cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48370/ofd/uoxgem
title: Prosienicznik szorstki (Hypochoeris radicata L.), 8458

description: Herbarium
DOI: 10.48370/ofd/kkpcfh/amh6iq
title: HMW_Milium_effusum_L._H_1681.jpg

description: :unav
DOI: 10.48370/ofd/kkpcfh
title: Prosownica rozpierzchła (Milium effusum L.), 1681

description: Herbarium
DOI: 10.48370/ofd/wk6bdh/rbx4sl
title: HMW_Milium_effusum_L._H_1754.jpg

description: :unav
DOI: 10.48370/ofd/wk6bdh
title: Prosownica rozpierzchła (Milium effusum L.), 1754

description: Herbarium
DOI: 10.34740/kaggle/dsv/2503908
title: Latest Covid-19 Global Countrywise Data
DOI: 10.5281/zenodo.5167248
title: Dataset of "Knowledge-based Sense Disambiguation of Multiword Expressions in Requirements Documents"

description: This is the dataset used in the paper "Knowledge-based Sense Disambiguation of Multiword Expressions in Requirements Documents" at AIRE'21 In this paper, we explore the use of a multiword expression detection in combination with a knowledge-based word sense disambiguation to disambiguate expressions in requirements documents. The dataset comprises a gold standard for multiword expression detection and sense disambiguation for Wikipedia and WordNet 3.1. It covers 18 projects: CM1, EBT and GANTT as well as the 15 projects of the NFR dataset. <strong>File format</strong> We use a tab-separated version of the DiMSUM file format and extended it with sense information. The nine original DiMSUM tab-separated columns: 1. token offset 2. word 3. lowercase lemma 4. POS 5. MWE tag 6. offset of parent token (i.e. previous token in the same MWE), if applicable 7. strength level encoded in the tag, if applicable. Currently not used 8. supersense label, Currently not used 9. sentence ID and the two further columns for sense information: 10. Wikipedia article name 11. WordNet 3.1 synset The last two columns might end with .1 or .0 indicating that the sense is a fully applicable or partial sense of a multiword expression. <strong>Attribution (of datasets used)</strong> The NFR Dataset can be attributed to Jane Cleland-Huang.<br> Jane Cleland-Huang, Sepideh Mazrouee, Huang Liguo, & Dan Port. (2007). nfr [Data set]. Zenodo. Available: http://doi.org/10.5281/zenodo.268542<br> The CM1, EBT and GANTT datasets were retrieved from the Center of Excellence for Software & Systems Traceability (CoEST) http://coest.org/
DOI: 10.5281/zenodo.5167247
title: Dataset of "Knowledge-based Sense Disambiguation of Multiword Expressions in Requirements Documents"

description: This is the dataset used in the paper "Knowledge-based Sense Disambiguation of Multiword Expressions in Requirements Documents" at AIRE'21 In this paper, we explore the use of a multiword expression detection in combination with a knowledge-based word sense disambiguation to disambiguate expressions in requirements documents. The dataset comprises a gold standard for multiword expression detection and sense disambiguation for Wikipedia and WordNet 3.1. It covers 18 projects: CM1, EBT and GANTT as well as the 15 projects of the NFR dataset. <strong>File format</strong> We use a tab-separated version of the DiMSUM file format and extended it with sense information. The nine original DiMSUM tab-separated columns: 1. token offset 2. word 3. lowercase lemma 4. POS 5. MWE tag 6. offset of parent token (i.e. previous token in the same MWE), if applicable 7. strength level encoded in the tag, if applicable. Currently not used 8. supersense label, Currently not used 9. sentence ID and the two further columns for sense information: 10. Wikipedia article name 11. WordNet 3.1 synset The last two columns might end with .1 or .0 indicating that the sense is a fully applicable or partial sense of a multiword expression. <strong>Attribution (of datasets used)</strong> The NFR Dataset can be attributed to Jane Cleland-Huang.<br> Jane Cleland-Huang, Sepideh Mazrouee, Huang Liguo, & Dan Port. (2007). nfr [Data set]. Zenodo. Available: http://doi.org/10.5281/zenodo.268542<br> The CM1, EBT and GANTT datasets were retrieved from the Center of Excellence for Software & Systems Traceability (CoEST) http://coest.org/
DOI: 10.48370/ofd/t7t5y1/jprzio
title: HMW_Milium_effusum_L._H_0252.jpg

description: :unav
DOI: 10.48370/ofd/t7t5y1
title: Prosownica rozpierzchła (Milium effusum L.), 252

description: Herbarium
DOI: 10.48370/ofd/bst1dl/dricei
title: HMW_Milium_effusum_L._H_0058.jpg

description: :unav
DOI: 10.48370/ofd/bst1dl
title: Prosownica rozpierzchła (Milium effusum L.), 58

description: Herbarium
DOI: 10.48370/ofd/j9r3wn/cnfkni
title: HMW_Milium_effusum_L._H_8255.jpg

description: :unav
DOI: 10.48370/ofd/j9r3wn
title: Prosownica rozpierzchła (Milium effusum L.), 8255

description: Herbarium
DOI: 10.48370/ofd/6rdazk/3uacaw
title: HMW_Milium_effusum_L._H_8535.jpg

description: :unav
DOI: 10.48370/ofd/6rdazk
title: Prosownica rozpierzchła (Milium effusum L.), 8535

description: Herbarium
DOI: 10.48370/ofd/4lr8jd/1htyey
title: HMW_Milium_effusum_L._H_9048.jpg

description: :unav
DOI: 10.48370/ofd/4lr8jd
title: Prosownica rozpierzchła (Milium effusum L.), 9048

description: Herbarium
DOI: 10.48370/ofd/r2mifj/zqnqln
title: HMW_Hepatica_nobilis_Schreb._H_6839.jpg

description: :unav
DOI: 10.48370/ofd/r2mifj
title: Przylaszczka pospolita (Hepatica nobilis Schreb.), 6839

description: Herbarium
DOI: 10.48370/ofd/xdcewf/rtq2bn
title: HMW_Hepatica_nobilis_Schreb._H_0892.jpg

description: :unav
DOI: 10.48370/ofd/xdcewf
title: Przylaszczka pospolita (Hepatica nobilis Schreb.), 892

description: Herbarium
DOI: 10.17036/researchdata.aston.ac.uk.00000507
title: Data underpinning 'Membrane protein extraction and purification using partially esterified SMA polymers'
DOI: 10.48370/ofd/nqoimm/trkbxx
title: HMW_Erigeron_ramosus_(Walters)_Britton,_Sterns_&_Poggenb._H_4910.jpg

description: :unav
DOI: 10.48370/ofd/nqoimm
title: Przymiotno gałęziste (Erigeron ramosus (Walters) Britton, Sterns Poggenb.), 4910

description: Herbarium
DOI: 10.48370/ofd/usgkuj/h65vpg
title: HMW_Erigeron_ramosus_(Walters)_Britton,_Sterns_&_Poggenb._H_7150.jpg

description: :unav
DOI: 10.48370/ofd/usgkuj
title: Przymiotno gałęziste (Erigeron ramosus (Walters) Britton, Sterns Poggenb.), 7150

description: Herbarium
DOI: 10.48370/ofd/riqcls/hlwrmx
title: HMW_Erigeron_ramosus_(Walters)_Britton,_Sterns_&_Poggenb._H_4815.jpg

description: :unav
DOI: 10.48370/ofd/riqcls
title: Przymiotno gałęziste (Erigeron ramosus (Walters) Britton, Sterns Poggenb.), 4815

description: Herbarium
DOI: 10.17894/ucph.04e91c97-5c5d-45d7-afd3-c5e0b5953f58
title: OpenJaw Dataset

description: This repository represents an open-access dataset including reconstructed geometries acquired from the cone-beam computed tomography (CBCT) of three patients' jaws for research purposes only. Each patient’s data includes surface meshes of the mandible, full mandibular dentition, and associated periodontal ligaments (PDLs) stored in the Stereolithography (STL) file format.
DOI: 10.5281/zenodo.5167258
title: VThunell/Warming_IGP_communities: Second release

description: Release for DOI
DOI: 10.5281/zenodo.5167233
title: Evaluation of restoration on post–mining areas using a game theory - data

description: Supplementary data to the article - numerical values from graphs (Fig 1-2, 5-12) + input data for calculations. The resulting NE probability values can be verified at equsis.com (outside of Fig 8, the limit is 32 cases).
DOI: 10.5281/zenodo.3484798
title: Evaluation of restoration on post–mining areas using a game theory - data

description: Supplementary data to the article - numerical values from graphs (Fig 1-2, 5-12) + input data for calculations. The resulting NE probability values can be verified at equsis.com (outside of Fig 8, the limit is 32 cases).
DOI: 10.48370/ofd/mzm9tb/1u6cpl
title: HMW_Erigeron_acris_L._H_0222.jpg

description: :unav
DOI: 10.48370/ofd/mzm9tb
title: Przymiotno ostre (Erigeron acris L.), 222

description: Herbarium
DOI: 10.48370/ofd/jlewib/jqzmgb
title: HMW_Erigeron_acris_L._H_0233.jpg

description: :unav
DOI: 10.48370/ofd/jlewib
title: Przymiotno ostre (Erigeron acris L.), 233

description: Herbarium
DOI: 10.48370/ofd/nbtsbv/qc21wb
title: HMW_Erigeron_acris_L._H_0236.jpg

description: :unav
DOI: 10.48370/ofd/nbtsbv
title: Przymiotno ostre (Erigeron acris L.), 236

description: Herbarium
DOI: 10.48370/ofd/0xs43a/zdiblp
title: HMW_Erigeron_acris_L._H_0038.jpg

description: :unav
DOI: 10.48370/ofd/0xs43a
title: Przymiotno ostre (Erigeron acris L.), 38

description: Herbarium
DOI: 10.48370/ofd/ka44zn/tkglhn
title: HMW_Erigeron_acris_L._H_5433.jpg

description: :unav
DOI: 10.48370/ofd/ka44zn
title: Przymiotno ostre (Erigeron acris L.), 5433

description: Herbarium
DOI: 10.48370/ofd/limjpe/2axozt
title: HMW_Erigeron_acris_L._H_8627`.jpg

description: :unav
DOI: 10.48370/ofd/limjpe
title: Przymiotno ostre (Erigeron acris L.), 8627

description: Herbarium
DOI: 10.5281/zenodo.5031335
title: A High-Resolution Spatial Room Impulse Response Database

description: <strong>A High-Resolution Spatial Room Impulse Response Database:</strong> A Database of various SRIRs measured in three rooms, for two receiver and 3 source positions each. The positions are shown in the floor plans. <strong>Naming Convention:</strong> <strong>Receivers</strong>: SMA (DRIRs): spherical microphone array impulse responses on a 2702 sampling point Lebedev grid. KU100 (BRIRs): Neumann KU100 dummy head impulse responses on a 360 sampling point horizontal grid Omni_ir: Omnidirectional impulse responses measured with an Earthworks M30 microphone <strong>Receiver positions:</strong> P1, P2 as indicated in the floor plans <strong>Source positions:</strong> LSL: left speaker, LSR: right speaker, LSC: center speaker as indicated in the floor plans <strong>Rooms: </strong>Audiolab, Classroom, Audimax _______________________________________________________________________________________ <strong>Contact:</strong><br> Tim Lübeck, Johannes M. Arend, and Christoph Pörschmann<br> TH Köln - University of Applied Sciences<br> Institute of Communications Engineering<br> Department of Acoustics and Audio Signal Processing<br> Betzdorfer Str. 2, D-50679 Cologne, Germany https://www.th-koeln.de/personen/tim.luebeck/ https://www.th-koeln.de/personen/johannes.arend/ https://www.th-koeln.de/personen/christoph.poerschmann/<br> <br>
description: {"references": ["L\u00fcbeck, T., Arend, J.M., and P\u00f6rschmann, C. (2021). \"A High-Resolution Spatial Room Impulse Response Database\", in Proceedings of the 47th DAGA, August 15-18, Vienna, Austria"]}
DOI: 10.5281/zenodo.5031334
title: A High-Resolution Spatial Room Impulse Response Database

description: <strong>A High-Resolution Spatial Room Impulse Response Database:</strong> A Database of various SRIRs measured in three rooms, for two receiver and 3 source positions each. The positions are shown in the floor plans. <strong>Naming Convention:</strong> <strong>Receivers</strong>: SMA (DRIRs): spherical microphone array impulse responses on a 2702 sampling point Lebedev grid. KU100 (BRIRs): Neumann KU100 dummy head impulse responses on a 360 sampling point horizontal grid Omni_ir: Omnidirectional impulse responses measured with an Earthworks M30 microphone <strong>Receiver positions:</strong> P1, P2 as indicated in the floor plans <strong>Source positions:</strong> LSL: left speaker, LSR: right speaker, LSC: center speaker as indicated in the floor plans <strong>Rooms: </strong>Audiolab, Classroom, Audimax _______________________________________________________________________________________ <strong>Contact:</strong><br> Tim Lübeck, Johannes M. Arend, and Christoph Pörschmann<br> TH Köln - University of Applied Sciences<br> Institute of Communications Engineering<br> Department of Acoustics and Audio Signal Processing<br> Betzdorfer Str. 2, D-50679 Cologne, Germany https://www.th-koeln.de/personen/tim.luebeck/ https://www.th-koeln.de/personen/johannes.arend/ https://www.th-koeln.de/personen/christoph.poerschmann/<br> <br>
description: {"references": ["L\u00fcbeck, T., Arend, J.M., and P\u00f6rschmann, C. (2021). \"A High-Resolution Spatial Room Impulse Response Database\", in Proceedings of the 47th DAGA, August 15-18, Vienna, Austria"]}
DOI: 10.6084/m9.figshare.12130980.v104
title: MOOD Maps of Google community mobility change during the COVID-19 outbreak

description: The MOOD project (MOnitoring Outbreak events for Disease surveillance in a data science context. H2020) has geo-referenced the data Google has published as a series of PDF files presenting reports on national and subnational human mobility levels relative to a baseline data of late January 2020. The details and the PDF files can be found at https://www.google.com/covid19/mobility/.<br>More detail on these files can be found at https://www.moodspatialdata.com/humanmobilityforcovid19 <br>The first set of data were released on April 2 2020 and have been revised weekly since then. The maps now utilise the CSV data released by Google. Please note that the maps figures use a mean of the previous three days, while the Google PDFs use a single days data so there will be differences between values in our maps when compare to the Google PDFs.<br>The authors have extracted the majority of these data into a series of excel spreadsheets. Each worksheet provides the data for % change in numbers of records at various types of location categories illustrated by: retail and recreation, grocery and pharmacy, parks and beaches, transit stations, workplaces and residential (columns f to K). A second set of columns calculates the difference of each value from the mean values for each category (columns L to P) Columns A to E contain geographical details. Column Q contains the names used to link to a mapping file.There are separate worksheets for the date of the data from each dated release (e.g. 2903, 0504 etc.) and separate worksheets calculating the changes between specific dates.<br>A second spreadsheet has been added calculating the 3 day moving mean of each day from the 15th of February. Each day is referenced by the Gregorian calendar day count. So day 48 = Feb 17th.<br>The maps (for EU & Global) display these data. We provide 600 dpi jpegs of the Global (“WD”) and European (“EU”) mapped values at the latest date available, for each of the mobility categories: retail and recreation (“retrec”) , grocery and pharmacy (“grocphar”) , parks (“parks”) , transit stations (“transit”), residential (“resid”) and workplaces (“work”). We also provide maps of the changes from the previous week (“ch”).<br>All data extracting and subsequent processing have been carried out by ERGO (Environmental Research Group Oxford, c/o Dept Zoology, University of Oxford) on behalf of the MOOD H2020 project. Data will be periodically updated. Additional maps can be obtained on request to the authors.
DOI: 10.6084/m9.figshare.15124755
title: Wind and wave datasets in the Gulf of Mexico (Version 1)

description: This dataset includes wind and wave datasets. Among them, the wind data comes from the ERA5 reanalysis wind dataset of the European Center for Medium-Term Weather Forecast (ECMWF; https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=form). The time range of wind data is from January 4, 2017, to December 31, 2017. After bilinear interpolation, the spatial resolution of wind data is increased from 0.25°×0.25° to 0.05°×0.05°. The wave dataset is a significant wave height dataset simulated by the SWAN model with wind data as input. The time range and resolution of the wave dataset are consistent with the processed wind dataset.<br>The dataset includes two folders, one is data1, the other is data2. The target sea area of data1 is 25.05°N94.65°W−27.00°N92.70°W, which contains the files of wind U and V component matrix (data_u10.csv, data_v10.csv) and the file of significant wave height (data_swh.csv). Matrix elements correspond to spatial locations. Their spatial resolution is 0.05 ° × 0.05 °. The target sea area of data2 is 24.05°N95.65°W−28.00°N91.70°W, which contains the files of wind field U and V component matrix (data_u10.csv, data_v10.csv) and the file of significant wave height (data_swh_41x41.csv, data_swh_81x81.csv). Matrix elements correspond to spatial locations. The spatial resolutions of data_u10.csv, data_v10.csv, and data_swh_81x81.csv are all 0.05° × 0.05°. The spatial resolution of data_swh_41x41.csv is 0.1° × 0.1°.<br>
DOI: 10.6084/m9.figshare.15124647.v1
title: Puy_JEcology_2021.xlsx

description: Experimental data
DOI: 10.6084/m9.figshare.14643388.v1
title: Direct synthesis of sulfinic esters via ultrasound accelerated tandem reaction of thiols and alcohols with <i>N</i>-bromosuccinimide

description: The direct transformation of various thiols and simple alcohols with N-bromosuccinimide into sulfinic esters has been investigated by using different categories of base/acidic catalysts as well as co-solvents under varied reaction conditions. The reaction was found out to afford the sulfinic esters with high yields in the absence of catalysts, especially within the shorter time under the acceleration of ultrasonic irradiation than under the longer-lasting conventional stirring conditions.
DOI: 10.34740/kaggle/dsv/2503987
title: COVID Vaccination in World (updated daily)
DOI: 10.6084/m9.figshare.14776272.v1
title: Co-cultivation of selected combinations of HOB and MOB

description: The eight best combinations were selected based on the plating of the combinations of the 9 MOB with the 19 HOB. Additionally,<i> X. autotrophicus</i> and <i>C. necator</i> were combined with the best growing MOB, <i>Methyloparacoccus murrelli </i>LMG 27482, as established by the results of plating and flow cytometry measurements. <i>C. necator</i> is one of the most well-described species for hydrogen-driven MP production (Yu, 2018), whereas we recently identified <i>X. autotrophicus </i>as a autotrophic, nitrogen fixing HOB (Hu et al., 2020). As before, the MOB and HOB pure cultures were diluted in DSMZ medium 81 containing trace elements, at a final cell density of 10<sup>6</sup> cells/mL, before being subjected to triplicate incubations
DOI: 10.6084/m9.figshare.14776263.v1
title: Preliminary screening of HOB and MOB co-cultivations

description: This is the preliminary screening for Kerckhof, Sakarika <i>et al</i> 2021 - the project where this dataset belongs to and the accompanying paper. In this set 9 MOB and the 19 HOB obtained from an isolation campaign were combined (1 MOB with 1 HOB) and grown in liquid medium in order to obtain the best performing combinations. The experiments were performed in 96-well plates, at a final working volume of 0.2 mL. The MOB and HOB pure cultures were diluted in DSMZ medium 81 containing trace elements, at a final cell density of 10<sup>6 </sup>cells/mL. Next a volume of 0.2 mL was transferred in the respective well for the growth of the individual strains, while for the combinations of one HOB and one MOB, a volume of 0.1 mL and from each strain was used (i.e. to achieve a final volume of 0.2 mL). Each combination was tested in duplicate
DOI: 10.5519/qd.neszic5m
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (132 records)
DOI: 10.5517/ccdc.csd.cc214nnj
title: CCDC 1881317: Experimental Crystal Structure Determination

description: Related Article: Jianling Ni|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc27619t
title: CCDC 2061385: Experimental Crystal Structure Determination

description: Related Article: Zhenqiang Xia, Ridong Huang, Xinglong Zhou, Yingying Chai, Hai Chen, Lingling Ma, Quanwei Yu, Ying Li, Weimin Li, Yang He|2021|Eur.J.Med.Chem.|224|113711|doi:10.1016/j.ejmech.2021.113711
description: Related Article: zhenqiang xia|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2764tf
title: CCDC 2061494: Experimental Crystal Structure Determination

description: Related Article: Si-Yu Xu, Rui Zhang, ShuSheng Zhang, Chen-Guo Feng|2021|CSD Communication|||
description: Related Article: Si-Yu Xu,   Rui Zhang,   ShuSheng Zhang  and  Chen-Guo Feng  |2021|Org.Biomol.Chem.|19|4492|doi:10.1039/D1OB00487E
DOI: 10.5517/ccdc.csd.cc27mlwc
title: CCDC 2074423: Experimental Crystal Structure Determination

description: Related Article: Bo Zhu, Tianxiao Yang, Yingxin Gu, Shuping Zhu, Gongming Zhu, Junbiao Chang|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc27n3cd
title: CCDC 2074903: Experimental Crystal Structure Determination

description: Related Article: Natal'ya Davletshina, Albina Khabibullina, Rustam Davletshin, Kamil Ivshin, Olga Kataeva, Rafael Cherkasov|2021|J.Organomet.Chem.|951|121996|doi:10.1016/j.jorganchem.2021.121996
DOI: 10.5517/ccdc.csd.cc27qtc5
title: CCDC 2077507: Experimental Crystal Structure Determination

description: Related Article: Suman Mandal, Suman Mallick, Purnananda Garu, Jagannath Chowdhury, Saikat Banerjee, Samya Sen, Keka Sarkar, Swarup Chattopadhyay|2021|Polyhedron|207|115373|doi:10.1016/j.poly.2021.115373
DOI: 10.5517/ccdc.csd.cc27qtd6
title: CCDC 2077508: Experimental Crystal Structure Determination

description: Related Article: Suman Mandal, Suman Mallick, Purnananda Garu, Jagannath Chowdhury, Saikat Banerjee, Samya Sen, Keka Sarkar, Swarup Chattopadhyay|2021|Polyhedron|207|115373|doi:10.1016/j.poly.2021.115373
DOI: 10.5517/ccdc.csd.cc22yg7r
title: CCDC 1934934: Experimental Crystal Structure Determination

description: Related Article: Shoukun Zhang|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc27st51
title: CCDC 2079423: Experimental Crystal Structure Determination

description: Related Article: María Galiana-Cameo, Vincenzo Passarelli, Jesús J. Pérez-Torrente, Andrea Di Giuseppe, Ricardo Castarlenas|2021|Eur.J.Inorg.Chem.|2021|2947|doi:10.1002/ejic.202100399
DOI: 10.5517/ccdc.csd.cc27st62
title: CCDC 2079424: Experimental Crystal Structure Determination

description: Related Article: María Galiana-Cameo, Vincenzo Passarelli, Jesús J. Pérez-Torrente, Andrea Di Giuseppe, Ricardo Castarlenas|2021|Eur.J.Inorg.Chem.|2021|2947|doi:10.1002/ejic.202100399
DOI: 10.6084/m9.figshare.15123879
title: Dataset_university1.xlsx

description: The dataset store the data from the interview in a university library. This library has has 24.354 book titles with 71.368 copies. The total staff who work in this library are 28 consist of 12 librarians and 14 administration staff. The transaction total in this library every day about 160 transactions. This dataset documented from the interview is written in English. All the response of the interview show in each row per questions. The interview is about all processes that occur in the this library. There are 16 questions with 110 sentences as responses store in this dataset. The dataset contains 1247 words with 196 sequence words.
DOI: 10.15161/oar.it/74008
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.23729/482b4145-e450-46f4-9f1d-f6ae02453ab0
title: Crushed Ore

description: Crushed talc (T) and skarn (TS) ore samples used for textural quantification in: Guntoro, P.I., Ghorbani, Y., Parian, M., Butcher, A.R., Kuva, J., Rosenkranz, J., 2021. Development and experimental validation of a texture-based 3D liberation model. Minerals Engineering 164. Preview dataset found at https://doi.org/10.23729/d74f92f8-90aa-4b85-97b5-534d13c9f0a7 . To obtain data, please contact fairdata-pas@gtk.fi .