9807 test-data/annotemp/annotations_template_4.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/annotemp/annotations_template_4.txt Tue Sep 10 12:50:27 2024 +0000 @@ -0,0 +1,13 @@ +id element context subject predicate_label predicate_uri object_label object_uri +/dataset /dataset eml dataset is about http://purl.obolibrary.org/obo/IAO_0000136 +/pivot_wider_jupytool_notebook.ipynb /otherEntity dataset pivot_wider_jupytool_notebook.ipynb is about http://purl.obolibrary.org/obo/IAO_0000136 +/Marc Eléaume /ResponsibleParty dataset Marc Eléaume is a http://www.w3.org/1999/02/22-rdf-syntax-ns#type Person https://schema.org/Person +/Marc Eléaume /ResponsibleParty dataset Marc Eléaume member of https://schema.org/memberOf +/Lenaïg G. Hemery /ResponsibleParty dataset Lenaïg G. Hemery is a http://www.w3.org/1999/02/22-rdf-syntax-ns#type Person https://schema.org/Person +/Lenaïg G. Hemery /ResponsibleParty dataset Lenaïg G. Hemery member of https://schema.org/memberOf +/Ben Galton-Fenzi /ResponsibleParty dataset Ben Galton-Fenzi is a http://www.w3.org/1999/02/22-rdf-syntax-ns#type Person https://schema.org/Person +/Ben Galton-Fenzi /ResponsibleParty dataset Ben Galton-Fenzi member of https://schema.org/memberOf +/Pauline Seguineau /ResponsibleParty dataset Pauline Seguineau is a http://www.w3.org/1999/02/22-rdf-syntax-ns#type Person https://schema.org/Person +/Pauline Seguineau /ResponsibleParty dataset Pauline Seguineau member of https://schema.org/memberOf +/Yvan Le Bras /ResponsibleParty dataset Yvan Le Bras is a http://www.w3.org/1999/02/22-rdf-syntax-ns#type Person https://schema.org/Person +/Yvan Le Bras /ResponsibleParty dataset Yvan Le Bras member of https://schema.org/memberOf diff -r 559744b4c50c -r c65dd54f9807 test-data/annotemp/attributes_ceamarc_env.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/annotemp/attributes_ceamarc_env.txt Tue Sep 10 12:50:27 2024 +0000 @@ -0,0 +1,20 @@ +attributeName attributeDefinition class unit dateTimeFormatString missingValueCode missingValueCodeExplanation +long Longitude is a geographic coordinate that specifies the east–west position of a point numeric degree "" -9999 no data available +lat Latitude is a geographic coordinate that specifies the north–south position of a point. numeric degree "" -9999 no data available +Carbo Percentage of biogenic carbonate numeric percent "" -9999 no data available +Grav Percentage of gravel in the seabed numeric percent "" -9999 no data available +Maxbearing Maximum current bearing numeric radian "" -9999 no data available +Maxmagnit Maximum current magnitude numeric meterPerSecond "" -9999 no data available +Meancurmag Mean current magnitude numeric meterPerSecond "" -9999 no data available +Meansal Mean salinity of the sea numeric PSU "" -9999 no data available +Meantheta Mean temperature of the sea numeric degreeCelsius "" -9999 no data available +Mud Percentage of mud in the seabed numeric percent "" -9999 no data available +Prof Depth of the sea numeric meter "" -9999 no data available +Rugosity Rugosity of the seabed numeric dimensionless "" -9999 no data available +Sand Percentage of sand in the seabed numeric percent "" -9999 no data available +Seaice_prod Seaice production in meter per year numeric meterPerYear "" -9999 no data available +Sili Percentage of biogenic silica in the seabed numeric percent "" -9999 no data available +Slope Slope of the seabed numeric degree "" -9999 no data available +Standcurmag Current magnitude standard deviation numeric meterPerSecond "" -9999 no data available +Standsal Salinity standard deviation numeric PSU "" -9999 no data available +Standtheta Temperature standard deviation numeric degreeCelsius "" -9999 no data available diff -r 559744b4c50c -r c65dd54f9807 test-data/annotemp/ceamarc_env.tsv --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/annotemp/ceamarc_env.tsv Tue Sep 10 12:50:27 2024 +0000 @@ -0,0 +1,10 @@ +long lat Carbo Grav Maxbearing Maxmagnit Meancurmag Meansal Meantheta Mud Prof Rugosity Sand Seaice_prod Sili Slope Standcurmag Standsal Standtheta +139.22 -65.57 0.88 28.59 3.67 0.03 0.03 34.62 -0.13 22.72 -441 -9999 55.76 0.24 3.27 0.28 0.01 0.01 0.18 +139.22 -65.57 0.88 28.61 3.64 0.02 0.03 34.62 -0.13 22.48 -439 -9999 55.74 0.24 3.29 0.27 0.01 0.01 0.18 +139.23 -65.57 0.92 28.62 3.59 0.02 0.03 34.62 -0.14 22.25 -438 -9999 56.28 0.25 3.32 0.22 0.01 0.01 0.19 +139.24 -65.57 0.92 28.63 3.51 0.01 0.03 34.62 -0.14 21.95 -436 -9999 56.57 0.26 3.3 0.08 0.01 0.01 0.19 +139.24 -65.57 0.92 28.64 3.35 0.01 0.03 34.62 -0.14 21.7 -437 -9999 56.58 0.26 3.28 0.05 0.01 0.01 0.19 +139.25 -65.57 0.93 28.65 3 0.0096293305978179 0.03 34.62 -0.15 21.44 -436 -9999 56.63 0.26 3.26 0.29 0.01 0.01 0.19 +139.26 -65.57 0.93 28.63 2.49 0.00871255807578564 0.03 34.62 -0.15 21.11 -432 -9999 56.67 0.26 3.23 0.43 0.01 0.01 0.19 +139.26 -65.57 0.93 28.64 2.01 0.01 0.03 34.62 -0.16 20.83 -429 -9999 56.71 0.26 3.21 0.37 0.01 0.01 0.19 +139.27 -65.57 0.94 28.65 1.71 0.01 0.03 34.62 -0.16 20.55 -427 -9999 56.75 0.26 3.19 0.32 0.01 0.01 0.2 diff -r 559744b4c50c -r c65dd54f9807 test-data/annotemp/custom_units.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/annotemp/custom_units.txt Tue Sep 10 12:50:27 2024 +0000 @@ -0,0 +1,4 @@ +id unitType parentSI multiplierToSI description +PSU density gramPerGram 0.001 "1 PSU = 1g/kg" +degreeCelsius temperature dimensionless 1 "0 °C + 273,15 = 273,15 Kelvin" +meterPerYear speed centimeterPerYear 0.01 "meter per year" diff -r 559744b4c50c -r c65dd54f9807 test-data/annotemp/entities.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/annotemp/entities.txt Tue Sep 10 12:50:27 2024 +0000 @@ -0,0 +1,2 @@ +objectName variable value +pivot_wider_jupytool_notebook.ipynb entityType executable diff -r 559744b4c50c -r c65dd54f9807 test-data/annotemp/geographic_coverage.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/annotemp/geographic_coverage.txt Tue Sep 10 12:50:27 2024 +0000 @@ -0,0 +1,2 @@ +geographicDescription northBoundingCoordinate southBoundingCoordinate eastBoundingCoordinate westBoundingCoordinate +Dumont D'Urville sea sampling border -65.57 -67.01 145.53 139.22 diff -r 559744b4c50c -r c65dd54f9807 test-data/annotemp/intellectual_rights.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/annotemp/intellectual_rights.txt Tue Sep 10 12:50:27 2024 +0000 @@ -0,0 +1,1 @@ +This information is released under the Creative Commons license - Attribution - CC BY (https://creativecommons.org/licenses/by/4.0/). The consumer of these data ("Data User" herein) is required to cite it appropriately in any publication that results from its use. The Data User should realize that these data may be actively used by others for ongoing research and that coordination may be necessary to prevent duplicate publication. The Data User is urged to contact the authors of these data if any questions about methodology or results occur. Where appropriate, the Data User is encouraged to consider collaboration or co-authorship with the authors. The Data User should realize that misinterpretation of data may occur if used out of context of the original study. While substantial efforts are made to ensure the accuracy of data and associated documentation, complete accuracy of data sets cannot be guaranteed. All data are made available "as is." The Data User should be aware, however, that data are updated periodically and it is the responsibility of the Data User to check for new versions of the data. The data authors and the repository where these data were obtained shall not be liable for damages resulting from any use or misinterpretation of the data. Thank you. diff -r 559744b4c50c -r c65dd54f9807 test-data/annotemp/keywords.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/annotemp/keywords.txt Tue Sep 10 12:50:27 2024 +0000 @@ -0,0 +1,9 @@ +keyword keywordThesaurus +Antarctica "" +Southern Ocean "" +Dumont D'Urville sea "" +CEAMARC "" +Abiotic and physical parameters "" +Ecoregionalization "" +Jupyter notebook "" +Pivot wider function "" diff -r 559744b4c50c -r c65dd54f9807 test-data/annotemp/methods.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/annotemp/methods.txt Tue Sep 10 12:50:27 2024 +0000 @@ -0,0 +1,1 @@ +Abiotic and physical parameters in this dataset were taken from oceanographic model and in situ measurements (Hemery et al., 2011). Here we quote the relevant section of the “Materials and methods” part from the study: “Abiotic or physical parameters. Two different categories of abiotic parameters were used (Fig. 2): parameters likely to be subject to daily or seasonal variability (temperature, salinity, current magnitude, general current direction and sea-ice concentration) and parameters with long-term stability (bathymetry, slope, rugosity and seabed sediments). Parameters with short-term variability are taken from an oceanographic model, whereas parameters with long-term stability are derived from in situ measurements. Physical oceanography. Physical oceanographic parameters near the seabed (temperature, salinity, mean current magnitude, standard deviations of these 3 parameters, maximum current magnitude and general current direction) are taken from a climatologically forced ocean circulation model. The model was run for a total of 23 yr. A spinup phase of 20 yr was required for the model to reach quasi-equilibrium. The mean and SD were calculated by using 6-hourly model data for the last 3 yr. Sea ice growth rate was calculated directly from special sensor microwave imager (SSM/I) observations (Tamura et al. 2008). The model is based on the Rutgers/University of California Los Angeles Regional Ocean Model System (ROMS; Shchepetkin & McWilliams 2005) and is identical to the one described by B. K. Galton-Fenzi et al. (unpubl.). The model used here, initially developed for regional modelling studies of the Amery Ice Shelf/Ocean system and has been used in circum-Antarctic modelling studies, is able to simulate ice/ocean interactions at a high level of realism (Galton-Fenzi 2009, 2010). For the region of this study, the model is able to reproduce the circulation patterns and water mass properties when compared with oceanographic measurements taken in the vicinity of the George V and Adélie basins (A. Meijers pers. comm.). The model domain extends from 135.77° E to 158.08° E and from 69.417° S to 62.724° S. The southern boundary of the model is a closed, solid, free slip wall and the eastern and western boundaries are partially open. The horizontal grid resolution is between 2.16 km near the southern boundary to 2.88 km near the northern boundary. There are 31 vertical levels that are concentrated towards the top and bottom of the model domain. The parameters used here were taken from the lowest vertical level in the model that lies immediately adjacent to the seabed. The choice of mixing and advection schemes follows the choices that were successfully used by Dinniman et al. (2003, 2007) for studies of the shelf seas near the Ross Ice Shelf. The melting and freezing formulation uses the full 3-equation formulation and dynamics frazil ice model used in the studies of Galton-Fenzi (2009, 2010). Lateral boundary fields (potential temperature, salinity and currents) on the open boundaries are relaxed to monthly climatologies from ECCO2 (Menemenlis et al. 2008, Wunsch et al. 2009). Ten primary tidal constituents were added as a free-surface forcing. The tidal amplitudes and phase are calculated with a nonstandard ROMS subroutine, based on tidal information from the Proudman Oceanographic Laboratory (Murray 1964) and modified to be included within ROMS, yielding a standard tidal prediction. The bathymetry and the ice-draft information come from a version of R-TOPO (Timmermann et al. 2010) that was modified to include the high-resolution bathymetric data (outlined below, Beaman et al. 2011) and knowledge of the glacial ice drafts in the region (B. Legresy pers.comm.). The open ocean surface fluxes are modified by an imposed climatological sea-ice cover that includes polynyas, derived from SSM/I observations (Tamura et al. 2008). During summer, the Tamura et al. (2008) data are supplemented with open-water heat and salt fluxes by using the monthly climatologies from the NCEP-2 (Kanamitsu et al. 2002). Bathymetry and seabed sediments. A bathymetry model based on multibeam swath sonar and single beam bathymetry data was produced at about 250 m resolution for the study area (Beaman et al. 2011). A raster map of the slope gradient was generated from this bathymetry model by using ESRI ArcGIS 9.2 Spatial Analysis Tools and a raster map of the rugosity was generated by using Benthic Terrain Modeler tools. Sediment grabs provided substratum composition data, such as the percentage of gravel, mud, sand, biogenic carbonate and biogenic silica at sample sites (Beaman & O’Brien 2009). These data are used as a broad-scale representation of the seafloor substratum.” (Hemery et al., 2011). The Jupyter notebook file in this dataset was created with the Interactive JupyTool and the notebook Galaxy tool (https://ecology.usegalaxy.eu/root?tool_id=interactive_tool_jupyter_notebook). This Jupyter notebook script uses the pivot_wider function from the tidyr library to prepare data for the Ecoregionalization workflow. diff -r 559744b4c50c -r c65dd54f9807 test-data/annotemp/personnel.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/annotemp/personnel.txt Tue Sep 10 12:50:27 2024 +0000 @@ -0,0 +1,7 @@ +givenName middleInitial surName organizationName electronicMailAddress userId role projectTitle fundingAgency fundingNumber +Marc "" Eléaume Muséum National d'Histoire Naturelle marc.eleaume@mnhn.fr 0000-0003-1999-1177 creator "" "" "" +Marc "" Eléaume Muséum National d'Histoire Naturelle marc.eleaume@mnhn.fr 0000-0003-1999-1177 contact "" "" "" +Lenaïg G. Hemery Pacific Northwest National Laboratory Marine Sciences Laboratory lenaighemery@gmail.com,lenaig.hemery@pnnl.gov 0000-0001-5337-4514 creator "" "" "" +Ben "" Galton-Fenzi Australian Antarctic Division:Kingston, Tasmania, AU "" 0000-0003-1404-4103 creator "" "" "" +Pauline "" Seguineau Muséum National d'Histoire Naturelle pauline.seguineau@mnhn.fr 0009-0009-5969-8478 creator "" "" "" +Yvan "" Le Bras Muséum National d'Histoire Naturelle yvan.le-bras@mnhn.fr 0000-0002-8504-068X creator "" "" "" diff -r 559744b4c50c -r c65dd54f9807 test-data/annotemp/pivot_wider_jupytool_notebook.ipynb --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/annotemp/pivot_wider_jupytool_notebook.ipynb Tue Sep 10 12:50:27 2024 +0000 @@ -0,0 +1,85 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Pivot wider Jupytool " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This Jupyter notebook is dedicated to the pivot_wider function from the tidyr R package. \n", + "This script is the final part of the data preparation for the ecoregionalization Galaxy workflow. " + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "#Date : 22/05/2024\n", + "#Author : Seguineau Pauline & Yvan Le Bras \n", + "\n", + "#Load libraries\n", + "library(tidyr)\n", + "\n", + "#load file \n", + "\n", + "input_path = \"galaxy_inputs\"\n", + "\n", + "for (dir in list.dirs(input_path)){\n", + " for (file in list.files(dir)) {\n", + " file_path = file.path(dir, file)}\n", + "}\n", + "\n", + "file = read.table(file_path,header=T, sep = \"\\t\")\n", + "\n", + "#Run pivot_wider function\n", + "pivot_file = pivot_wider(data = file,\n", + " names_from = phylum_class_order_family_genus_specificEpithet,\n", + " values_from = individualCount,\n", + " values_fill = 0,\n", + " values_fn = sum)\n", + "\n", + "#Replace all occurences >= 1 by 1 to have only presence (1) or absence (0) data\n", + "for(c in 3:length(pivot_file)){\n", + " pivot_file[c][pivot_file[c]>=1] <- 1}\n", + "\n", + "\n", + "write.table(pivot_file, \"outputs/pivot_file.tabular\", sep = \"\\t\", quote = F, row.names = F)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In this Jupyter notebook, we used the pivot_wider function of the tidyr package to transform our data into a wider format and adapted to subsequent analyses as part of the Galaxy workflow for ecoregionalization. This transformation allowed us to convert our data to a format where each taxon becomes a separate column. We also took care to fill in the missing values with zeros and to sum the individual counts in case of duplications. Then all data >= 1 are replace by 1 to have only presence (1) or abscence (0) data.\n", + "\n", + "Thus, this notebook is an essential building block of our analysis pipeline, ensuring that the data is properly formatted and ready to be explored and interpreted for ecoregionalization studies." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "R", + "language": "R", + "name": "ir" + }, + "language_info": { + "codemirror_mode": "r", + "file_extension": ".r", + "mimetype": "text/x-r-source", + "name": "R", + "pygments_lexer": "r", + "version": "4.0.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff -r 559744b4c50c -r c65dd54f9807 test-data/test_geocov.tsv --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_geocov.tsv Tue Sep 10 12:50:27 2024 +0000 @@ -0,0 +1,5 @@ +site lat long +1 -65.999946 142.3360535 +2 -66.394359 140.4840125 +3 -66.023545 142.745584 +4 -66.3379125 144.011634 diff -r 559744b4c50c -r c65dd54f9807 vector_template.xml --- a/vector_template.xml Mon Jan 22 14:55:43 2024 +0000 +++ b/vector_template.xml Tue Sep 10 12:50:27 2024 +0000 @@ -52,10 +52,21 @@ **How to use it?** -------------------- + To use this tool, you need to select, in your history a data collection with your vector data file(s) (format GeoJSON). To do so, you can select the **Upload file** tool, select the *Collection* tab, upload all your templates, click on the *Start* button to integrate the files to Galaxy and then click on *Build*. You will need to choose a name and select *Create collection* to build a collection with your templates. You also can upload your files to Galaxy, select them in the history by clicking the *Select items* button, click on the newly appeared box on the right and select *Build dataset list*. To upload shapefile you need to create a composite data. .. class:: warningmark + '''TIP''' This tool dont accept as inputs composite data like shapefile at the moment. ]]> + + @Manual{, + title = {EMLassemblyline: A tool kit for building EML metadata workflows}, + author = {Colin Smith}, + year = {2022}, + note = {https://github.com/EDIorg/EMLassemblyline, + https://ediorg.github.io/EMLassemblyline/}, + } +