Execution du pipeline. Actualisation des dois et des graphes.

6738aaa1 · Elias Chetouane · e000dd7c · 6738aaa1 · 6738aaa1 · e000dd7c
Commit 6738aaa1 authored 1 year ago by Elias Chetouane
--- a/1-enrich-with-datacite/all_datacite_clients_for_uga.csv
+++ b/1-enrich-with-datacite/all_datacite_clients_for_uga.csv
 client,count,name,year,url
-cern.zenodo,723,Zenodo,2013,https://zenodo.org/
+cern.zenodo,724,Zenodo,2013,https://zenodo.org/
 inist.sshade,469,Solid Spectroscopy Hosting Architecture of Databases and Expertise,2019,https://www.sshade.eu/
 inist.osug,238,Observatoire des Sciences de l'Univers de Grenoble,2014,http://doi.osug.fr
 figshare.ars,232,figshare Academic Research System,2016,http://figshare.com/
-dryad.dryad,155,DRYAD,2018,https://datadryad.org
+dryad.dryad,156,DRYAD,2018,https://datadryad.org
 inist.resif,78,Réseau sismologique et géodésique français,2014,https://www.resif.fr/
 inist.persyval,55,PERSYVAL-Lab : Pervasive Systems and Algorithms Lab,2016,
 rdg.prod,43,Recherche Data Gouv France,2022,https://recherche.data.gouv.fr/en

--- a/1-enrich-with-datacite/nb-dois.txt
+++ b/1-enrich-with-datacite/nb-dois.txt
-2105
\ No newline at end of file
+2107
\ No newline at end of file
--- a/2-produce-graph/hist-evol-datasets-per-repo.png
+++ b/2-produce-graph/hist-evol-datasets-per-repo.png
--- a/2-produce-graph/hist-last-datasets-by-client.png
+++ b/2-produce-graph/hist-last-datasets-by-client.png
--- a/2-produce-graph/hist-quantity-year-type.png
+++ b/2-produce-graph/hist-quantity-year-type.png
--- a/2-produce-graph/pie--datacite-client.png
+++ b/2-produce-graph/pie--datacite-client.png
--- a/2-produce-graph/pie--datacite-type.png
+++ b/2-produce-graph/pie--datacite-type.png
--- a/dois-uga.csv
+++ b/dois-uga.csv
@@ -6012,3 +6012,18 @@ The calculations were carried out using t4gpd (https://pypi.org/project/t4gpd/).
 10.34847/nkl.c9e92or4,"Taciti et C. Velleii Paterculi scripta quae exstant; recognita, emaculata. Additique commentarii copiosissimi et notae non antea editae Paris e typographia Petri Chevalier, in monte diui Hilarii - II-0705",NAKALA - https://nakala.fr (Huma-Num - CNRS),2020,,Image,,,api,True,findable,0,0,0,0,0,2023-01-30T09:25:06.000Z,2023-01-30T09:25:06.000Z,inist.humanum,jbru,,,['53932108 Bytes'],['image/tiff']
 10.5281/zenodo.10794760,NeoGeographyToolkit/StereoPipeline: 2024-03-07-daily-build,Zenodo,2024,,Software,Creative Commons Attribution 4.0 International,Recent additions log: https://stereopipeline.readthedocs.io/en/latest/news.html,api,True,findable,0,0,0,0,0,2024-03-07T17:47:37.000Z,2024-03-07T17:47:38.000Z,cern.zenodo,cern,,,,
 10.34847/nkl.b1cb3arm,"Taciti et C. Velleii Paterculi scripta quae exstant; recognita, emaculata. Additique commentarii copiosissimi et notae non antea editae Paris e typographia Petri Chevalier, in monte diui Hilarii - II-0689",NAKALA - https://nakala.fr (Huma-Num - CNRS),2020,,Image,,,api,True,findable,0,0,0,0,0,2023-01-17T17:24:40.000Z,2023-01-17T17:24:41.000Z,inist.humanum,jbru,,,['52872938 Bytes'],['image/tiff']
+10.5061/dryad.83bk3jb0h,Land use and land cover scenarios for the Maurienne valley (French Alps) at 2085 horizon produced using CLUMPY model,Dryad,2024,en,Dataset,Creative Commons Zero v1.0 Universal,"We built three contrasted future LULC scenarios from 2020 to 2085 with the
+ CLUMPY model (Mazy and Longaretti, 2022). The CLUMPY model is an
+ innovative model of land use and land cover change comprising a
+ calibration-estimation module separate from a non-biased allocation
+ module. It is calibrated by using time series of past LULC maps (Mazy and
+ Longaretti, 2022). The model then calculates transition probabilities for
+ each LULC class according to relevant spatial explanatory variables. Next,
+ the model can produce maps of future LULC distributions according to
+ information it learned during the calibration-estimation phase. This model
+ has the benefits of being easy to use, proposing nonbiased allocation
+ methods and producing scenarios of future LULC change either by adjusting
+ manually the matrix of LULC transitions probabilities (used for the
+ Conservation and Tourism scenarios) or by training the model on specific
+ areas of the past time series (only used for the Conservation scenario).",mds,True,findable,0,0,0,0,0,2024-03-08T13:28:51.000Z,2024-03-08T13:28:52.000Z,dryad.dryad,dryad,"LULC,modelling,Alps,scenarios,FOS: Earth and related environmental sciences,FOS: Earth and related environmental sciences","[{'subject': 'LULC'}, {'subject': 'modelling'}, {'subject': 'Alps'}, {'subject': 'scenarios'}, {'subject': 'FOS: Earth and related environmental sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['307008659 bytes'],
+10.5281/zenodo.10801510,NeoGeographyToolkit/StereoPipeline: 2024-03-10-daily-build,Zenodo,2024,,Software,Creative Commons Attribution 4.0 International,Recent additions log: https://stereopipeline.readthedocs.io/en/latest/news.html,api,True,findable,0,0,0,1,0,2024-03-10T09:19:59.000Z,2024-03-10T09:19:59.000Z,cern.zenodo,cern,,,,