cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/28bea1cf041a7971fc79e11534e25745
title: Daily summarized seasonal measurements of discharge, water temperature, and specific conductivity from the Onyx River at Lower Wright, McMurdo Dry Valleys, Antarctica (1972-2020, ongoing)

description: As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a systematic sampling program has been undertaken to monitor the glacial meltwater streams in that region. This package contains daily summaries derived from 15-minute measurements of water quality and quantity parameters measured with automatic recording devices on streams in this region. Specifically, this metadata record describes the daily hydrological summaries for the McMurdo Dry Valley's Onyx River, located in the Wright Valley. Measurements commenced in 1972 and are ongoing. This dataset extends through the first half of the 2019-20 field season.
DOI: 10.6073/pasta/420a218a4f698b5bc856f8f1def675b2
title: Daily summarized seasonal measurements of discharge, water temperature, and specific conductivity from Adams Stream at M1, McMurdo Dry Valleys, Antarctica (2018-2020, ongoing)

description: As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a systematic sampling program has been undertaken to monitor the glacial meltwater streams in that region. This package contains daily summaries derived from 15-minute measurements of water quality and quantity parameters measured with automatic recording devices on streams in this region. Specifically, this metadata record describes the daily hydrological summaries for the McMurdo Dry Valleys' Adams Stream at the M1 streamgage, located in Miers Valley. Measurements commenced during the 2018-19 season. This dataset extends through the first half of the 2019-20 field season.
DOI: 10.6073/pasta/f101a3d8133dae794191ce21025fd793
title: Daily summarized seasonal measurements of discharge, water temperature, and specific conductivity from Miers Stream at M2, McMurdo Dry Valleys, Antarctica (2014-2020, ongoing)

description: As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a systematic sampling program has been undertaken to monitor the glacial meltwater streams in that region. This package contains daily summaries derived from 15-minute measurements of water quality and quantity parameters measured with automatic recording devices on streams in this region. Specifically, this metadata record describes the daily hydrological summaries for the McMurdo Dry Valleys' Miers Stream at the M2 streamgage, located in Miers Valley. Measurements commenced during the 2014-15 austral summer. This dataset extends through the first half of the 2019-20 field season.
DOI: 10.6084/m9.figshare.13218017
title: New Residential Landscapes: Lawn Data and Code

description: New residential landscapes in King County, Washington:<br>Metadata, four datasets, and two R scripts from dissertation on lawn floras, species diversity, urban environment, homeowner yard care goals, and homeowner lawn care practices.<br><br><br>
DOI: 10.6084/m9.figshare.13218017.v1
title: New Residential Landscapes: Lawn Data and Code

description: New residential landscapes in King County, Washington:<br>Metadata, four datasets, and two R scripts from dissertation on lawn floras, species diversity, urban environment, homeowner yard care goals, and homeowner lawn care practices.<br><br><br>
DOI: 10.6084/m9.figshare.14515587
title: Source Data for Nature Communications Cry14Ab Paper

description: Source Data for Nature Communications Cry14Ab Paper<br>
DOI: 10.6084/m9.figshare.14515587.v1
title: Source Data for Nature Communications Cry14Ab Paper

description: Source Data for Nature Communications Cry14Ab Paper<br>
DOI: 10.6084/m9.figshare.14515590
title: Supplementary data for 'More than 1000 rivers account for 80% of global riverine plsatic emissions into the ocean'

description: Here we provide the outputs from the model presented in Meijer et al. 2021 for the mid-point scenario of mismanaged plastic waste generation. The dataset distributed as GIS shapefile, represents 31,819 river outfalls emitting floating macro-plastic pollution globally. The emissions are expressed in metric tons per year.
DOI: 10.17632/gdhxwpc626.1
title: Data for: Late Permian medium-pressure metamorphism and closure of the Paleo-Asian Ocean in the eastern Central Asian Orogenic Belt: constraints from petrology, mineralogy, and geochronology of the Dongfengshan Group

description: The new data include SIMS U–Pb isotopic data of zircon and titanite, EMPA data of representative minerals, and P–T conditions calculation of metamorphic rocks from the Dongfengshan Group in the Songnen Massif, NE China.
DOI: 10.17632/6gc4597rgm.1
title: Data for: MULTICHANNEL PRESENCE, BOON OR CURSE?: A COMPARISON IN PRICE, LOYALTY, REGRET, AND DISAPPOINTMENT

description: Study 1 contains the data for the changes in emotion (positive and negative) by tracking consumer's facial expressions when they see promotion in online channel after purchasing from offline store in different price/loyalty contexts. Study 2 contains the self-reported survey data for regret and disappointment given the same scenario as Study 1 Study 3 contains the self-reported survey data for regret and disappointment when they see promotion in offline channel after purchasing from online store in different price/loyalty contexts.
DOI: 10.6084/m9.figshare.13370504.v12
title: Speedtest Open Data - Australia 2020 Q2, Q3, Q4 extract

description: This is an Australian extract of Speedtest Open data available at Amazon WS (link below - opendata.aws).<br>AWS data licence is "CC BY-NC-SA 4.0", so use of this data must be:- non-commercial (NC)- reuse must be share-alike (SA)(add same licence).This restricts the standard CC-BY Figshare licence.<br>A world speedtest open data was dowloaded (&gt;400Mb, 7M lines of data). An extract of Australia's location (lat, long) revealed 88,000 lines of data (attached as csv).<br>A Jupyter notebook of extract process is attached.A link to Twitter thread of outputs provided.A link to Data tutorial provided (GitHub), including Jupyter Notebook to analyse World Speedtest data, selecting one US State.<br>Data Shows: (Q2)- 3.1M speedtests- 762,000 devices- 88,000 grid locations (600m * 600m), summarised as a point- average speed 33.7Mbps (down), 12.4M (up)- Max speed 724Mbps- data is for 600m * 600m grids, showing average speed up/down, number of tests, and number of users (IP). Added centroid, and now lat/long.<br>See tweet of image of centroids also attached.<br>Versions:v12 - Added AUS - Syd - Mel Line Chart Q320.v11 - Add line chart compare Q2, Q3, Q4 plus Melb - result virtually indistinguishable. Add line chart to compare Syd - Melb Q3. Also virtually indistinguishable. Add HIST compare Syd - Melb Q3. Add new Jupyter with graph calcs (nbn-AUS-v1.3). Some ERRATA document in Notebook. Issue with resorting table, and graphing only part of table. Not an issue if all lines of table graphed.v10 - Load AURIN sample pics. Speedtest data loaded to AURIN geo-analytic platform; requires edu.au login.v9 - Add comparative Q2, Q3, Q4 Hist pic.v8 - Added Q4 data geojson. Add Q3, Q4 Hist pic.v7 - Rename to include Q2, Q3 in Title.v6 - Add Q3 20 data. Rename geojson AUS data as Q2. Add comparative Histogram. Calc in International.ipynb.v5 - add Jupyter Notebook inc Histograms. Hist is count of geo-locations avg download speed (unweighted by tests).v4 - added Melb choropleth (png 50Mpix) inc legend. (To do - add Melb.geojson). Posted Link to AURIN description of Speedtest data.v3 - Add super fast data (&gt;100Mbps) less than 1% of data - 697 lines. Includes png of superfast.plot(). Link below to Google Maps version of superfast data points. Also Google map of first 100 data points - sample data. Geojson format for loading into GeoPandas, per Jupyter Notebook. New version of Jupyter Notebook, v.1.1.v2 - add centroids image.v1 - initial data load.<br>** Future Work- combine Speedtest data with NBN Technology by location data (national map.gov.au); https://www.data.gov.au/dataset/national-broadband-network-connections-by-technology-type- combine Speedtest data with SEIFA data - socioeconomic categories - to discuss with AURIN.- Further international comparisons- discussed collaboration with Assoc Prof Tooran Alizadeh, USyd.
DOI: 10.25345/c5m23x
title: MassIVE Reanalysis RMSV000000319.3 - CoronaMassKB Hackathon: MassIVE/CCMS MSStats on Maestro /MaxQuant reanalysis of MSV000080025 / PXD004716 Human Calu-3 cell proteome response to Middle Eastern Respiratory Syndrome (icMERS) coronavirus
title: CoronaMassKB Hackathon: Early-access community reanalysis of mass spectrometry data. MassIVE/CCMS MSStats on Maestro /MaxQuant reanalysis of MSV000080025 / PXD004716 Human Calu-3 cell proteome response to Middle Eastern Respiratory Syndrome (icMERS) coronavirus
DOI: 10.5281/zenodo.4729027
title: CoVaxxy Tweet IDs data set

description: A collection of Tweet IDs related to Covid-19 Vaccines, gathered from Twitter since Jan 4, 2021. Please see https://arxiv.org/abs/2101.07694 for more information.
DOI: 10.25345/c5g810
title: MassIVE Reanalysis RMSV000000342.1 - CoronaMassKB Hackathon: MassIVE/CCMS MSStats on Maestro/ MaxQuant reanalysis of MSV000083529, MSV000083530, MSV000083531 Primary human airway epithelial cells proteome response to an icMERS coronavirus
title: CoronaMassKB Hackathon: Early-access community reanalysis of mass spectrometry data. MassIVE/CCMS MSStats on Maestro/ MaxQuant reanalysis of MSV000083529, MSV000083530, MSV000083531 Primary human airway epithelial cells proteome response to an icMERS coronavirus
DOI: 10.25345/c5bj85
title: MassIVE Reanalysis RMSV000000322.3 - CoronaMassKB Hackathon: MassIVE/CCMS MSStats on Maestro/ MaxQuant reanalysis of MSV000079703 / PXD004101, MSV000080029 / PXD004719, MSV000081888 Primary human microvascular endothelial cells Proteome response to an icMERS coronavirus
title: CoronaMassKB Hackathon: Early-access community reanalysis of mass spectrometry data. MassIVE/CCMS MSStats on Maestro/ MaxQuant reanalysis of MSV000079703 / PXD004101, MSV000080029 / PXD004719, MSV000081888 Primary human microvascular endothelial cells Proteome response to an icMERS coronavirus
DOI: 10.25345/c56r67
title: MassIVE Reanalysis RMSV000000341.2 - CoronaMassKB Hackathon: MassIVE/CCMS MSStats on Maestro reanalysis of MSV000085494 / PXD018357 Inhibition of growth factor signaling prevents SARS-CoV-2 replication (Non-phospho files only)
title: CoronaMassKB Hackathon: Early-access community reanalysis of mass spectrometry data. MassIVE/CCMS MSStats on Maestro reanalysis of MSV000085494 / PXD018357 Inhibition of growth factor signaling prevents SARS-CoV-2 replication (Non-phospho files only)
DOI: 10.6084/m9.figshare.14515722
title: Dexterous manual movement facilitates information processing in the primary somatosensory cortex

description: This is the data concerning the modulation of the primary somatosensory area during dexterous manual movement using a magnetoencephalography.
DOI: 10.6084/m9.figshare.14515722.v1
title: Dexterous manual movement facilitates information processing in the primary somatosensory cortex

description: This is the data concerning the modulation of the primary somatosensory area during dexterous manual movement using a magnetoencephalography.
DOI: 10.25345/c5324n
title: MassIVE Reanalysis RMSV000000343.1 - CoronaMassKB Hackathon: MassIVE/CCMS MSStats on Maestro/ MaxQuant reanalysis of MSV000085516 / PXD018970 Urine proteomics profiling of the COVID-19
title: CoronaMassKB Hackathon: Early-access community reanalysis of mass spectrometry data. MSStats on Maestro/ MaxQuant reanalysis of MSV000085516 / PXD018970 Urine proteomics profiling of the COVID-19
DOI: 10.6084/m9.figshare.14515803.v1
title: AI倫理指針リスト(2017/1-2021/4)

description: 2021年4月現在までに主要な倫理指針の一覧。国際的な指針および国内企業の指針を含む。
DOI: 10.6084/m9.figshare.14515803
title: AI倫理指針リスト(2017/1-2021/4)

description: 2021年4月現在までに主要な倫理指針の一覧。国際的な指針および国内企業の指針を含む。
DOI: 10.25345/c5z81b
title: MassIVE Reanalysis RMSV000000341.3 - CoronaMassKB Hackathon: MassIVE/CCMS MSStats on MS-GF+ reanalysis of MSV000085494 / PXD018357 Inhibition of growth factor signaling prevents SARS-CoV-2 replication, Phospho files only
title: CoronaMassKB Hackathon: Early-access community reanalysis of mass spectrometry data. MassIVE/CCMS MSStats on MS-GF+ reanalysis of MSV000085494 / PXD018357 Inhibition of growth factor signaling prevents SARS-CoV-2 replication, Phospho files only
DOI: 10.25345/c5tj9w
title: MassIVE Reanalysis RMSV000000321.3 - CoronaMassKB Hackathon: MassIVE/CCMS MSStats on Maestro/ MaxQuant reanalysis of MSV000079701 / PXD004100, MSV000080028 / PXD004718, MSV000081887 Primary human fibroblasts proteome response to an icMERS coronavirus
title: CoronaMassKB Hackathon: Early-access community reanalysis of mass spectrometry data. MassIVE/CCMS MSStats on Maestro/ MaxQuant reanalysis of MSV000079701 / PXD004100, MSV000080028 / PXD004718, MSV000081887 Primary human fibroblasts proteome response to an icMERS coronavirus
DOI: 10.22029/jlupub-12
title: Data for "The impact of negative mood on eventrelated potentials when viewing pornographic pictures"

description: Raw data, analysis syntax for the manuscript "The impact of negative mood on event-related potentials when viewing pornographic pictures"
DOI: 10.25345/c5pr6k
title: MassIVE Reanalysis RMSV000000341.4 - CoronaMassKB Hackathon: MassIVE/CCMS MSStats on MS-GF+ reanalysis of MSV000085494 / PXD018357 Inhibition of growth factor signaling prevents SARS-CoV-2 replication, Non-phospho files only
title: CoronaMassKB Hackathon: Early-access community reanalysis of mass spectrometry data. MassIVE/CCMS MSStats on MS-GF+ reanalysis of MSV000085494 / PXD018357 Inhibition of growth factor signaling prevents SARS-CoV-2 replication, Non-phospho files only
DOI: 10.6084/m9.figshare.13370504.v13
title: Speedtest Open Data - Australia 2020 Q2, Q3, Q4 extract

description: This is an Australian extract of Speedtest Open data available at Amazon WS (link below - opendata.aws).<br>AWS data licence is "CC BY-NC-SA 4.0", so use of this data must be:- non-commercial (NC)- reuse must be share-alike (SA)(add same licence).This restricts the standard CC-BY Figshare licence.<br>A world speedtest open data was dowloaded (&gt;400Mb, 7M lines of data). An extract of Australia's location (lat, long) revealed 88,000 lines of data (attached as csv).<br>A Jupyter notebook of extract process is attached.A link to Twitter thread of outputs provided.A link to Data tutorial provided (GitHub), including Jupyter Notebook to analyse World Speedtest data, selecting one US State.<br>Data Shows: (Q2)- 3.1M speedtests- 762,000 devices- 88,000 grid locations (600m * 600m), summarised as a point- average speed 33.7Mbps (down), 12.4M (up)- Max speed 724Mbps- data is for 600m * 600m grids, showing average speed up/down, number of tests, and number of users (IP). Added centroid, and now lat/long.<br>See tweet of image of centroids also attached.<br>Versions:v13 - Added three colour MELB map (less than 20Mbps, over 90Mbps, 20-90Mbps)v12 - Added AUS - Syd - Mel Line Chart Q320.v11 - Add line chart compare Q2, Q3, Q4 plus Melb - result virtually indistinguishable. Add line chart to compare Syd - Melb Q3. Also virtually indistinguishable. Add HIST compare Syd - Melb Q3. Add new Jupyter with graph calcs (nbn-AUS-v1.3). Some ERRATA document in Notebook. Issue with resorting table, and graphing only part of table. Not an issue if all lines of table graphed.v10 - Load AURIN sample pics. Speedtest data loaded to AURIN geo-analytic platform; requires edu.au login.v9 - Add comparative Q2, Q3, Q4 Hist pic.v8 - Added Q4 data geojson. Add Q3, Q4 Hist pic.v7 - Rename to include Q2, Q3 in Title.v6 - Add Q3 20 data. Rename geojson AUS data as Q2. Add comparative Histogram. Calc in International.ipynb.v5 - add Jupyter Notebook inc Histograms. Hist is count of geo-locations avg download speed (unweighted by tests).v4 - added Melb choropleth (png 50Mpix) inc legend. (To do - add Melb.geojson). Posted Link to AURIN description of Speedtest data.v3 - Add super fast data (&gt;100Mbps) less than 1% of data - 697 lines. Includes png of superfast.plot(). Link below to Google Maps version of superfast data points. Also Google map of first 100 data points - sample data. Geojson format for loading into GeoPandas, per Jupyter Notebook. New version of Jupyter Notebook, v.1.1.v2 - add centroids image.v1 - initial data load.<br>** Future Work- combine Speedtest data with NBN Technology by location data (national map.gov.au); https://www.data.gov.au/dataset/national-broadband-network-connections-by-technology-type- combine Speedtest data with SEIFA data - socioeconomic categories - to discuss with AURIN.- Further international comparisons- discussed collaboration with Assoc Prof Tooran Alizadeh, USyd.
DOI: 10.6084/m9.figshare.13621169.v12
title: Speedtest Open Data - Four International cities - MEL, BKK, SHG, LAX

description: This dataset compares four cities broadband internet speeds:- Melbourne, AU- Bangkok, TH- Shanghai, CN- Los Angeles, US<br>ERRATA:1.Data is for Q3 2020, but some files are labelled incorrectly as 02-20 of June 20. They all should read Sept 20, or 09-20 as Q3 20, rather than Q2. Will rename and reload.Amended in v7.<br>2. LAX file named 0320, when should be Q320.Amended in v8.<br><br>*lines of data for each geojson file; a line equates to a 600m^2 location, inc total tests, devices used, and average upload and download speed- MEL 16181 locations/lines =&gt; 0.85M speedtests (16.7 tests per 100people)- SHG 31745 lines =&gt; 0.65M speedtests (2.5/100pp)- BKK 29296 lines =&gt; 1.5M speedtests (14.3/100pp)- LAX 15899 lines =&gt; 1.3M speedtests (10.4/100pp)<br>Geojsons of these 2* by 2* extracts for MEL, BKK, SHG now added, and LAX added v6.<br>This dataset unpacks, geospatially, data summaries provided in Speedtest Global Index (linked below). See Jupyter Notebook (*.ipynb) to interrogate geo data. See link to install Jupyter.<br>** To DoWill add Google Map versions so everyone can see without installing Jupyter.- Link to Google Map (BKK) added below. Key:Green &gt; 100Mbps(Superfast). Black &gt; 500Mbps (Ultrafast). CSV provided. Code in Speedtestv1.1.ipynb Jupyter Notebook.<br>** Pythonmelb = au_tiles.cx[144:146 , -39:-37] #Lat/Lon extract<br>shg = tiles.cx[120:122 , 30:32] #Lat/Lon extract<br>bkk = tiles.cx[100:102 , 13:15] #Lat/Lon extract<br>lax = tiles.cx[-118:-120, 33:35] #lat/Lon extract<br>Histograms (v9), and data visualisations (v3,5,9,11) will be provided.Data Sourced from - This is an extract of Speedtest Open data available at Amazon WS (link below - opendata.aws).<br>**VERSIONSv13. Added Twitter link to pics.v12 Add Line-Compare pic (fastest 1000 locations) inc Jupyter (nbn-intl-v1.2.ipynb).v11 Add Line-Compare pic, plotting Four Cities on a graph.v10 Add Four Histograms in one pic.v9 Add Histogram for Four Cities. Add NBN-Intl.v1.1.ipynb (Jupyter Notebook).v8 Renamed LAX file to Q3, rather than 03.v7 Amended file names of BKK files to correctly label as Q3, not Q2 or 06.v6 Added LAX file.v5 Add screenshot of BKK Google Map.v4 Add BKK Google map(link below), and BKK csv mapping files. v3 replaced MEL map with big key version. Prev key was very tiny in top right corner.v2 Uploaded MEL, SHG, BKK data and Jupyter Notebookv1 Metadata record<br>** LICENCEAWS data licence on Speedtest data is "CC BY-NC-SA 4.0", so use of this data must be:- non-commercial (NC)- reuse must be share-alike (SA)(add same licence).This restricts the standard CC-BY Figshare licence.<br>** Other uses of Speedtest Open Data;- see link at Speedtest below.<br>
DOI: 10.25345/c5k23m
title: MassIVE Reanalysis RMSV000000316.3 - CoronaMassKB Hackathon: MassIVE/CCMS MSStats on Maestro/ MaxQuant reanalysis of MSV000085144 / PXD018117 A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Purposing
title: CoronaMassKB Hackathon: Early-access community reanalysis of mass spectrometry data. MassIVE/CCMS MSStats on Maestro/ MaxQuant reanalysis of MSV000085144 / PXD018117 A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Purposing
DOI: 10.6084/m9.figshare.13370504.v14
title: Speedtest Open Data - Australia 2020 Q2, Q3, Q4 extract

description: This is an Australian extract of Speedtest Open data available at Amazon WS (link below - opendata.aws).<br>AWS data licence is "CC BY-NC-SA 4.0", so use of this data must be:- non-commercial (NC)- reuse must be share-alike (SA)(add same licence).This restricts the standard CC-BY Figshare licence.<br>A world speedtest open data was dowloaded (&gt;400Mb, 7M lines of data). An extract of Australia's location (lat, long) revealed 88,000 lines of data (attached as csv).<br>A Jupyter notebook of extract process is attached.A link to Twitter thread of outputs provided.A link to Data tutorial provided (GitHub), including Jupyter Notebook to analyse World Speedtest data, selecting one US State.<br>Data Shows: (Q2)- 3.1M speedtests- 762,000 devices- 88,000 grid locations (600m * 600m), summarised as a point- average speed 33.7Mbps (down), 12.4M (up)- Max speed 724Mbps- data is for 600m * 600m grids, showing average speed up/down, number of tests, and number of users (IP). Added centroid, and now lat/long.<br>See tweet of image of centroids also attached.<br>Versions:v14 Add AUS Speedtest Q1 2021 geojson.(79k lines avg d/l 45.4Mbps)v13 - Added three colour MELB map (less than 20Mbps, over 90Mbps, 20-90Mbps)v12 - Added AUS - Syd - Mel Line Chart Q320.v11 - Add line chart compare Q2, Q3, Q4 plus Melb - result virtually indistinguishable. Add line chart to compare Syd - Melb Q3. Also virtually indistinguishable. Add HIST compare Syd - Melb Q3. Add new Jupyter with graph calcs (nbn-AUS-v1.3). Some ERRATA document in Notebook. Issue with resorting table, and graphing only part of table. Not an issue if all lines of table graphed.v10 - Load AURIN sample pics. Speedtest data loaded to AURIN geo-analytic platform; requires edu.au login.v9 - Add comparative Q2, Q3, Q4 Hist pic.v8 - Added Q4 data geojson. Add Q3, Q4 Hist pic.v7 - Rename to include Q2, Q3 in Title.v6 - Add Q3 20 data. Rename geojson AUS data as Q2. Add comparative Histogram. Calc in International.ipynb.v5 - add Jupyter Notebook inc Histograms. Hist is count of geo-locations avg download speed (unweighted by tests).v4 - added Melb choropleth (png 50Mpix) inc legend. (To do - add Melb.geojson). Posted Link to AURIN description of Speedtest data.v3 - Add super fast data (&gt;100Mbps) less than 1% of data - 697 lines. Includes png of superfast.plot(). Link below to Google Maps version of superfast data points. Also Google map of first 100 data points - sample data. Geojson format for loading into GeoPandas, per Jupyter Notebook. New version of Jupyter Notebook, v.1.1.v2 - add centroids image.v1 - initial data load.<br>** Future Work- combine Speedtest data with NBN Technology by location data (national map.gov.au); https://www.data.gov.au/dataset/national-broadband-network-connections-by-technology-type- combine Speedtest data with SEIFA data - socioeconomic categories - to discuss with AURIN.- Further international comparisons- discussed collaboration with Assoc Prof Tooran Alizadeh, USyd.
DOI: 10.6084/m9.figshare.14096912.v1
title: Table of plastisphere studies

description: Placeholder for the table of studies that are included in the figures of the review chapter