cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12768806
title: Additional file 3 of Transcriptomic profiling revealed key signaling pathways for cold tolerance and acclimation of two carp species

description: Additional file 3. Validation of RNA-seq data by qPCR.
DOI: 10.6084/m9.figshare.12768806.v1
title: Additional file 3 of Transcriptomic profiling revealed key signaling pathways for cold tolerance and acclimation of two carp species

description: Additional file 3. Validation of RNA-seq data by qPCR.
DOI: 10.6084/m9.figshare.19579933
title: Additional file 1 of ANGPTL3 impacts proteinuria and hyperlipidemia in primary nephrotic syndrome

description: Additional file 1.
DOI: 10.5281/zenodo.4018520
title: Dataset related to article: "Psychosocial Cardiological Schedule-Revised (PCS-R) in a Cardiac Rehabilitation Unit: Reflections Upon Data Collection (2010–2017) and New Challenges"

description: <strong>Introduction: </strong>The Psychosocial Cardiological Schedule (PCS) was developed as a screening tool for patients undergoing cardiac rehabilitation (CR) to detect clinically relevant psychosocial/cognitive problems requiring psychological assessment/intervention. Filled out by a trained nurse, it classifies patients according to their need or not for a psychological interview and intervention provided by the psychologist (PCS-Yes vs. PCS-No). <strong>Aims: </strong>The main aim was to compare PCS data collected, respectively, in 2010 and 2017, regarding patients' socio-demographic characteristics, clinical variables, and the inclusion criteria for psychological counseling. Subsequently, the original Italian PCS was revised and an English version of the schedule was provided [PCS-Revised (PCS-R)]. <strong>Results: </strong>28 patients (aged 53.5 + 12.6 years, M = 20) of the 87 recruited in 2010 vs. 35 (aged 64.9 + 12.7 years, M = 28) of the 83 recruited in 2017 met the criteria for PCS-Yes: age &lt; 55 years, social problems (living alone, no social support), manifest psychological/behavioral problems, suspected neuropsychological disorders, low prescription adherence, inadequate disease awareness. Comparing the two samples (2010 vs. 2017), clinical variables were similar, and the need for a psychological interview did not differ substantially (32.2 vs. 42.2%), but age increased significantly (PCS-Yes: 53.5 ± 12.6 vs. 64.9 ± 12.7 years, <em>p</em> = 0.001; PCS-No: 68.3 ± 8.0 vs. 75.0 ± 7.7 years, <em>p</em> = 0.0001). A significant increase was observed in the recommendation for neuropsychological assessment (3.6 vs. 25.7%, <em>p</em> = 0.02) to confirm eventual cognitive deficits. These results, the clinical experience, and the recent evidences from literature led to the PCS-R, incorporating a psychosocial screening, a psychological/neuropsychological deeper assessment, and a recommendation for a specific intervention to be carried out either during rehabilitation or in outpatient services. <strong>Conclusion: </strong>The data comparison highlight changes in the cardiac population, which is aging and more frequently requires neuropsychological assessment. The PCS-R could be considered in clinical practice as a useful screening tool to implement a timely coordinated interdisciplinary intervention, comprehensive of specific and tailored psychotherapeutic techniques.
DOI: 10.5281/zenodo.4018519
title: Dataset related to article: "Psychosocial Cardiological Schedule-Revised (PCS-R) in a Cardiac Rehabilitation Unit: Reflections Upon Data Collection (2010–2017) and New Challenges"

description: <strong>Introduction: </strong>The Psychosocial Cardiological Schedule (PCS) was developed as a screening tool for patients undergoing cardiac rehabilitation (CR) to detect clinically relevant psychosocial/cognitive problems requiring psychological assessment/intervention. Filled out by a trained nurse, it classifies patients according to their need or not for a psychological interview and intervention provided by the psychologist (PCS-Yes vs. PCS-No). <strong>Aims: </strong>The main aim was to compare PCS data collected, respectively, in 2010 and 2017, regarding patients' socio-demographic characteristics, clinical variables, and the inclusion criteria for psychological counseling. Subsequently, the original Italian PCS was revised and an English version of the schedule was provided [PCS-Revised (PCS-R)]. <strong>Results: </strong>28 patients (aged 53.5 + 12.6 years, M = 20) of the 87 recruited in 2010 vs. 35 (aged 64.9 + 12.7 years, M = 28) of the 83 recruited in 2017 met the criteria for PCS-Yes: age &lt; 55 years, social problems (living alone, no social support), manifest psychological/behavioral problems, suspected neuropsychological disorders, low prescription adherence, inadequate disease awareness. Comparing the two samples (2010 vs. 2017), clinical variables were similar, and the need for a psychological interview did not differ substantially (32.2 vs. 42.2%), but age increased significantly (PCS-Yes: 53.5 ± 12.6 vs. 64.9 ± 12.7 years, <em>p</em> = 0.001; PCS-No: 68.3 ± 8.0 vs. 75.0 ± 7.7 years, <em>p</em> = 0.0001). A significant increase was observed in the recommendation for neuropsychological assessment (3.6 vs. 25.7%, <em>p</em> = 0.02) to confirm eventual cognitive deficits. These results, the clinical experience, and the recent evidences from literature led to the PCS-R, incorporating a psychosocial screening, a psychological/neuropsychological deeper assessment, and a recommendation for a specific intervention to be carried out either during rehabilitation or in outpatient services. <strong>Conclusion: </strong>The data comparison highlight changes in the cardiac population, which is aging and more frequently requires neuropsychological assessment. The PCS-R could be considered in clinical practice as a useful screening tool to implement a timely coordinated interdisciplinary intervention, comprehensive of specific and tailored psychotherapeutic techniques.
DOI: 10.21227/psy6-0b07
title: Wireless Sensor Networks Dataset (TSCH a Compromise Between Reliability, Power Consumption, and Latency)

description: Performance of Wireless Sensor Networks (WSN) based on IEEE 802.15.4 and Time Slotted Channel Hopping (TSCH) has been shown to be mostly predictable in typical real-world operating conditions. This is especially true for performance indicators like reliability, power consumption, and latency. This article provides and describes a database (i.e., a set of data acquired with real devices deployed in a real environment) about measurements on OpenMote B devices, implementing the 6TiSCH protocol, made in different experimental configurations. A post-analysis Python script for calculating the above performance indicators from values stored in the database is additional provided. The results obtained by applying the script to the included database were published in [1], which contains more details than those reported in this short presentation of the dataset. Data and software are useful for two main reasons: on the one hand the dataset can be further processed to obtain new performance indices, so as to support, e.g., new ideas about possible protocol modifications; on the other hand, they constitute a simple yet effective example of measurement technique (based on the ping tool and on the accompanying script), which can be customized at will and reused to analyze the performance of other real TSCH installations.
DOI: 10.21227/avdp-6q45
title: Test

description: 1
DOI: 10.5281/zenodo.4288440
title: SciGRID_gas IGGINL

description: This data set has been was generated by combining the following data sources:<br> • InternetDaten data set (INET)<br> • Gas Infrastructure Europe data set (GIE)<br> • Gas Storages Europe data set (GSE)<br> • International Gas Union data set (IGU)<br> • Norway data set (NO).<br> • Long-term Planning and Short-term Optimization data set (LKD) .<br>
DOI: 10.5281/zenodo.4288439
title: SciGRID_gas IGGINL

description: This data set has been was generated by combining the following data sources:<br> • InternetDaten data set (INET)<br> • Gas Infrastructure Europe data set (GIE)<br> • Gas Storages Europe data set (GSE)<br> • International Gas Union data set (IGU)<br> • Norway data set (NO).<br> • Long-term Planning and Short-term Optimization data set (LKD) .<br>
DOI: 10.25502/v1f3-6a57/d
title: Yam tuber production in the aeroponics - 2018

description:  Propagation of clean seed yam in high ratio propagation techniques(aeroponics)
DOI: 10.5517/ccdc.csd.cc23p1mh
title: CCDC 1956646: Experimental Crystal Structure Determination

description: Related Article: Kun Fan, Song-Song Bao, Ran Huo, Xin-Da Huang, Yu-Jie Liu, Zi-Wen Yu, Mohamedally Kurmoo, Li-Min Zheng|2020|Inorg.Chem.Front.|7|4580|doi:10.1039/C9QI01504C
DOI: 10.5517/ccdc.csd.cc23p1ql
title: CCDC 1956649: Experimental Crystal Structure Determination

description: Related Article: Kun Fan, Song-Song Bao, Ran Huo, Xin-Da Huang, Yu-Jie Liu, Zi-Wen Yu, Mohamedally Kurmoo, Li-Min Zheng|2020|Inorg.Chem.Front.|7|4580|doi:10.1039/C9QI01504C
DOI: 10.5517/ccdc.csd.cc23p1pk
title: CCDC 1956648: Experimental Crystal Structure Determination

description: Related Article: Kun Fan, Song-Song Bao, Ran Huo, Xin-Da Huang, Yu-Jie Liu, Zi-Wen Yu, Mohamedally Kurmoo, Li-Min Zheng|2020|Inorg.Chem.Front.|7|4580|doi:10.1039/C9QI01504C
DOI: 10.5517/ccdc.csd.cc23p1nj
title: CCDC 1956647: Experimental Crystal Structure Determination

description: Related Article: Kun Fan, Song-Song Bao, Ran Huo, Xin-Da Huang, Yu-Jie Liu, Zi-Wen Yu, Mohamedally Kurmoo, Li-Min Zheng|2020|Inorg.Chem.Front.|7|4580|doi:10.1039/C9QI01504C
DOI: 10.5517/ccdc.csd.cc24372l
title: CCDC 1969308: Experimental Crystal Structure Determination

description: Related Article: Hua Huang, Qing-Zhu Li, Yan-Qing Liu, Hai-Jun Leng, Peng Xiang, Qing-Song Dai, Xiang-Hong He, Wei Huang, Jun-Long Li|2020|Org.Chem.Front.|7|3862|doi:10.1039/D0QO00868K
DOI: 10.5517/ccdc.csd.cc1p9ynl
title: CCDC 1558700: Experimental Crystal Structure Determination

description: Related Article: Senqiang Zhu, Jinyang Hu, Shengliang Zhai, Yutian Wang, Zengchuang Xu, Rui Liu, Hongjun Zhu|2020|Inorg.Chem.Front.|7|4677|doi:10.1039/D0QI00735H
description: Related Article: Sen-Qiang Zhu|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc25g36z
title: CCDC 2009550: Experimental Crystal Structure Determination

description: Related Article: Yu-Ting Liu, Lei He, Ping-Ping Shi, Qiong Ye, Da-Wei Fu|2020|Chem.Commun.|56|13764|doi:10.1039/D0CC05648K
DOI: 10.5517/ccdc.csd.cc25zn1w
title: CCDC 2025448: Experimental Crystal Structure Determination

description: Related Article: Bin Li, Chenhao Guo, Nana Shen, Xinying Zhang, Xuesen Fan|2020|Org.Chem.Front.|7|3698|doi:10.1039/D0QO01109F
DOI: 10.5517/ccdc.csd.cc249kcd
title: CCDC 1975393: Experimental Crystal Structure Determination

description: Related Article: Burcu Aydıner, Ömer Şahin, Deniz Çakmaz, Gökhan Kaplan, Kerem Kaya, Ümmühan Özmen Özdemir, Nurgül Seferoğlu, Zeynel Seferoğlu|2020|New J.Chem.|44|19155|doi:10.1039/D0NJ03003A
DOI: 10.5517/ccdc.csd.cc23czwc
title: CCDC 1947943: Experimental Crystal Structure Determination

description: Related Article: Xue-Mei Zhang, Yao-Yao Duan, Hong-Ling Gao, Jian-Zhong Cui|2020|New J.Chem.|44|19135|doi:10.1039/D0NJ03837G
DOI: 10.5517/ccdc.csd.cc239tdn
title: CCDC 1945851: Experimental Crystal Structure Determination

description: Related Article: Xue-Mei Zhang, Yao-Yao Duan, Hong-Ling Gao, Jian-Zhong Cui|2020|New J.Chem.|44|19135|doi:10.1039/D0NJ03837G
DOI: 10.5517/ccdc.csd.cc235npn
title: CCDC 1941861: Experimental Crystal Structure Determination

description: Related Article: Xue-Mei Zhang, Yao-Yao Duan, Hong-Ling Gao, Jian-Zhong Cui|2020|New J.Chem.|44|19135|doi:10.1039/D0NJ03837G
DOI: 10.5517/ccdc.csd.cc23czl2
title: CCDC 1947934: Experimental Crystal Structure Determination

description: Related Article: Xue-Mei Zhang, Yao-Yao Duan, Hong-Ling Gao, Jian-Zhong Cui|2020|New J.Chem.|44|19135|doi:10.1039/D0NJ03837G
DOI: 10.5517/ccdc.csd.cc239tlv
title: CCDC 1945857: Experimental Crystal Structure Determination

description: Related Article: Xue-Mei Zhang, Yao-Yao Duan, Hong-Ling Gao, Jian-Zhong Cui|2020|New J.Chem.|44|19135|doi:10.1039/D0NJ03837G
DOI: 10.5517/ccdc.csd.cc239thr
title: CCDC 1945854: Experimental Crystal Structure Determination

description: Related Article: Xue-Mei Zhang, Yao-Yao Duan, Hong-Ling Gao, Jian-Zhong Cui|2020|New J.Chem.|44|19135|doi:10.1039/D0NJ03837G
DOI: 10.5517/ccdc.csd.cc235nqp
title: CCDC 1941862: Experimental Crystal Structure Determination

description: Related Article: Xue-Mei Zhang, Yao-Yao Duan, Hong-Ling Gao, Jian-Zhong Cui|2020|New J.Chem.|44|19135|doi:10.1039/D0NJ03837G
DOI: 10.5517/ccdc.csd.cc23yfvc
title: CCDC 1964713: Experimental Crystal Structure Determination

description: Related Article: Sen-Da Su, Jia-Xin Li, Fan Xu, Chen-Xiao Wang, Kai Wang, Yan Li, Shu-Hua Zhang, Xiu-Qing Zhang, Yi-Quan Zhang, Fu-Pei Liang|2020|Dalton Trans.|49|15739|doi:10.1039/C9DT04434E
DOI: 10.5517/ccdc.csd.cc23yfwd
title: CCDC 1964714: Experimental Crystal Structure Determination

description: Related Article: Sen-Da Su, Jia-Xin Li, Fan Xu, Chen-Xiao Wang, Kai Wang, Yan Li, Shu-Hua Zhang, Xiu-Qing Zhang, Yi-Quan Zhang, Fu-Pei Liang|2020|Dalton Trans.|49|15739|doi:10.1039/C9DT04434E
DOI: 10.5517/ccdc.csd.cc23yfxf
title: CCDC 1964715: Experimental Crystal Structure Determination

description: Related Article: Sen-Da Su, Jia-Xin Li, Fan Xu, Chen-Xiao Wang, Kai Wang, Yan Li, Shu-Hua Zhang, Xiu-Qing Zhang, Yi-Quan Zhang, Fu-Pei Liang|2020|Dalton Trans.|49|15739|doi:10.1039/C9DT04434E
DOI: 10.5525/gla.researchdata.1072
title: Identifying Differing Intracellular Cargo Release Mechanisms by Monitoring in vitro Drug Delivery from MOFs in Real Time
DOI: 10.25502/7yp2-7r11/d
title: Yam tuber production in the aeroponics - 2019

description:  Yam Improvement for Income and Food Security in West Africa
DOI: 10.21227/sqck-d230
title: Test

description: 1
DOI: 10.21227/pvc3-9h58
title: Test

description: 1
DOI: 10.6084/m9.figshare.13280930
title: Wave fetch for South Africa and Namibia at 100m scale

description: This data layer gives values of summed wave fetch in 32 angular sectors around focal cells, using a model modified from that given in Burrows et al (2012 - see reference). Wave fetch is the distance to the nearest land in a defined direction. The model performs a three-scale search for land around each cell in the model, sparsely (every 10km) up to 200km, every 1km up to 20km away, and every 100m up to 1km distant. Fetch is calculated up to 5km from the coastline.<br>Values represent the summed number of grid cells to the nearest land across all 32 11.5° sectors. Files are GeoTIFFs using the WGS84 projection.<br>
DOI: 10.6084/m9.figshare.13280930.v1
title: Wave fetch for South Africa and Namibia at 100m scale

description: This data layer gives values of summed wave fetch in 32 angular sectors around focal cells, using a model modified from that given in Burrows et al (2012 - see reference). Wave fetch is the distance to the nearest land in a defined direction. The model performs a three-scale search for land around each cell in the model, sparsely (every 10km) up to 200km, every 1km up to 20km away, and every 100m up to 1km distant. Fetch is calculated up to 5km from the coastline.<br>Values represent the summed number of grid cells to the nearest land across all 32 11.5° sectors. Files are GeoTIFFs using the WGS84 projection.<br>
DOI: 10.21227/vhzz-pq51
title: Test

description: 1
DOI: 10.24378/exe.2904
title: Development of exploration tools for porphyry-breccia-hosted mineral deposits (Appendix iii QEMSCAN data)

description: Appendix iii for the Doctoral thesis "Development of exploration tools for porphyry-breccia-hosted mineral deposits".
description: QEMSCAN data for samples associated with PhD
description: The thesis associated with this dataset is located in ORE at: http://hdl.handle.net/10871/123750
DOI: 10.24378/exe.2905
title: Development of exploration tools for porphyry-breccia-hosted mineral deposits (Appendix iv - XRD data)

description: Appendix iv for the Doctoral thesis "Development of exploration tools for porphyry-breccia-hosted mineral deposits".
description: Spreadsheet containing XRD data.
description: The thesis associated with this dataset is located in ORE at: http://hdl.handle.net/10871/123750
DOI: 10.24378/exe.2906
title: Development of exploration tools for porphyry-breccia-hosted mineral deposits (Appendix v Tourmaline EPMA and LA-ICP-MS)

description: Appendix v for the Doctoral thesis "Development of exploration tools for porphyry-breccia-hosted mineral deposits".
description: Excel spreadsheet containing tourmaline EPMA and LA-ICP-MS data.
description: The thesis associated with this dataset is located in ORE at: http://hdl.handle.net/10871/123750
DOI: 10.24378/exe.2907
title: Development of exploration tools for porphyry-breccia-hosted mineral deposits (Appendix vi Ti_in_quartz)

description: Appendix vi for the Doctoral thesis "Development of exploration tools for porphyry-breccia-hosted mineral deposits".
description: Excel spreadsheet containing Ti-in-quartz data.
description: The thesis associated with this dataset is located in ORE at: http://hdl.handle.net/10871/123750
DOI: 10.24378/exe.2908
title: Development of exploration tools for porphyry-breccia-hosted mineral deposits (Appendix vii Whole Rock raw data)

description: Appendix vii for the Doctoral thesis "Development of exploration tools for porphyry-breccia-hosted mineral deposits".
description: Excel spreadsheet containing whole-rock data of the samples crushed and ground during PhD.
description: The thesis associated with this dataset is located in ORE at: http://hdl.handle.net/10871/123750
DOI: 10.5285/b3a75382-31db-428c-90bb-458fdf66d77a
title: Initiation files for Fluidity numerical modelling code, used in the paper Suchoy et al., 2020

description: Initiation files for 2D numerical models for Fluidity code. The models simulate subduction of an oceanic plate under various conditions described in Suchoy et al., 2020. The models use temperature, pressure and strain-rate dependent composite rheology, which generates different regions without prescribing material fields. The models are similar in nature to other geodynamic models (e.g. Billen and Arredondo, 2018) and can be used for further investigation of subduction dynamics, and to reproduce the results presented in Suchoy et al., 2020. For further enquiries regarding these models please contact Lior Suchoy (Imperial College London), Saskia Goes (Imperial College London) or Rhodri Davies (Australia National University).
DOI: 10.5281/zenodo.4090953
title: Data and code for the paper Atmospheric Observations with E-band Microwave Links – Challenges and Opportunities

description: Raw and preprocessed data for the paper Atmospheric Observations with E-band Microwave Links – Challenges and Opportunities accepted for publication in the journal Atmospheric Measurement Techniques. The dataset includes total losses (transmitted - received power levels) of commercial microwave links and observations of rainfall, air temperature, and air relative humidity. In addition, theoretical gaseous attenuation calculated from air temperature and relative humidity is provided. Data are stored in semicolon-delimited csv files. Time stamps are in UTC time in the format yyyy-mm-dd HH:MM:SS. Raw data contain not regular time series, preprocessed data contain regular time series at 1-min and 5-min temporal resolution. Metadata are stored in textfiles. Dataset contains also R code for processing and analyzing the data as presented in the paper Atmospheric Observations with E-band Microwave Links – Challenges and Opportunities. The code is in the form of R Markdown files and interactive html notebooks.
description: The collection and curation of the dataset was supported by the project of Czech Science Foundation (GACR) No. 17-16389S and 20-14151J. The dataset was collected to evaluate E-band commercial microwave links as opportunistic sensors of rainfall and water vapor.
DOI: 10.5281/zenodo.3632094
title: Data and code for the paper Atmospheric Observations with E-band Microwave Links – Challenges and Opportunities

description: Raw and preprocessed data for the paper Atmospheric Observations with E-band Microwave Links – Challenges and Opportunities accepted for publication in the journal Atmospheric Measurement Techniques. The dataset includes total losses (transmitted - received power levels) of commercial microwave links and observations of rainfall, air temperature, and air relative humidity. In addition, theoretical gaseous attenuation calculated from air temperature and relative humidity is provided. Data are stored in semicolon-delimited csv files. Time stamps are in UTC time in the format yyyy-mm-dd HH:MM:SS. Raw data contain not regular time series, preprocessed data contain regular time series at 1-min and 5-min temporal resolution. Metadata are stored in textfiles. Dataset contains also R code for processing and analyzing the data as presented in the paper Atmospheric Observations with E-band Microwave Links – Challenges and Opportunities. The code is in the form of R Markdown files and interactive html notebooks.
description: The collection and curation of the dataset was supported by the project of Czech Science Foundation (GACR) No. 17-16389S and 20-14151J. The dataset was collected to evaluate E-band commercial microwave links as opportunistic sensors of rainfall and water vapor.
DOI: 10.5281/zenodo.4288913
title: Validation of ESA CCI SM combined v05.2 vs ISMN 20191211 global - Anomalies and ISMN flagged

description: QA4SM validation of soil moisture data: ESA CCI SM combined v05.2 vs ISMN 20191211 global. URL: https://qa4sm.eu/result/d8b5f409-2bb3-4580-be0b-0c9c2d71c968/. Produced on QA4SM (https://qa4sm.eu)
DOI: 10.5281/zenodo.4288912
title: Validation of ESA CCI SM combined v05.2 vs ISMN 20191211 global - Anomalies and ISMN flagged

description: QA4SM validation of soil moisture data: ESA CCI SM combined v05.2 vs ISMN 20191211 global. URL: https://qa4sm.eu/result/d8b5f409-2bb3-4580-be0b-0c9c2d71c968/. Produced on QA4SM (https://qa4sm.eu)
DOI: 10.5281/zenodo.4288915
title: Validation of ESA CCI SM combined v05.2 vs ISMN 20191211 global - Anomalies and no ISMN flags

description: QA4SM validation of soil moisture data: ESA CCI SM combined v05.2 vs ISMN 20191211 global. URL: https://qa4sm.eu/result/5f6ae4c5-5115-4022-b489-99f4dda1089f/. Produced on QA4SM (https://qa4sm.eu)
DOI: 10.5281/zenodo.4288914
title: Validation of ESA CCI SM combined v05.2 vs ISMN 20191211 global - Anomalies and no ISMN flags

description: QA4SM validation of soil moisture data: ESA CCI SM combined v05.2 vs ISMN 20191211 global. URL: https://qa4sm.eu/result/5f6ae4c5-5115-4022-b489-99f4dda1089f/. Produced on QA4SM (https://qa4sm.eu)
DOI: 10.18430/m36tm8
title: X-ray diffraction data for the crystal structure of glycoprotein D of Equine Herpesvirus Type 4 (6TM8)
DOI: 10.5281/zenodo.4288919
title: Validation of ESA CCI SM combined v05.2 vs ISMN 20191211 global - without anomalies and without ISMN flags

description: QA4SM validation of soil moisture data: ESA CCI SM combined v05.2 vs ISMN 20191211 global. URL: https://qa4sm.eu/result/bbf7f693-74ff-4b03-8f5d-792b7b846b40/. Produced on QA4SM (https://qa4sm.eu)
DOI: 10.5281/zenodo.4288918
title: Validation of ESA CCI SM combined v05.2 vs ISMN 20191211 global - without anomalies and without ISMN flags

description: QA4SM validation of soil moisture data: ESA CCI SM combined v05.2 vs ISMN 20191211 global. URL: https://qa4sm.eu/result/bbf7f693-74ff-4b03-8f5d-792b7b846b40/. Produced on QA4SM (https://qa4sm.eu)
DOI: 10.5281/zenodo.4288921
title: Validation of ESA CCI SM combined v05.2 vs ISMN 20191211 global - without Anomalies and ISMN flagged

description: QA4SM validation of soil moisture data: ESA CCI SM combined v05.2 vs ISMN 20191211 global. URL: https://qa4sm.eu/result/73ed1e31-eaa5-469a-ab9b-4451e4e4d4df/. Produced on QA4SM (https://qa4sm.eu)