diff --git a/1-enrich-with-datacite/all_datacite_clients_for_uga.csv b/1-enrich-with-datacite/all_datacite_clients_for_uga.csv
index c3931c13b0674421fef5e2324e77c6f7286a013e..a03432aeff8218be8724868f323dc3c76b7d2db7 100644
--- a/1-enrich-with-datacite/all_datacite_clients_for_uga.csv
+++ b/1-enrich-with-datacite/all_datacite_clients_for_uga.csv
@@ -1,33 +1,33 @@
 client,count,name,year,url
-cern.zenodo,784,Zenodo,2013,https://zenodo.org/
+cern.zenodo,793,Zenodo,2013,https://zenodo.org/
 inist.sshade,496,Solid Spectroscopy Hosting Architecture of Databases and Expertise,2019,https://www.sshade.eu/
 figshare.ars,359,figshare Academic Research System,2016,http://figshare.com/
 inist.osug,238,Observatoire des Sciences de l'Univers de Grenoble,2014,http://doi.osug.fr
 dryad.dryad,163,DRYAD,2018,https://datadryad.org
 inist.resif,93,Réseau sismologique et géodésique français,2014,https://www.resif.fr/
+rdg.prod,65,Recherche Data Gouv France,2022,https://recherche.data.gouv.fr/en
 inist.humanum,65,NAKALA,2020,https://nakala.fr
-rdg.prod,64,Recherche Data Gouv France,2022,https://recherche.data.gouv.fr/en
 inist.persyval,61,PERSYVAL-Lab : Pervasive Systems and Algorithms Lab,2016,
 fmsh.prod,28,Fondation Maison des sciences de l'homme,2023,
 mcdy.dohrmi,12,dggv-e-publications,2020,https://www.dggv.de/publikationen/dggv-e-publikationen.html
+pangaea.repository,7,PANGAEA,2020,https://www.pangaea.de/
 figshare.sage,6,figshare SAGE Publications,2018,
 iris.iris,5,Incorporated Research Institutions for Seismology,2018,http://www.iris.edu/hq/
-tib.repod,3,RepOD,2015,https://repod.icm.edu.pl/
 tib.gfzbib,3,GFZpublic,2011,https://gfzpublic.gfz-potsdam.de
+cnic.sciencedb,3,ScienceDB,2022,https://www.scidb.cn/en
 vqpf.dris,3,Direction des ressources et de l'information scientifique,2021,
-pangaea.repository,3,PANGAEA,2020,https://www.pangaea.de/
+tib.repod,3,RepOD,2015,https://repod.icm.edu.pl/
+inist.eost,2,Ecole et Observatoire des Sciences de la Terre,2017,https://eost.unistra.fr/en/
 ugraz.unipub,2,unipub,2019,http://unipub.uni-graz.at
-bl.nerc,2,NERC Environmental Data Service,2011,https://eds.ukri.org
 ethz.sed,2,"Swiss Seismological Service, national earthquake monitoring and hazard center",2013,http://www.seismo.ethz.ch
-cnic.sciencedb,2,ScienceDB,2022,https://www.scidb.cn/en
-crui.ingv,1,Istituto Nazionale di Geofisica e Vulcanologia (INGV),2013,http://data.ingv.it/
+bl.nerc,2,NERC Environmental Data Service,2011,https://eds.ukri.org
 ethz.zora,1,"Universität Zürich, ZORA",2013,https://www.zora.uzh.ch/
 inist.ird,1,IRD,2016,
 estdoi.ttu,1,TalTech,2019,https://digikogu.taltech.ee
 repod.dbuw,1,University of Warsaw Research Data Repository,2023,https://danebadawcze.uw.edu.pl/
 tug.openlib,1,TU Graz OPEN Library,2020,https://openlib.tugraz.at/
+crui.ingv,1,Istituto Nazionale di Geofisica e Vulcanologia (INGV),2013,http://data.ingv.it/
 ethz.da-rd,1,ETHZ Data Archive - Research Data,2013,http://data-archive.ethz.ch
-inist.eost,1,Ecole et Observatoire des Sciences de la Terre,2017,https://eost.unistra.fr/en/
 inist.opgc,1,Observatoire de Physique du Globe de Clermont-Ferrand,2017,
 inist.omp,1,Observatoire Midi-Pyrénées,2011,
 ihumi.pub,1,IHU Méditerranée Infection,2020,
diff --git a/1-enrich-with-datacite/nb-dois.txt b/1-enrich-with-datacite/nb-dois.txt
index 1014e4e4eee83512f29a17f20d2f80df6eef3065..1c9d6bd480b8f617fe364c3824b54d239b5db058 100644
--- a/1-enrich-with-datacite/nb-dois.txt
+++ b/1-enrich-with-datacite/nb-dois.txt
@@ -1 +1 @@
-2411
\ No newline at end of file
+2427
\ No newline at end of file
diff --git a/2-produce-graph/hist-evol-datasets-per-repo.png b/2-produce-graph/hist-evol-datasets-per-repo.png
index f40e703d6d421f847de15c5e5e07d7b93cc0345a..74676243ddf1c5f215795c51a3c95c48db43f278 100644
Binary files a/2-produce-graph/hist-evol-datasets-per-repo.png and b/2-produce-graph/hist-evol-datasets-per-repo.png differ
diff --git a/2-produce-graph/hist-last-datasets-by-client.png b/2-produce-graph/hist-last-datasets-by-client.png
index 20a9d5119d003ac7b0efc9446cf2b4be0fe2e661..ba85de981cc40dd70dc6649a567845e00f54be1b 100644
Binary files a/2-produce-graph/hist-last-datasets-by-client.png and b/2-produce-graph/hist-last-datasets-by-client.png differ
diff --git a/2-produce-graph/hist-quantity-year-type.png b/2-produce-graph/hist-quantity-year-type.png
index 1802e96e39e560d4faa9aae6cfcddd6b9bc8b4ff..c7e2f96b802da2f4ebe3a32f469158d6df732821 100644
Binary files a/2-produce-graph/hist-quantity-year-type.png and b/2-produce-graph/hist-quantity-year-type.png differ
diff --git a/2-produce-graph/pie--datacite-client.png b/2-produce-graph/pie--datacite-client.png
index f8950b7630351d48aa23a3c25a2f86c6796931c7..ae7e3b3e4f60ee0728171c662ae606c29dc02dec 100644
Binary files a/2-produce-graph/pie--datacite-client.png and b/2-produce-graph/pie--datacite-client.png differ
diff --git a/2-produce-graph/pie--datacite-type.png b/2-produce-graph/pie--datacite-type.png
index c56140e22d803fddf222843e288d063c08154d3e..137c318fff3d2cca35179bb2d1f66f9ad8e0d72a 100644
Binary files a/2-produce-graph/pie--datacite-type.png and b/2-produce-graph/pie--datacite-type.png differ
diff --git a/dois-uga--last-500.csv b/dois-uga--last-500.csv
index 6b42bba27237e71436f249acd3fd30b781d72b29..5a055bfca551c9c34d3cbabb313497fc4043a578 100644
--- a/dois-uga--last-500.csv
+++ b/dois-uga--last-500.csv
@@ -1,4 +1,18 @@
 doi,client,resourceTypeGeneral,created,publisher,rights,sizes
+10.57760/sciencedb.16149,cnic.sciencedb,Dataset,2024-11-04,Science Data Bank,Creative Commons Attribution Non Commercial 4.0 International,"['2433253276 bytes', '4 files']"
+10.5281/zenodo.14003384,cern.zenodo,Dataset,2024-11-01,Zenodo,Creative Commons Attribution 4.0 International,
+10.5281/zenodo.14016979,cern.zenodo,Other,2024-10-31,Zenodo,Creative Commons Attribution 4.0 International,
+10.5281/zenodo.14016634,cern.zenodo,Other,2024-10-31,Zenodo,Creative Commons Attribution 4.0 International,
+10.5281/zenodo.14013195,cern.zenodo,Dataset,2024-10-30,Zenodo,Creative Commons Attribution 4.0 International,
+10.1594/pangaea.972515,pangaea.repository,Dataset,2024-10-30,PANGAEA,Creative Commons Attribution 4.0 International,['264 data points']
+10.1594/pangaea.972514,pangaea.repository,Dataset,2024-10-30,PANGAEA,Creative Commons Attribution 4.0 International,['9249 data points']
+10.1594/pangaea.972510,pangaea.repository,Dataset,2024-10-30,PANGAEA,Creative Commons Attribution 4.0 International,['20736 data points']
+10.1594/pangaea.972508,pangaea.repository,Dataset,2024-10-30,PANGAEA,Creative Commons Attribution 4.0 International,['17667 data points']
+10.5281/zenodo.14008283,cern.zenodo,Dataset,2024-10-29,Zenodo,Creative Commons Attribution 4.0 International,
+10.5281/zenodo.14006429,cern.zenodo,Text,2024-10-29,"Université Grenoble Alpes, UGA",Creative Commons Attribution 4.0 International,
+10.5281/zenodo.13987040,cern.zenodo,Dataset,2024-10-29,Zenodo,Creative Commons Attribution 4.0 International,
+10.25577/fr1v-0577,inist.eost,Dataset,2024-10-28,"EOST UAR830, Université de Strasbourg, CNRS",Creative Commons Attribution 4.0 International,
+10.5281/zenodo.14002372,cern.zenodo,Software,2024-10-28,Zenodo,Creative Commons Attribution 4.0 International,
 10.5281/zenodo.13996908,cern.zenodo,Dataset,2024-10-26,Zenodo,Creative Commons Attribution 4.0 International,
 10.5281/zenodo.13919736,cern.zenodo,ComputationalNotebook,2024-10-25,Zenodo,Creative Commons Attribution 4.0 International,
 10.6084/m9.figshare.c.7507882,figshare.ars,Collection,2024-10-24,figshare,Creative Commons Attribution 4.0 International,
@@ -9,6 +23,8 @@ doi,client,resourceTypeGeneral,created,publisher,rights,sizes
 10.5281/zenodo.13951667,cern.zenodo,Dataset,2024-10-18,Zenodo,Creative Commons Attribution 4.0 International,
 10.5281/zenodo.13940200,cern.zenodo,Software,2024-10-16,Zenodo,Creative Commons Attribution 4.0 International,
 10.5281/zenodo.13932813,cern.zenodo,Software,2024-10-15,Zenodo,Creative Commons Attribution 4.0 International,
+10.5281/zenodo.13927580,cern.zenodo,Software,2024-10-14,Zenodo,Creative Commons Attribution 4.0 International,
+10.57745/izde4q,rdg.prod,Dataset,2024-10-11,Recherche Data Gouv,,
 10.15778/resif.zp2020,inist.resif,Dataset,2024-10-08,RESIF - Réseau Sismologique et géodésique Français,,"['10 stations, 41Go (miniseed format)']"
 10.5281/zenodo.13899342,cern.zenodo,Dataset,2024-10-07,Zenodo,Creative Commons Attribution 4.0 International,
 10.5281/zenodo.13898563,cern.zenodo,Dataset,2024-10-07,Zenodo,Creative Commons Attribution 4.0 International,
@@ -40,11 +56,11 @@ doi,client,resourceTypeGeneral,created,publisher,rights,sizes
 10.5281/zenodo.13785330,cern.zenodo,Dataset,2024-09-18,Zenodo,Creative Commons Attribution 4.0 International,
 10.26302/sshade/experiment_op_20050205_001,inist.sshade,Dataset,2024-09-13,SSHADE/FAME (OSUG Data Center),"Any use of downloaded SSHADE data in a scientific or technical paper or a presentation is free but you should cite both SSHADE and the used data in the text ( 'first author' et al., year) with its full reference (with its DOI) in the main reference section of the paper (or in a special 'data citation' section) and, when available, the original paper(s) presenting the data.",['1 spectrum']
 10.26302/sshade/experiment_op_20170206_001,inist.sshade,Dataset,2024-09-13,SSHADE/FAME (OSUG Data Center),"Any use of downloaded SSHADE data in a scientific or technical paper or a presentation is free but you should cite both SSHADE and the used data in the text ( 'first author' et al., year) with its full reference (with its DOI) in the main reference section of the paper (or in a special 'data citation' section) and, when available, the original paper(s) presenting the data.",['1 spectrum']
-10.6084/m9.figshare.c.7447186,figshare.ars,Collection,2024-09-13,figshare,Creative Commons Attribution 4.0 International,
 10.6084/m9.figshare.27012151,figshare.ars,Text,2024-09-13,figshare,Creative Commons Attribution 4.0 International,['450818 Bytes']
+10.6084/m9.figshare.c.7447186,figshare.ars,Collection,2024-09-13,figshare,Creative Commons Attribution 4.0 International,
 10.5281/zenodo.13748961,cern.zenodo,Text,2024-09-11,Zenodo,"Creative Commons Attribution 4.0 International,Creative Commons Attribution Share Alike 4.0 International",
-10.6084/m9.figshare.c.6585842,figshare.ars,Collection,2024-09-11,figshare,Creative Commons Attribution 4.0 International,
 10.6084/m9.figshare.26985715,figshare.ars,Text,2024-09-11,figshare,Creative Commons Attribution 4.0 International,['25284 Bytes']
+10.6084/m9.figshare.c.6585842,figshare.ars,Collection,2024-09-11,figshare,Creative Commons Attribution 4.0 International,
 10.5281/zenodo.13745070,cern.zenodo,Dataset,2024-09-11,Zenodo,Creative Commons Attribution 4.0 International,
 10.26302/sshade/experiment_zed_20240701_01,inist.sshade,Dataset,2024-09-11,SSHADE/DAYSY (OSUG Data Center),"Any use of downloaded SSHADE data in a scientific or technical paper or a presentation is free but you should cite both SSHADE and the used data in the text ( 'first author' et al., year) with its full reference (with its DOI) in the main reference section of the paper (or in a special 'data citation' section) and, when available, the original paper(s) presenting the data.",['14 spectra']
 10.5281/zenodo.11108225,cern.zenodo,Dataset,2024-09-08,Zenodo,Creative Commons Attribution 4.0 International,
@@ -87,8 +103,8 @@ doi,client,resourceTypeGeneral,created,publisher,rights,sizes
 10.57760/sciencedb.11705,cnic.sciencedb,Dataset,2024-08-15,Science Data Bank,Creative Commons Attribution Non Commercial Share Alike 4.0 International,"['99398887984 bytes', '14 files']"
 10.6084/m9.figshare.26722614,figshare.ars,Text,2024-08-15,figshare,Creative Commons Attribution 4.0 International,['12341 Bytes']
 10.6084/m9.figshare.25854698,figshare.ars,Image,2024-08-15,figshare,Creative Commons Attribution 4.0 International,['464136 Bytes']
-10.6084/m9.figshare.26713777,figshare.ars,Dataset,2024-08-15,figshare,Creative Commons Attribution 4.0 International,['553168 Bytes']
 10.6084/m9.figshare.c.7204785,figshare.ars,Collection,2024-08-15,figshare,Creative Commons Attribution 4.0 International,
+10.6084/m9.figshare.26713777,figshare.ars,Dataset,2024-08-15,figshare,Creative Commons Attribution 4.0 International,['553168 Bytes']
 10.6084/m9.figshare.25711209,figshare.ars,Text,2024-08-15,figshare,Creative Commons Attribution 4.0 International,['33449 Bytes']
 10.6084/m9.figshare.c.7116481,figshare.ars,Collection,2024-08-15,figshare,Creative Commons Attribution 4.0 International,
 10.6084/m9.figshare.26691925,figshare.ars,Text,2024-08-15,figshare,Creative Commons Attribution 4.0 International,['2061125 Bytes']
@@ -164,8 +180,8 @@ doi,client,resourceTypeGeneral,created,publisher,rights,sizes
 10.6084/m9.figshare.26585823,figshare.ars,Text,2024-08-13,figshare,Creative Commons Attribution 4.0 International,['11099 Bytes']
 10.6084/m9.figshare.26577821,figshare.ars,Dataset,2024-08-13,figshare,Creative Commons Attribution 4.0 International,['56397 Bytes']
 10.6084/m9.figshare.c.6596504,figshare.ars,Collection,2024-08-13,figshare,Creative Commons Attribution 4.0 International,
-10.6084/m9.figshare.c.6586928,figshare.ars,Collection,2024-08-13,figshare,Creative Commons Attribution 4.0 International,
 10.6084/m9.figshare.26567603,figshare.ars,Text,2024-08-13,figshare,Creative Commons Attribution 4.0 International,['360541 Bytes']
+10.6084/m9.figshare.c.6586928,figshare.ars,Collection,2024-08-13,figshare,Creative Commons Attribution 4.0 International,
 10.15778/resif.z42022,inist.resif,Dataset,2024-08-12,RESIF - Réseau Sismologique et géodésique Français,,"['98 stations, 280Go (miniseed format)']"
 10.12686/eshm20-output,ethz.sed,Dataset,2024-08-12,EFEHR (European Facilities of Earthquake Hazard and Risk),Creative Commons Attribution 4.0 International,['529MB']
 10.5281/zenodo.7447726,cern.zenodo,Dataset,2024-08-12,Zenodo,Creative Commons Attribution 4.0 International,
@@ -386,8 +402,8 @@ doi,client,resourceTypeGeneral,created,publisher,rights,sizes
 10.60527/fpa9-1718,fmsh.prod,Other,2024-03-06,"Univ. Grenoble Alpes, GRESEC",,
 10.60527/zxn9-6b90,fmsh.prod,Audiovisual,2024-03-06,"Univ. Grenoble Alpes, GRESEC",Droit commun de la propriété intellectuelle,
 10.5281/zenodo.10788911,cern.zenodo,Dataset,2024-03-06,Zenodo,Creative Commons Attribution 4.0 International,
-10.6084/m9.figshare.c.7105606,figshare.ars,Collection,2024-03-05,figshare,Creative Commons Attribution 4.0 International,
 10.6084/m9.figshare.25341247,figshare.ars,Dataset,2024-03-05,figshare,Creative Commons Attribution 4.0 International,['29389796 Bytes']
+10.6084/m9.figshare.c.7105606,figshare.ars,Collection,2024-03-05,figshare,Creative Commons Attribution 4.0 International,
 10.6084/m9.figshare.25329673,figshare.ars,Text,2024-03-02,figshare,Creative Commons Attribution 4.0 International,['15066 Bytes']
 10.6084/m9.figshare.c.7097182,figshare.ars,Collection,2024-02-29,figshare,Creative Commons Attribution 4.0 International,
 10.6084/m9.figshare.25309966,figshare.ars,Text,2024-02-29,figshare,Creative Commons Attribution 4.0 International,['584702 Bytes']
@@ -432,8 +448,8 @@ doi,client,resourceTypeGeneral,created,publisher,rights,sizes
 10.57745/krycyy,rdg.prod,Dataset,2024-01-29,Recherche Data Gouv,,
 10.5281/zenodo.10578348,cern.zenodo,Software,2024-01-28,Zenodo,GNU General Public License v3.0 or later,
 10.5281/zenodo.10577878,cern.zenodo,Software,2024-01-28,Zenodo,Creative Commons Attribution 4.0 International,
-10.6084/m9.figshare.25097340,figshare.ars,Text,2024-01-28,figshare,Creative Commons Attribution 4.0 International,['302967 Bytes']
 10.6084/m9.figshare.c.7046484,figshare.ars,Collection,2024-01-28,figshare,Creative Commons Attribution 4.0 International,
+10.6084/m9.figshare.25097340,figshare.ars,Text,2024-01-28,figshare,Creative Commons Attribution 4.0 International,['302967 Bytes']
 10.5281/zenodo.10575610,cern.zenodo,Dataset,2024-01-27,Zenodo,Creative Commons Attribution 4.0 International,
 10.57745/rjx9xh,rdg.prod,Dataset,2024-01-26,Recherche Data Gouv,,
 10.5281/zenodo.10551644,cern.zenodo,Dataset,2024-01-22,Zenodo,Creative Commons Attribution 4.0 International,
@@ -483,32 +499,3 @@ doi,client,resourceTypeGeneral,created,publisher,rights,sizes
 10.48380/2gzr-9q70,mcdy.dohrmi,Text,2023-12-11,Deutsche Geologische Gesellschaft - Geologische Vereinigung e.V. (DGGV),,
 10.48380/cwsp-mj37,mcdy.dohrmi,Text,2023-12-11,Deutsche Geologische Gesellschaft - Geologische Vereinigung e.V. (DGGV),,
 10.5281/zenodo.10262983,cern.zenodo,Text,2023-12-11,Unite! Alliance Publications,Creative Commons Attribution 4.0 International,
-10.18709/perscido.2023.12.ds403,inist.persyval,Dataset,2023-12-11,PerSCiDO,,['10 Mo']
-10.5281/zenodo.10341148,cern.zenodo,Software,2023-12-10,Zenodo,INRIA Non-Commercial License Agreement,
-10.5281/zenodo.10277798,cern.zenodo,Dataset,2023-12-07,Zenodo,Creative Commons Attribution 4.0 International,
-10.17178/emaa_so_fine_e3d652e7,inist.osug,Dataset,2023-12-07,"UGA, CNRS, CNRS-INSU, OSUG","Please acknowledge the use of EMAA Database by citing the original articles in which the data were published (BibTeX format available), and adding the following sentence in your publication: 
-This research has made use of spectroscopic and collisional data from the EMAA database (https://emaa.osug.fr). EMAA is supported by the Observatoire des Sciences de l'Univers de Grenoble (OSUG),Creative Commons Attribution 4.0 International,Data access and use are ruled by the EMAA data policy.",
-10.17178/emaa_para-nh3_rotation-hot_9da5b297,inist.osug,Dataset,2023-12-07,"UGA, CNRS, CNRS-INSU, OSUG","Please acknowledge the use of EMAA Database by citing the original articles in which the data were published (BibTeX format available), and adding the following sentence in your publication: 
-This research has made use of spectroscopic and collisional data from the EMAA database (https://emaa.osug.fr). EMAA is supported by the Observatoire des Sciences de l'Univers de Grenoble (OSUG),Creative Commons Attribution 4.0 International,Data access and use are ruled by the EMAA data policy.",
-10.17178/emaa_para-nh3_hyperfine_1be97812,inist.osug,Dataset,2023-12-07,"UGA, CNRS, CNRS-INSU, OSUG","Please acknowledge the use of EMAA Database by citing the original articles in which the data were published (BibTeX format available), and adding the following sentence in your publication: 
-This research has made use of spectroscopic and collisional data from the EMAA database (https://emaa.osug.fr). EMAA is supported by the Observatoire des Sciences de l'Univers de Grenoble (OSUG),Creative Commons Attribution 4.0 International,Data access and use are ruled by the EMAA data policy.",
-10.17178/emaa_para-h2s_rotation_f76b8b70,inist.osug,Dataset,2023-12-07,"UGA, CNRS, CNRS-INSU, OSUG","Please acknowledge the use of EMAA Database by citing the original articles in which the data were published (BibTeX format available), and adding the following sentence in your publication: 
-This research has made use of spectroscopic and collisional data from the EMAA database (https://emaa.osug.fr). EMAA is supported by the Observatoire des Sciences de l'Univers de Grenoble (OSUG),Creative Commons Attribution 4.0 International,Data access and use are ruled by the EMAA data policy.",
-10.17178/emaa_para-h2(34s)_rotation_52d67276,inist.osug,Dataset,2023-12-07,"UGA, CNRS, CNRS-INSU, OSUG","Please acknowledge the use of EMAA Database by citing the original articles in which the data were published (BibTeX format available), and adding the following sentence in your publication: 
-This research has made use of spectroscopic and collisional data from the EMAA database (https://emaa.osug.fr). EMAA is supported by the Observatoire des Sciences de l'Univers de Grenoble (OSUG),Creative Commons Attribution 4.0 International,Data access and use are ruled by the EMAA data policy.",
-10.17178/emaa_para-d2s_rotation_1e071ded,inist.osug,Dataset,2023-12-07,"UGA, CNRS, CNRS-INSU, OSUG","Please acknowledge the use of EMAA Database by citing the original articles in which the data were published (BibTeX format available), and adding the following sentence in your publication: 
-This research has made use of spectroscopic and collisional data from the EMAA database (https://emaa.osug.fr). EMAA is supported by the Observatoire des Sciences de l'Univers de Grenoble (OSUG),Creative Commons Attribution 4.0 International,Data access and use are ruled by the EMAA data policy.",
-10.17178/emaa_para-c3h2_rotation_bcdd4e50,inist.osug,Dataset,2023-12-07,"UGA, CNRS, CNRS-INSU, OSUG","Please acknowledge the use of EMAA Database by citing the original articles in which the data were published (BibTeX format available), and adding the following sentence in your publication: 
-This research has made use of spectroscopic and collisional data from the EMAA database (https://emaa.osug.fr). EMAA is supported by the Observatoire des Sciences de l'Univers de Grenoble (OSUG),Creative Commons Attribution 4.0 International,Data access and use are ruled by the EMAA data policy.",
-10.17178/emaa_para-(13c)c2h2_rotation_62296b37,inist.osug,Dataset,2023-12-07,"UGA, CNRS, CNRS-INSU, OSUG","Please acknowledge the use of EMAA Database by citing the original articles in which the data were published (BibTeX format available), and adding the following sentence in your publication: 
-This research has made use of spectroscopic and collisional data from the EMAA database (https://emaa.osug.fr). EMAA is supported by the Observatoire des Sciences de l'Univers de Grenoble (OSUG),Creative Commons Attribution 4.0 International,Data access and use are ruled by the EMAA data policy.",
-10.17178/emaa_ortho-nh3_rotation-hot_2c68197a,inist.osug,Dataset,2023-12-07,"UGA, CNRS, CNRS-INSU, OSUG","Please acknowledge the use of EMAA Database by citing the original articles in which the data were published (BibTeX format available), and adding the following sentence in your publication: 
-This research has made use of spectroscopic and collisional data from the EMAA database (https://emaa.osug.fr). EMAA is supported by the Observatoire des Sciences de l'Univers de Grenoble (OSUG),Creative Commons Attribution 4.0 International,Data access and use are ruled by the EMAA data policy.",
-10.17178/emaa_ortho-nh3_rotation_331d9739,inist.osug,Dataset,2023-12-07,"UGA, CNRS, CNRS-INSU, OSUG","Please acknowledge the use of EMAA Database by citing the original articles in which the data were published (BibTeX format available), and adding the following sentence in your publication: 
-This research has made use of spectroscopic and collisional data from the EMAA database (https://emaa.osug.fr). EMAA is supported by the Observatoire des Sciences de l'Univers de Grenoble (OSUG),Creative Commons Attribution 4.0 International,Data access and use are ruled by the EMAA data policy.",
-10.17178/emaa_ortho-nh3_hyperfine_22b1dfb7,inist.osug,Dataset,2023-12-07,"UGA, CNRS, CNRS-INSU, OSUG","Please acknowledge the use of EMAA Database by citing the original articles in which the data were published (BibTeX format available), and adding the following sentence in your publication: 
-This research has made use of spectroscopic and collisional data from the EMAA database (https://emaa.osug.fr). EMAA is supported by the Observatoire des Sciences de l'Univers de Grenoble (OSUG),Creative Commons Attribution 4.0 International,Data access and use are ruled by the EMAA data policy.",
-10.17178/emaa_ortho-h2s_rotation_3f29e6c3,inist.osug,Dataset,2023-12-07,"UGA, CNRS, CNRS-INSU, OSUG","Please acknowledge the use of EMAA Database by citing the original articles in which the data were published (BibTeX format available), and adding the following sentence in your publication: 
-This research has made use of spectroscopic and collisional data from the EMAA database (https://emaa.osug.fr). EMAA is supported by the Observatoire des Sciences de l'Univers de Grenoble (OSUG),Creative Commons Attribution 4.0 International,Data access and use are ruled by the EMAA data policy.",
-10.17178/emaa_ortho-h2co_hyperfine_21889b23,inist.osug,Dataset,2023-12-07,"UGA, CNRS, CNRS-INSU, OSUG","Please acknowledge the use of EMAA Database by citing the original articles in which the data were published (BibTeX format available), and adding the following sentence in your publication: 
-This research has made use of spectroscopic and collisional data from the EMAA database (https://emaa.osug.fr). EMAA is supported by the Observatoire des Sciences de l'Univers de Grenoble (OSUG),Creative Commons Attribution 4.0 International,Data access and use are ruled by the EMAA data policy.",
diff --git a/dois-uga.csv b/dois-uga.csv
index 262a415de992b477862a69e1fc37c77bce024f6c..fe5cef1c6c7211dbc41c0df78bde291a449db260 100644
--- a/dois-uga.csv
+++ b/dois-uga.csv
@@ -11245,3 +11245,240 @@ The dataset contains the log files of 79382 frames sent by two LoRaWAN endpoints
 The exact location is [45.23513,5.7617](https://www.openstreetmap.org/search?query=45.23513%2C5.7617#map=19/45.23513/5.76170). The GPS altitude is 1350 meters.
 ",api,True,findable,0,0,0,0,0,2024-10-22T14:45:56.000Z,2024-10-22T14:45:57.000Z,inist.persyval,vcob,"Information Technology,Engineering","[{'subject': 'Information Technology', 'subjectScheme': 'http://www.radar-projekt.org/display/Information_Technology'}, {'subject': 'Engineering', 'subjectScheme': 'http://www.radar-projekt.org/display/Engineering'}]",['10 Mo'],['JSON'],,,,
 10.6084/m9.figshare.27289282,Additional file 2 of Predictive value of tumor microenvironment on pathologic response to neoadjuvant chemotherapy in patients with undifferentiated pleomorphic sarcomas,figshare,2024,,Text,Creative Commons Attribution 4.0 International,Supplementary Material 2,mds,True,findable,0,0,0,1,0,2024-10-24T04:22:01.000Z,2024-10-24T04:22:02.000Z,figshare.ars,otjm,"Medicine,Genetics,FOS: Biological sciences,Pharmacology,Immunology,FOS: Clinical medicine,Biological Sciences not elsewhere classified,Cancer,Science Policy","[{'subject': 'Medicine'}, {'subject': 'Genetics'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Pharmacology'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Biological Sciences not elsewhere classified'}, {'subject': 'Cancer'}, {'subject': 'Science Policy'}]",['783979 Bytes'],,,,"['IsIdenticalTo', 'IsSupplementTo']","[['IsIdenticalTo', '10.6084/m9.figshare.27289282']]"
+10.5281/zenodo.13927580,sylvainschmitt/sdmverse: Ecography version 1.0.0,Zenodo,2024,,Software,Creative Commons Attribution 4.0 International,The version 1.0.0 corresponds to the manuscript acceptance in Ecography.,api,True,findable,0,0,0,0,1,2024-10-14T07:08:07.000Z,2024-10-14T07:08:07.000Z,cern.zenodo,cern,,,,,,,"['IsSupplementTo', 'HasVersion']",
+10.5281/zenodo.14013195,Bimetallic Pd–Rh Nanoparticles Supported on Co3O4(111): Atomic Ordering and Stability,Zenodo,2024,,Dataset,Creative Commons Attribution 4.0 International,Synchrotron radiation photoelectron spectroscopy (SRPES) and scanning tunneling microscopy (STM) datasets,api,True,findable,0,0,0,0,0,2024-10-30T15:36:28.000Z,2024-10-30T15:36:28.000Z,cern.zenodo,cern,,,,,,,['HasVersion'],"[['IsVersionOf', '10.5281/zenodo.14013195']]"
+10.5281/zenodo.14016979,RES4CITY Case Study: Sustainable Heating: Grenoble's Solutions for Heat Recovery from a Nearby Industry (Full version),Zenodo,2024,,Other,Creative Commons Attribution 4.0 International,"This case study presents the heating network in Grenoble, including its stakeholders and the different power plants involved. The results show that among the three scenarios presented, the most realistic is the scenario with 25% wood pellets and 75% wood consumption. In fact, the construction of a new power plant is not useful since this plant would only operate half of the time foreseen. ",api,True,findable,0,0,0,0,1,2024-10-31T10:32:33.000Z,2024-10-31T10:32:34.000Z,cern.zenodo,cern,,,,,,,"['Continues', 'HasVersion']",
+10.1594/pangaea.972510,Continuous Antarctic Carbon monoxide (CO) record from Bryan Coast ice core from 1820 to 1995 CE,PANGAEA,2024,,Dataset,Creative Commons Attribution 4.0 International,"Continuous ice core carbon monoxide (CO) mixing ratios are presented for three West Antarctic Cores (Jurassic, Bryan Coast, and Dyer Plateau). Data cover from 1820 CE to 1995 CE. For each core, data are presented integrated at 10-second intervals from an original acquisition rate of 4 Hz. Data were measured continuously utilising Optical Feedback Cavity Enhanced Spectroscopy connected to a continuous ice core melting system at the British Antarctic Survey. A smoothed spline composed of the bottom 5th percentile of each record is also presented. A percentile re-sampling method is required to remove the impact of in situ production. The spline is used to interpret Southern Hemisphere CO variability from the pre-industrial with a particular focus on biomass burning.",mds,True,findable,0,0,1,0,0,2024-10-30T01:08:34.000Z,2024-10-30T01:08:34.000Z,pangaea.repository,pangaea,"biomass burning,carbon monoxide,Ice core,pre-industrial,Southern Hemisphere,DEPTH, ice/snow,Gas age,Carbon monoxide,Carbon monoxide, uncertainty,Ice drill,Continuous Flow Analysis (CFA) coupled with laser spectroscopy detection (OF-CEAS)","[{'subject': 'biomass burning'}, {'subject': 'carbon monoxide'}, {'subject': 'Ice core'}, {'subject': 'pre-industrial'}, {'subject': 'Southern Hemisphere'}, {'subject': 'DEPTH, ice/snow', 'subjectScheme': 'Parameter'}, {'subject': 'Gas age', 'subjectScheme': 'Parameter'}, {'subject': 'Carbon monoxide', 'subjectScheme': 'Parameter'}, {'subject': 'Carbon monoxide, uncertainty', 'subjectScheme': 'Parameter'}, {'subject': 'Ice drill', 'subjectScheme': 'Method'}, {'subject': 'Continuous Flow Analysis (CFA) coupled with laser spectroscopy detection (OF-CEAS)', 'subjectScheme': 'Method'}]",['20736 data points'],['text/tab-separated-values'],,,"['IsPartOf', 'References']",
+10.1594/pangaea.972514,Continuous Antarctic Carbon monoxide (CO) record from Dyer Plateau ice core from 1820 to 1995 CE,PANGAEA,2024,,Dataset,Creative Commons Attribution 4.0 International,"Continuous ice core carbon monoxide (CO) mixing ratios are presented for three West Antarctic Cores (Jurassic, Bryan Coast, and Dyer Plateau). Data cover from 1820 CE to 1995 CE. For each core, data are presented integrated at 10-second intervals from an original acquisition rate of 4 Hz. Data were measured continuously utilising Optical Feedback Cavity Enhanced Spectroscopy connected to a continuous ice core melting system at the British Antarctic Survey. A smoothed spline composed of the bottom 5th percentile of each record is also presented. A percentile re-sampling method is required to remove the impact of in situ production. The spline is used to interpret Southern Hemisphere CO variability from the pre-industrial with a particular focus on biomass burning.",mds,True,findable,0,0,1,0,0,2024-10-30T01:08:35.000Z,2024-10-30T01:08:36.000Z,pangaea.repository,pangaea,"biomass burning,carbon monoxide,Ice core,pre-industrial,Southern Hemisphere,DEPTH, ice/snow,Gas age,Carbon monoxide,Carbon monoxide, uncertainty,Ice drill,Continuous Flow Analysis (CFA) coupled with laser spectroscopy detection (OF-CEAS)","[{'subject': 'biomass burning'}, {'subject': 'carbon monoxide'}, {'subject': 'Ice core'}, {'subject': 'pre-industrial'}, {'subject': 'Southern Hemisphere'}, {'subject': 'DEPTH, ice/snow', 'subjectScheme': 'Parameter'}, {'subject': 'Gas age', 'subjectScheme': 'Parameter'}, {'subject': 'Carbon monoxide', 'subjectScheme': 'Parameter'}, {'subject': 'Carbon monoxide, uncertainty', 'subjectScheme': 'Parameter'}, {'subject': 'Ice drill', 'subjectScheme': 'Method'}, {'subject': 'Continuous Flow Analysis (CFA) coupled with laser spectroscopy detection (OF-CEAS)', 'subjectScheme': 'Method'}]",['9249 data points'],['text/tab-separated-values'],,,"['IsPartOf', 'References']",
+10.5281/zenodo.14008283,The Little Prince AMR Corpus (Expanded with Korean and Croatian),Zenodo,2024,,Dataset,Creative Commons Attribution 4.0 International,"We expanded The Little Prince AMR Corpus (https://amr.isi.edu/). The original data is available in English and Chinese. By manually aligning Korean and Croatian texts to English, we obtained multilingual The Little Corpus AMR Corpus. ",api,True,findable,0,0,0,0,0,2024-10-29T15:17:01.000Z,2024-10-29T15:17:02.000Z,cern.zenodo,cern,,,,,,,['HasVersion'],"[['IsVersionOf', '10.5281/zenodo.14008283']]"
+10.5281/zenodo.14006429,Hydrodynamic modelling of a meso-tidal river using in-situ and SWOT measurements in a data-scarce region,"Université Grenoble Alpes, UGA",2024,en,Text,Creative Commons Attribution 4.0 International,"Coastal environments have historically supported thriving societies due to their rich food resources, fertile soils, and strategic locations as transportation hubs, fostering urban development and economic growth. This trend continues today, with many of the world’s most densely populated cities situated in Low-Elevation Coastal Zones (LECZs). Currently, approximately 896 million people, nearly 11% of the global population in 2020, reside in LECZs, and this number is projected to exceed one billion by 2050. Coastal megacities face substantial risks from climate change due to their low elevation, climate-sensitive physical and ecological characteristics, and high societal exposure and vulnerability. Despite these risks, LECZs are poorly monitored globally, especially in under-developed and developing countries.
+
+This thesis focuses on the poorly gauged LECZ of Ho Chi Minh City (HCMC) in South Vietnam. HCMC, a densely populated megacity, has urban center areas with up to 30,000 inhabitants per square kilometer. The city is traversed by the tidal Saigon River, which includes a network of about 800 km of watercourses and canals. With 90% of HCMC’s urban area being impermeable, the hydrological cycle is significantly impacted, leading to frequent flooding from coastal, riverine, and rainfall runoff sources.Achieving a sustainable future for HCMC relies on our ability to monitor both hydrological and oceanographic variables concurrently to better understand the physics of these systems. To enhance our understanding of this estuarine system, two key variables are of interest: river and coastal ocean water levels, and river discharge. These variables can be effectively monitored using a combination of in-situ and satellite measurements.
+
+The general objective of this thesis is to achieve a better understanding of the hydrological-to-ocean continuum in the LECZ of Ho Chi Minh City. To do so we use a trinity of tools: in-situ measurements, remote sensing measurements and hydrodynamic modelling. In specific, we are interested in assessing the potential of the new Surface Water and Ocean Topography (SWOT) satellite mission over this region.
+
+Chapter 1 introduces the subject area of the thesis.
+
+Chapter 2 assesses the impact of Typhoon Usagi, which made landfall in HCMC in 2018. The typhoon did not create a significant storm surge but caused extreme rainfall, leading to significant inland water level surges. Prolonged flooding in the city, especially in Thao Dien, resulted from the combination of a high river spring tide and  impervious, low-lying streets. Coastal tidal forcing was the main driver of river discharge during this event. A general insight into the the behaviour of the Saigon river was also found: seasonal coastal storm surges from East Asian summer monsoon wind patterns, rather than precipitation, were found to control river water levels.
+
+Chapter 3 presents data from a two-month field campaign in HCMC, where high-resolution river water level and discharge measurements were obtained. This campaign was managed and supervised by me, with assistance from Mr. Tin Nguyen Trung of the Center for Asian Research on Water (CARE). 
+
+Chapter 4 details the implementation, calibration, and validation of a 1D hydrodynamic model of the Saigon and Dongnai rivers, addressing calibration challenges in this data-scarce region. The model, coupled with a modified Manning-Strickler (MS) law, was developed in collaboration with Dr. Benoit Camenen of INRAE. The best calibration strategy was found to involve directly measured water levels and indirectly measured discharge data, despite challenges from dynamic tidal conditions and lack of reliable upstream discharge data. Validation against independent measurements showed promising results, demonstrating the effectiveness of the modified MS equation in  enhancing discharge estimates.
+
+Chapter 5 provides a statistical study of the potential of SWOT satellite data to improve discharge estimations in the Saigon River, conducted before real SWOT data was available. A methodology using simulated SWOT products at a 200-meter node resolution showed improved discharge estimates by reducing mean relative RMSE and increasing R2 between true and estimated discharge.
+
+Chapter 6 explores the application of real SWOT data in one of the most challenging coastal environments this satellite mission could encounter: a datascarce, tropical region characterized by flat topography, a heavily urbanized environment, and a river with a weak water surface slope that fluctuates daily around zero due to strong coastal tidal forcing. To do so, we compare SWOT’s reach level products of river water level and slope against in-situ measurements. The results show that about 50% of SWOT’s water level measurements were found to be valid compared to in-situ data, showing a good accuracy despite the challenges posed by this region. However, SWOT’s slope measurements lack accuracy and are unreliable without prior validation against in-situ data. Despite these limitations, SWOT provides high-spatial resolution observations that can offer new insights into dynamic hydrological phenomena when combined with in-situ data and modeling efforts.
+
+Chapter 7 concludes the thesis and offers perspectives for future work.",api,True,findable,0,0,0,0,0,2024-10-29T10:07:23.000Z,2024-10-29T10:07:23.000Z,cern.zenodo,cern,"Coastal and estuarine hydraulics,Satellite technology,Hydrology,Vietnam,tidal river","[{'subject': 'Coastal and estuarine hydraulics', 'subjectScheme': 'EuroSciVoc'}, {'subject': 'Satellite technology', 'subjectScheme': 'EuroSciVoc'}, {'subject': 'Hydrology', 'subjectScheme': 'EuroSciVoc'}, {'subject': 'Vietnam'}, {'subject': 'tidal river'}]",,,,,['HasVersion'],"[['IsVersionOf', '10.5281/zenodo.14006429']]"
+10.57745/izde4q,Data for fast-charging of lithium iron phosphate battery with ohmic-drop compensation method,Recherche Data Gouv,2024,,Dataset,,"In this study, fast-charging of lithium iron phosphate batteries is investigated with ohmic-drop compensation method. The Li-ion batteries used are C-LiFePO4 cylinder cells manufactured by PHET (model: IFR13N0-PE1150). The nominal voltage for this battery is about 3.3 V at open-circuit. The nominal capacity of these batteries is 1.1Ah. Each file contains either data from charge or discharge at different C-rate: • Charge(XC)_X. This file contains the experimental raw data of the charge at XC • Discharge(XC)_X. This file contains the experimental raw data of the discharge at XC",mds,True,findable,5,0,0,0,0,2024-10-11T11:48:52.000Z,2024-10-31T09:02:01.000Z,rdg.prod,rdg,,,,,,,"['HasPart', 'HasPart', 'HasPart', 'HasPart', 'HasPart', 'HasPart', 'HasPart', 'HasPart', 'HasPart', 'HasPart', 'HasPart', 'HasPart', 'HasPart']",
+10.57760/sciencedb.16149,"Data of the article ""Coupled dissolution-precipitation and growth processes on calcite, aragonite, and Carrara marble exposed to cadmium-rich aqueous solutions""",Science Data Bank,2024,en,Dataset,Creative Commons Attribution Non Commercial 4.0 International,"This data is linked to the article ""Coupled dissolution-precipitation and growth processes on calcite, aragonite, and Carrara marble exposed to cadmium-rich aqueous solutions"", Maude Julia, Christine V. Putnis, Helen E. King, François Renard, Chemical Geology, 2023, 621, https://doi.org/10.1016/j.chemgeo.2023.121364.It contains the Atomic Force Microscopy (AFM) Height and deflection images, Phreeqc simulations, SEM images of reacted mineral samples and Raman spectra mentionned and/or described in the article. Data description documents are provided to help the reader navigate through the data and use it.",api,True,findable,0,0,0,1,0,2024-11-04T01:41:51.000Z,2024-11-04T01:41:52.000Z,cnic.sciencedb,cnic,"Chemical,Materials science,Environmental science and resources science and technology,Calcium carbonate,cadmium,coupled dissolution-precipitation,environmental remediation","[{'subject': 'Chemical', 'subjectScheme': 'GB/T 13745-2009', 'classificationCode': '150'}, {'subject': 'Materials science', 'subjectScheme': 'GB/T 13745-2009', 'classificationCode': '430'}, {'subject': 'Environmental science and resources science and technology', 'subjectScheme': 'GB/T 13745-2009', 'classificationCode': '610'}, {'subject': 'Calcium carbonate'}, {'subject': 'cadmium'}, {'subject': 'coupled dissolution-precipitation'}, {'subject': 'environmental remediation'}]","['2433253276 bytes', '4 files']",,,,['IsSupplementTo'],
+10.5281/zenodo.14003384,GNSS data at the Astrolabe Glacier,Zenodo,2024,,Dataset,Creative Commons Attribution 4.0 International,"This dataset contains GNSS measurements collected at the Astrolabe Glacier (Terre Adélie, East Antarctica) from January 17, 2023, to February 2, 2023 and presented in:
+
+Le Bris et al. (2024), Spatial and Temporal Variability in Tide-induced Icequake Activity at the Astrolabe Coastal Glacier, East Antarctica. Submitted in JGR.
+
+Data from each GNSS station (7 stations in total) are saved in individual files. The processed data (*pos files) are organized by columns as follows: Time, North, East, Up, and Up Detrended. Additionally, raw GNSS data files used to generate the processed outputs are included. Details on data processing steps are provided in the supporting materials of the above reference.",api,True,findable,0,0,0,0,0,2024-11-01T16:43:11.000Z,2024-11-01T16:43:12.000Z,cern.zenodo,cern,,,,,,,['HasVersion'],"[['IsVersionOf', '10.5281/zenodo.14003384']]"
+10.5281/zenodo.14016634,RES4CITY Case Study: Sustainable Heating: Grenoble's Solutions for Heat Recovery from a Nearby Industry (Full version),Zenodo,2024,en,Other,Creative Commons Attribution 4.0 International,"This case study presents the heating network in Grenoble, including its stakeholders and the different power plants involved. The results show that among the three scenarios presented, the most realistic is the scenario with 25% wood pellets and 75% wood consumption. In fact, the construction of a new power plant is not useful since this plant would only operate half of the time foreseen. ",api,True,findable,0,0,0,0,1,2024-10-31T10:02:58.000Z,2024-10-31T10:02:59.000Z,cern.zenodo,cern,"grenoble,power plants,renewable energy,case study,urban heating solutions","[{'subject': 'grenoble'}, {'subject': 'power plants'}, {'subject': 'renewable energy'}, {'subject': 'case study'}, {'subject': 'urban heating solutions'}]",,,,,"['Continues', 'HasVersion']",
+10.5281/zenodo.13987040,"Main output data used in ""Exploring the Greenland Ice Sheet's response to future warming-threshold scenarios over 200 years"" (Delhasse et al., 2024)",Zenodo,2024,,Dataset,Creative Commons Attribution 4.0 International,"Outputs used in:
+
+Delhasse, A., Kittel, C. and Beckmann, J.: Exploring the Greenland Ice Sheet’s response to future warming-threshold scenarios over 200 years, Geophysical Reschear Letters in review, 2024.
+
+Each MAR-PISM coupling experiment (1991-2200) is related to the Greenland warming over a 10-year period compared to our reference period (1961-1990) at which climate is stabilized until 2200. The last experiment is the Reverse one, where the climate is year by year reversed after 2100 to go back to 2000-climate as forcing in 2200, the last year of the simulation. Please refer to Delhasse et al. (2024) for the coupling description.
+
+
+
+
+
+
+
+
+Experiment 
+
+
+
+Exact Greenland warming at 600hPa (°C)
+
+
+
+10-years period
+
+
+
+
+
+
+
+CTRL
+
+
+
++0.00
+
+
+
+1961-1990
+
+
+
+
+
++1
+
+
+
++1.04
+
+
+
+1995-2004
+
+
+
+
+
++1.5
+
+
+
++1.51
+
+
+
+2010-2019
+
+
+
+
+
++2
+
+
+
++2.04
+
+
+
+2021-2030
+
+
+
+
+
++3
+
+
+
++2.98
+
+
+
+2040-2049
+
+
+
+
+
++4
+
+
+
++4.04
+
+
+
+2058-2067
+
+
+
+
+
++5
+
+
+
++5.00
+
+
+
+2074-2083
+
+
+
+
+
++6
+
+
+
++5.96
+
+
+
+2083-2092
+
+
+
+
+
++7
+
+
+
++6.85
+
+
+
+2091-2100
+
+
+
+
+
+
+Table 1. Greenland warmings at 600hPa since 1961-1990 used to define our experiments and the corresponding 10-years periods over which warmings are determined. 
+
+For each experiment, 3 types of output are available (where EXP corresponds to the name of the experiment as referenced in Table 1) : 
+
+
+
+
+
+EXP-PISM-thk-msk-1991-2200.nc: contain yearly ice thickness (THK) and ice mask (MASK) as simulated by PISM (PISM grid, 4.5 km);
+
+
+
+
+EXP-SMB-ME-RU-MAPI-CESM2-1991-2200.nc: contain yearly SMB (surface mass balance), ME (melt), and RU (runoff) on the MAR grid (25 km);
+
+
+
+
+EXP-ts-MB-D-SMB-1991-2200.nc: contain time series of the total MB (mass balance), D (discharge), and SMB (surface mass balance) integrated over the all ice sheet mask from PISM.
+
+
+
+The MAR code used in this dataset is tagged as v3.11.3 on https://gitlab.com/Mar-Group/MARv3/-/tree/v3.11.3 (last access: 24 October 2024) (MARTeam, 2024). The PISM code used is tagged as PISMv1.2.2 on https://github.com/pism/pism/releases/tag/v1.2.2 (last access: 24 October 2024).
+
+If you need other variables from MAR or PISM, send us an email (alison.delhasse@uliege.be) and we will be glad to help you. We will also be happy to share the scripts we have developed to analyze the outputs and make the figures in this paper if needed. Please cite the paper if you use these MAR-PISM outputs.Data usage notice:
+
+If you use any of these results, please acknowledge the work of the people involved in producing them. Acknowledgments should be similar to the one below that contains information related to MAR and PISM. To document MAR scientific impact and enable ongoing support of the model, users are likely encouraged to contact me to add their works to the list of MAR-related publications. 
+
+""We thank A. Delhasse, C. Kittel, and J. Beckmann, as well as the MAR and PISM teams which make available the model outputs. We also thank agencies (F.R.S - FNRS, CÉCI, and the Walloon Region) that provided computational resources for MAR-PISM simulations. ""
+
+You should also refer to and cite the following paper in its latest version:
+
+Delhasse, A., Kittel, C. and Beckmann, J.: Exploring the Greenland Ice Sheet’s response to future warming-threshold scenarios over 200 years, [JOURNAL UNDER REVIEW], 2024.
+
+References
+
+Delhasse, A., Beckmann, J., Kittel, C., and Fettweis, X.: Coupling MAR (Modèle Atmosphérique Régional) with PISM (Parallel Ice Sheet Model) mitigates the positive melt–elevation feedback, The Cryosphere, 18, 633–651, https://doi.org/10.5194/tc-18-633-2024, 2024.
+
+MARTeam: MARv3.11, GitLab [data set], https://gitlab.com/Mar-Group/MARv3# (last access: 24 October 2024), 2024.
+
+ ",api,True,findable,0,0,0,0,0,2024-10-29T08:56:57.000Z,2024-10-29T08:56:57.000Z,cern.zenodo,cern,,,,,,,"['IsDocumentedBy', 'HasVersion']","[['IsVersionOf', '10.5281/zenodo.13987040']]"
+10.1594/pangaea.972508,Continuous Antarctic Carbon monoxide (CO) record from Jurassic ice core from 1820 to 1995 CE,PANGAEA,2024,,Dataset,Creative Commons Attribution 4.0 International,"Continuous ice core carbon monoxide (CO) mixing ratios are presented for three West Antarctic Cores (Jurassic, Bryan Coast, and Dyer Plateau). Data cover from 1820 CE to 1995 CE. For each core, data are presented integrated at 10-second intervals from an original acquisition rate of 4 Hz. Data were measured continuously utilising Optical Feedback Cavity Enhanced Spectroscopy connected to a continuous ice core melting system at the British Antarctic Survey. A smoothed spline composed of the bottom 5th percentile of each record is also presented. A percentile re-sampling method is required to remove the impact of in situ production. The spline is used to interpret Southern Hemisphere CO variability from the pre-industrial with a particular focus on biomass burning.",mds,True,findable,0,0,1,0,0,2024-10-30T01:08:33.000Z,2024-10-30T01:08:33.000Z,pangaea.repository,pangaea,"biomass burning,carbon monoxide,Ice core,pre-industrial,Southern Hemisphere,DEPTH, ice/snow,Gas age,Carbon monoxide,Carbon monoxide, uncertainty,Ice drill,Continuous Flow Analysis (CFA) coupled with laser spectroscopy detection (OF-CEAS)","[{'subject': 'biomass burning'}, {'subject': 'carbon monoxide'}, {'subject': 'Ice core'}, {'subject': 'pre-industrial'}, {'subject': 'Southern Hemisphere'}, {'subject': 'DEPTH, ice/snow', 'subjectScheme': 'Parameter'}, {'subject': 'Gas age', 'subjectScheme': 'Parameter'}, {'subject': 'Carbon monoxide', 'subjectScheme': 'Parameter'}, {'subject': 'Carbon monoxide, uncertainty', 'subjectScheme': 'Parameter'}, {'subject': 'Ice drill', 'subjectScheme': 'Method'}, {'subject': 'Continuous Flow Analysis (CFA) coupled with laser spectroscopy detection (OF-CEAS)', 'subjectScheme': 'Method'}]",['17667 data points'],['text/tab-separated-values'],,,"['IsPartOf', 'References']",
+10.5281/zenodo.14002372,ToCCo,Zenodo,2024,,Software,Creative Commons Attribution 4.0 International,"ToCCo for “Topographic Coupling at Core-Mantle interface”, is a local perturbative model that calculates the flow over a topography or between two boundaries. It solves Magneto-Hydro-Dynamic equations in a Cartesian Boussinesq frame and can take into consideration: rotation, magnetic field, stratification, and fluid viscosity. ToCCo is coded in Python language combining symbolic mathematics with the SymPy library and numerical evaluation with the mpmath library , which provides arbitrary-precision floating-point calculation.
+
+
+ ",api,True,findable,0,0,0,0,1,2024-10-28T13:59:49.000Z,2024-10-28T13:59:49.000Z,cern.zenodo,cern,,,,,,,['HasVersion'],
+10.1594/pangaea.972515,Continuous Antarctic Carbon monoxide (CO) record (spline from 3 ice cores) from 1820 to 1995 CE,PANGAEA,2024,,Dataset,Creative Commons Attribution 4.0 International,"Continuous ice core carbon monoxide (CO) mixing ratios are presented for three West Antarctic Cores (Jurassic, Bryan Coast, and Dyer Plateau). Data cover from 1820 CE to 1995 CE. For each core, data are presented integrated at 10-second intervals from an original acquisition rate of 4 Hz. Data were measured continuously utilising Optical Feedback Cavity Enhanced Spectroscopy connected to a continuous ice core melting system at the British Antarctic Survey. A smoothed spline composed of the bottom 5th percentile of each record is also presented. A percentile re-sampling method is required to remove the impact of in situ production. The spline is used to interpret Southern Hemisphere CO variability from the pre-industrial with a particular focus on biomass burning.",mds,True,findable,0,0,1,0,0,2024-10-30T01:08:37.000Z,2024-10-30T01:08:37.000Z,pangaea.repository,pangaea,"biomass burning,carbon monoxide,Ice core,pre-industrial,Southern Hemisphere,Gas age,Carbon monoxide,Carbon monoxide, uncertainty,Ice drill,Average composite","[{'subject': 'biomass burning'}, {'subject': 'carbon monoxide'}, {'subject': 'Ice core'}, {'subject': 'pre-industrial'}, {'subject': 'Southern Hemisphere'}, {'subject': 'Gas age', 'subjectScheme': 'Parameter'}, {'subject': 'Carbon monoxide', 'subjectScheme': 'Parameter'}, {'subject': 'Carbon monoxide, uncertainty', 'subjectScheme': 'Parameter'}, {'subject': 'Ice drill', 'subjectScheme': 'Method'}, {'subject': 'Average composite', 'subjectScheme': 'Method'}]",['264 data points'],['text/tab-separated-values'],,,"['IsPartOf', 'References']",
+10.25577/fr1v-0577,Expertises bâtimentaires EMS-98 de bâtiments endommagés par le séisme de La Laigne du 16 juin 2023,"EOST UAR830, Université de Strasbourg, CNRS",2024,fr,Dataset,Creative Commons Attribution 4.0 International,"Ce jeu de données présente les résultats d’expertises bâtimentaires EMS-98, réalisées par le Groupe d’intervention macrosismique (GIM/Epos-France : EOST UAR830 &amp; ITES, RAP/ISterre, OMP/IRAP, IRSN) piloté par le BCSF-Rénass du 21 au 27 juin 2023 après le séisme de La Laigne du 16 juin 2023 (M=5,3).<br>Ce travail de terrain a été placé sous l’observation de deux experts en macrosismique d’EDF (Aix-en-Provence) et du CEA (Bruyères-le-Chatel).<br>Il s’agit principalement du degré de dommage EMS-98 (de 1 à 5) associé à la vulnérabilité sismique EMS-98 (A à F) du bâtiment.<br>Ces expertises ont été réalisées majoritairement à partir de la rue pour des raisons de sécurité, selon les critères de l’échelle macrosismique européenne EMS-98.<br>Les dommages aux bâtiments des deux communes de La Laigne (17201) et Cram-Chaban (17132) ont été relevés de façon complète, les autres communes expertisées ont été traitées par échantillonnage sur les dommages les plus importants indiqués par les mairies dans différentes classes de vulnérabilité (département 17 : Benon, Bouhet, Courçon, Ferrières, La Grève-sur-Mignon, Landrais, Le Gué-d'Alleré, Marans, Saint-Georges-du-Bois, Saint-Jean-de-Liversay, Saint-Pierre-d'Amilly, Saint-Saturnin-du-Bois, Saint-Sauveur-d'Aunis, Surgères, Vouhé; département 79 : Arçais, Mauzé-sur-le-Mignon, Saint-Hilaire-la-Palud).<br>Deux post-traitements ont été réalisés, l’un pour vérifier si les dommages expertisés n’étaient pas déjà présents avant le séisme grâce aux images Google Street View, l’autre pour confirmer les degrés de dommages et les vulnérabilités estimées à partir des données collectées par le GIM.<br>Les données sont géolocalisées avec une précision de 3 décimales (déviation possible de la localisation jusqu’à 100m).",fabricaForm,True,findable,0,0,0,0,0,2024-10-28T16:03:22.000Z,2024-10-29T15:30:50.000Z,inist.eost,jbru,"macrosismique,intensité,EMS-98,séisme,tremblement de terre,La Laigne,dommages aux constructions,vulnérabilité,structure,enquête de terrain,Charente-Maritime,catastrophe naturelle","[{'subject': 'macrosismique'}, {'subject': 'intensité'}, {'subject': 'EMS-98'}, {'subject': 'séisme'}, {'subject': 'tremblement de terre'}, {'subject': 'La Laigne'}, {'subject': 'dommages aux constructions'}, {'subject': 'vulnérabilité'}, {'subject': 'structure'}, {'subject': 'enquête de terrain'}, {'subject': 'Charente-Maritime'}, {'subject': 'catastrophe naturelle'}]",,['text/csv'],,,"['IsSourceOf', 'IsDocumentedBy', 'IsDocumentedBy', 'IsDocumentedBy']",