cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.24416/uu01-dv3yza
title: Pieta van Beek, Schurmanniana Series I-V

description: Bundel van vijf studies over Anna Maria van Schurman (1607-1678) door Pieta van Beek, de gehele Schurmanniana-reeks 1-5, vertaald in het Engels: ‘About God’ (I), ‘Your charming and well-written letter’ (II), ‘Devoured by his love’ (III), ‘Risen from the ashes' (IV) en ‘Ex libris’ (V), voorafgegaan door een Voorwoord (Preface). Dit is de Engelse vertaling van de data package 'Schurmanniana-reeks 1-5', gepubliceerd in 2023. Collection of five studies about Anna Maria van Schurman (1607-1678) by Pieta van Beek, the complete Schurmanniana Series 1-5, translated into English: 'About God’ (I), ‘Your charming and well-written letter’ (II), ‘Devoured by his love’ (III), ‘Risen from the ashes' (IV) en ‘Ex libris’ (V), introduced by a Preface. This is an English translation of the data package 'Schurmanniana-reeks 1-5', published in 2023.
DOI: 10.17028/rd.lboro.31305274
title: Supplementary information files for "Extraction ecologies in medieval Venice: nature, speculation, painting, and the gesture"

description: Supplementary files for article "Extraction ecologies in medieval Venice: nature, speculation, painting, and the gesture"<br><br>This paper looks at the specific political economic conditions of 16th century Venice and seeks to connect these with the introduction of the gesture in painting. Arguing that the production of “nature” and its exploitation via increased accumulation, and management of resources are enacted in Titan and Tintoretto’s painting via the expanded and abstracted gesture. I outline the development of financial and quantification techniques in Venice and Italy during the 15th century and ask if these were echoed in painting, that draws from nature while codifying it. Arguing that by looking at paintings made during the emergence of capitalism we can better understand the interaction of the economic and the ideological and locate painting as one such technique. By identifying the gesture in painting as speculative, we can read it through systems of fictitious capital that seek to capture future labour and nature, which underlines the role of credit for emergent capitalism. Arguing against previous conceptualising of the gesture as labour-time, to suggest instead it mimics the abstraction of future labour time in finance capitalism. I portend that by understanding more about ecological thinking in the emergence of capitalism we can better frame our ongoing metabolic rift.<br><br>CC BY-NC-ND, © The Author(s)
DOI: 10.17028/rd.lboro.31305274.v1
title: Supplementary information files for "Extraction ecologies in medieval Venice: nature, speculation, painting, and the gesture"

description: Supplementary files for article "Extraction ecologies in medieval Venice: nature, speculation, painting, and the gesture"<br><br>This paper looks at the specific political economic conditions of 16th century Venice and seeks to connect these with the introduction of the gesture in painting. Arguing that the production of “nature” and its exploitation via increased accumulation, and management of resources are enacted in Titan and Tintoretto’s painting via the expanded and abstracted gesture. I outline the development of financial and quantification techniques in Venice and Italy during the 15th century and ask if these were echoed in painting, that draws from nature while codifying it. Arguing that by looking at paintings made during the emergence of capitalism we can better understand the interaction of the economic and the ideological and locate painting as one such technique. By identifying the gesture in painting as speculative, we can read it through systems of fictitious capital that seek to capture future labour and nature, which underlines the role of credit for emergent capitalism. Arguing against previous conceptualising of the gesture as labour-time, to suggest instead it mimics the abstraction of future labour time in finance capitalism. I portend that by understanding more about ecological thinking in the emergence of capitalism we can better frame our ongoing metabolic rift.<br><br>CC BY-NC-ND, © The Author(s)
DOI: 10.5281/zenodo.18595516
title: A dataset of formal proofs in lean from the 1000 theorems project, for integration into the MaRDI knowledge graph.

description: The dataset was created by the following python code in the context of https://github.com/MaRDI4NFDI/MaRDIRoadmap/issues/65:

 



import yamlimport pandas as pd#obtained from https://github.com/leanprover-community/mathlib4/blob/master/docs/1000.yamlwith open("~/1000.yaml",encoding='utf-8') as stream:    theorems_dict = yaml.safe_load(stream)theorems_project_df = pd.DataFrame(theorems_dict).transpose()theorems_project_df.index.name = 'wikidata_qid'sparql_query = 'https://w.wiki/HcXE'#theorems from wikidata with english-language wikipedia article. obtained from wikidata via query https://w.wiki/HcXEnamed_theorems_json = '~/Downloads/named_theorems.json'with open(named_theorems_json, encoding='utf-8') as named_theorems_fh:    named_theorems = json.load(named_theorems_fh)theorems_df = pd.read_json(named_theorems_json)theorems_df['wikidata_qid'] = theorems_df.cid.apply(lambda x:x.split('/')[-1])theorems_df = theorems_df.join(theorems_project_df,how='outer',on='wikidata_qid')theorems_df['P31'] = 'Q6480412'theorems_df['P37']='Q6480413'theorems_df['P1603']=theorems_df.apply(lambda x:x['decl'] if x['decl'] else x['url'],axis=1)theorems_df['P1460'] = 'Q6534201'theorems_df['P12'] = theorems_df['wikidata_qid']theorems_df = theorems_df.rename({'date':'P140','comment':'Den','title':'Len'})theorems_df['P205'] = theorems_df.apply(lambda x:"https://leanprover-community.github.io/1000.html#"+x['P12'] if x['decl'] or x['url'] else '')theorems_df['P1648'] = 'Q27041'formal_proofs_df = theorems_df.drop(columns=['P1460','P37','P31','P1603','cid','label','article','decl','authors','url','statement'])formal_proofs_df = formal_proofs_df.dropna(columns=['P205'])formal_proofs_df.fillna('').to_csv('~/formal_proofs_mardi.csv',index=False)
DOI: 10.5281/zenodo.18391897
title: A dataset of formal proofs in lean from the 1000 theorems project, for integration into the MaRDI knowledge graph.

description: The dataset was created by the following python code in the context of https://github.com/MaRDI4NFDI/MaRDIRoadmap/issues/65:

 



import yamlimport pandas as pd#obtained from https://github.com/leanprover-community/mathlib4/blob/master/docs/1000.yamlwith open("~/1000.yaml",encoding='utf-8') as stream:    theorems_dict = yaml.safe_load(stream)theorems_project_df = pd.DataFrame(theorems_dict).transpose()theorems_project_df.index.name = 'wikidata_qid'sparql_query = 'https://w.wiki/HcXE'#theorems from wikidata with english-language wikipedia article. obtained from wikidata via query https://w.wiki/HcXEnamed_theorems_json = '~/Downloads/named_theorems.json'with open(named_theorems_json, encoding='utf-8') as named_theorems_fh:    named_theorems = json.load(named_theorems_fh)theorems_df = pd.read_json(named_theorems_json)theorems_df['wikidata_qid'] = theorems_df.cid.apply(lambda x:x.split('/')[-1])theorems_df = theorems_df.join(theorems_project_df,how='outer',on='wikidata_qid')theorems_df['P31'] = 'Q6480412'theorems_df['P37']='Q6480413'theorems_df['P1603']=theorems_df.apply(lambda x:x['decl'] if x['decl'] else x['url'],axis=1)theorems_df['P1460'] = 'Q6534201'theorems_df['P12'] = theorems_df['wikidata_qid']theorems_df = theorems_df.rename({'date':'P140','comment':'Den','title':'Len'})theorems_df['P205'] = theorems_df.apply(lambda x:"https://leanprover-community.github.io/1000.html#"+x['P12'] if x['decl'] or x['url'] else '')theorems_df['P1648'] = 'Q27041'formal_proofs_df = theorems_df.drop(columns=['P1460','P37','P31','P1603','cid','label','article','decl','authors','url','statement'])formal_proofs_df = formal_proofs_df.dropna(columns=['P205'])formal_proofs_df.fillna('').to_csv('~/formal_proofs_mardi.csv',index=False)
DOI: 10.57906/vbf5-m179
title: Annual Survey of Hours and Earnings linked to Migrant Worker Scan - GB
DOI: 10.24416/uu01-13tl1v
title: Visualizing Biofilms within opaque materials in 3D Using Micro-Computed Tomography

description: This dataset provides all the micro-computed tomography (µCT) data used for the manuscript Schröer et al. 2025. It evaluates the effect of isotonic Lugol and Hf-WD 1:2 POM to stain biofilms and make them visible using µCT. Each folder contains a stack of .tiff files achieved after reconstructing a µCT scan. The .tiff files represent a 3D volume of sand filters colonized with biofilms. The samples of 1. Isotonic Lugol (IL1 - IL3) originated from slow sand filter 5B of Monster production site, Dunea Water Company (the Netherlands), while the samples of Hf-WD 1:2 POM (Hf1 - Hf3) originated from slow sand filter 2 at the Groningen Water Company (the Netherlands). All samples were scanned six times: 1. (IL_Blank/Hf_Blank) in PBS, before staining at Day1; 2. (IL_CESA/Hf_CESA) around 18-21 hours after staining with Isotonic Lugol/Hf-WD 1:2 POM at Day 2; (3) IL_CESA+1d/Hf_CESA+1d after around an extra 24 hours at Day 3; 4. IL_Wash/Hf_Wash: Immediately after washing with PBS at Day 4; 5. IL_Wash+1d/Hf_Wash+1d: Around 24 hours after washing (Day 5); 6. IL_BaSO4/HF_BaSO4: Immediately after introducing a BaSO4 suspension (Day 5).

The data is provided in 2 subfolders. Detailed information about the files in these subfolders is given in the explanatory file ReadMe_3dbiofilm.txt. Contact person is Laurenz Schröer - laurenz.schroer@ugent.be
DOI: 10.24416/uu01-9hagpf
title: Negative cognitions and emotional distress following job loss: Development and validation of the Beliefs about Loss Of Work (BLOW) scale

description: Negative cognitions following job loss can contribute to emotional distress by motivating individuals to adopt coping styles that reduce stress in the short run, while obstructing adjustment in the long run. It is unclear which specific cognitions are related to symptoms of complicated grief, depression, and anxiety following job loss. To fill this gap, this study introduces the Beliefs about Loss Of Work (BLOW) scale and examines its psychometric properties. We recruited 222 Dutch workers who had lost their job, including 70 men and 152 women, with an average age of 52.5 years. Confirmatory factor analyses revealed that a second-order eight-factor model had the best fit to the data. The BLOW is a reliable instrument with a good convergent and divergent validity. This instrument may stimulate research on mechanisms involved in job loss-related distress and could help in creating clinical interventions to reduce emotional problems after job loss.  

The first author (JE) was responsible for the data collection.
DOI: 10.24416/uu01-rifw3x
title: Visualizing Cyanobacterial Biofilms in 3D Using Micro-Computed Tomography

description: This data package contains all the reconstructed µCT scans that were analyzed and displayed in the publication from Schröer et al. titled 3D Visualization of Cyanobacterial Biofilms using Micro-Computed Tomography with Contrast-Enhancing Staining Agents. The goal of this research and this data was to visualize cyanobacterial biofilms using micro-computed tomography using five different contras-enhancing staining agents (CESAs)
Every folder contains a series of .tiff files making up a 3D volume and a text file that describes either the scanning or reconstruction parameters. The µCT scans show six samples of biofilms of Phormidium autumnale ULC086 colonizing Bentheim sandstone. The biofilms were stained with (1) Isotonic Lugol, (2) Hexabrix, (3) Mono-WD POM, (4) Hf-WD 1:2 POM, (5) CA4+ or remained (6) blank as control.

The data is provided in six subfolders. Detailed information about the files in these subfolders is given in the explanatory file ReadMe_3dcyano.txt. Contact person is Laurenz Schröer - laurenz.schroer@ugent.be
DOI: 10.24416/uu01-w772vi
title: Grief, depression, and anxiety following job loss: Patterns and correlates

description: Abstract
Background. Research on grief, depression, and anxiety reactions following job loss is sparse. More insight in this matter could be important for the development of preventive and curative methods addressing the perceived emotional distress following job loss, especially in the case of job loss-related grief reactions.
Objective. The aim of this study was to examine job loss-related grief reactions in relation to depression and anxiety symptoms.
Method. A sample of 525 Dutch workers (59.8% women, mean age of 50.6 years) who had lost their job was recruited. A latent class analysis was used to examine whether separate classes for these three concepts could be distinguished, and which factors were associated with class membership.
Results. Latent class analysis revealed four distinct classes, that is, a so-called “mixed”, a “grieving”, a “depressed”, and a “resilient” class. Job loss circumstances and coping strategies (but not socio-demographic and work characteristics) were associated with class membership.
Conclusion. These results shed light on unique characteristics that might be targeted with specific clinical methods to increase mental health of different subgroups of individuals confronted with job loss.

The first author (JE) was responsible for the data collection.
DOI: 10.21227/9n4y-5d43
title: "A Generalized Framework for Optimization -datasets"

description: "Primariliy for the Paper submission done in IEEE Transactions on Reliability."
DOI: 10.24416/uu01-do6lt4
title: True 2D-to-3D Reconstruction of Heterogenous Porous Media via Deep Generative Adversarial Networks (GANs)

description: [The latest version of this dataset is accessible via the following DOI:
https://doi.org/10.24416/UU01-AFP38O]

We imaged samples of Berea sandstone from Ohio (USA) using two 2D imaging techniques: backscattered electron (BSE) and optical microscopy, and 3D X-ray (micro-)computed tomography (XCT). The goal is to employ a deep-learning-based generative model called a generative adversarial network (GAN) to reconstruct statistically equivalent microstructures in 3D from exclusively 2D training images. To evaluate the reconstruction accuracy, we conduct a visual and statistical analysis comparing reconstructions with a 3D X-ray tomography of the same sample. Unlike previous research, our method uses true 2D images from three orthogonally oriented planes for training the model. The data are organized into 10 folders: three contain the original segmented (binary) images of Berea sandstone samples, and the other 7 folders contain data and individual figures used to create figures in the main publication.

Link to GitHub containing codes:  
https://github.com/hamediut/2D-to3D-recon
DOI: 10.24416/uu01-0eiazx
title: Videos used in the Enthymeme-CT study

description: Can Video Lectures on Enthemymes Improve Adult Learner’s Critical Thinking and Clickbait Detection Skills?
This intervention had three conditions: a video lecture on enthymeme, a video lecture on critical thinking, and a control condition that entailed listening to the story of “Frog and Toad” by American children’s author, Arnold Lobel. All three conditions were video recorded in May 2022 with a Nikon camera and later edited in Adobe Premiere. The same native English speaker—a professor of rhetoric—delivered all three talks, with the same background (a bookshelf), and wearing the same light blue shirt. Videos were edited into three shorter video clips, balancing the length, and are available here. The participants could not move to the next section before playing the videos until the end.
DOI: 10.24416/uu01-w9rs5v
title: Dutch Tweets Before, During, and After a Black Lives Matter Demonstration in Amsterdam: Expert Annotated Data, Protocol, and Labelling Tool

description: The Dutch police are looking for measures to examine sentiment on social media related to protest demonstrations. While there exist models to detect more subtle expressions of sentiment within tweets, models trained in the Dutch language are scarce. Being able to predict sentiment development during protests is relevant for parties like the Dutch government and the police to get more insight as to when and where potential law enforcement is needed for public order and safety. Therefore, to analyze sentiment before, during, and after protest demonstrations, data was collected with tweets related to a Black Lives Matter protest that took place in Amsterdam during the COVID-19 pandemic. All tweets have been manually labelled by a dedicated open-source intelligence (OSINT) team within the Dutch police following an established protocol. Both the data and the protocol are available, and interesting for researchers in natural language processing, topic detection, sentiment analysis, and protests analysis. The developed labelling tool for the labelling process is publicly available.
DOI: 10.24416/uu01-2l689l
title: New 2D-to-3D Reconstruction of Heterogenous Porous Media via Deep Generative Adversarial Networks (GANs)

description: We imaged samples of Berea sandstone from Ohio (USA) using two 2D imaging techniques, backscattered electron (BSE) and optical microscopy, as well as one 3D imaging technique, X-ray (micro-)computed tomography (XCT). The goal is to employ a deep-learning-based generative model called a generative adversarial network (GAN) to reconstruct statistically equivalent microstructures in 3D from exclusively 2D training images. To evaluate the reconstruction accuracy, we conduct a visual and statistical analysis comparing reconstructions with a 3D X-ray tomography of the same sample. Our method uniquely uses true 2D images from three orthogonally oriented planes for training the model. The data are organized into 13 folders: three contain the original segmented (binary) images of Berea sandstone samples, and the other 10 folders contain data and individual figures used to create figures in the main publication.

Link to GitHub containing codes:  https://github.com/hamediut/2D-to3D-recon
DOI: 10.24416/uu01-afp38o
title: New 2D-to-3D Reconstruction of Heterogenous Porous Media via Deep Generative Adversarial Networks (GANs)

description: We imaged samples of Berea sandstone from Ohio (USA) using two 2D imaging techniques, backscattered electron (BSE) and optical microscopy, as well as one 3D imaging technique, X-ray (micro-)computed tomography (XCT). The goal is to employ a deep-learning-based generative model called a generative adversarial network (GAN) to reconstruct statistically equivalent microstructures in 3D from exclusively 2D training images. To evaluate the reconstruction accuracy, we conduct a visual and statistical analysis comparing reconstructions with a 3D X-ray tomography of the same sample. Our method uniquely uses true 2D images from three orthogonally oriented planes for training the model. The data are organized into 13 folders: three contain the original segmented (binary) images of Berea sandstone samples, and the other 10 folders contain data and individual figures used to create figures in the main publication.

Link to GitHub containing codes:  https://github.com/hamediut/2D-to3D-recon
DOI: 10.24416/uu01-er5krc
title: CT-optimal tactile imagery - data and analyses files

description: This dataset contains all data required to replicate the results presented in the manuscript 'The Power of Tactile Imagery: parallels between imagined and physical CT-optimal touch' authored by dr. Renee Lustenhouwer and dr. Larissa L. Meijer. 

All data processing was carried out in Python v 3.13. Required python packages are listed at the top of the python script. We employed pleasantness data (numeric rating scale from 0-100) and imagery duration data (in milliseconds) for this study. The data is provided in the data subfolder. Analysis files are in the main directory. Raw data (in data folder) have been processed using the python script. The variables used for subsequent statistical analyses have been entered into the SPSS database file. Statistical analyses were ran using the SPSS Syntax file.

Contact person is dr. Renee Lustenhouwer - assistant professor - r.lustenhouwer@uu.nl
DOI: 10.24416/uu01-u581cn
title: Model-driven sustainability accounting dissertation data

description: As part of the dissertation titled: “Model-driven sustainability accounting”, we have collected empirical data to answer the research question “How can model-driven engineering aid organisations account for their environmental, social and governance impact?”. To answer this research question we have created a model-driven open-source tool called openESEA. To develop the tool we have collected data on environmental, social and governance accounting (ESGA) methods, and conducted a survey. To validate the tool we have conducted interviews, and run user tests and case studies.  This folder contains the data gathered during the dissertation
DOI: 10.24416/uu01-kz91om
title: CT-optimal touch and chronic pain experience in Parkinson’s Disease; An intervention study 

description: Raw data files, SPPS data + output files and Read me file
DOI: 10.24416/uu01-a9jxh1
title: 2PIC CESM data for Baatsen et al. 2020

description: Averages and climatologies of primary atmosphere and ocean data from the CESM1.0.5 simulation with 38Ma paleomag reconstruction and 2xPIC (pre-industrial carbon; 560ppm CO2 / 1342ppb CH4)

This datapackage belongs to the Baatsen et al 2020 paper. There are two more datapackages:

- Pre Industrial CESM data for Baatsen et al. 2020
- 4PIC CESM data for Baatsen et al. 2020

that also belong to this paper. In fact there are three DOI's belonging to the paper which is a bit unhandy so we later created a new datapackage containing the same CESM data of all three simulations. This way we can refer to the paper with only one DOI, this new datapackage has DOI: 10.24416/UU01-KCSGFG
DOI: 10.24416/uu01-vbtkq0
title: PCR-GLOBWB community reference output - 4dHydro working package 2

description: 4dHydro working package 2 is dedicated to provided a set of land-surface and hydrological model community reference outputs. The community reference outputs are a set of hydrological simulation outputs from various land-surface and hydrological models from previous studies. Therefore, these outputs represent the current state-of-the-art in hydrological modeling (i.e. before the improvements made in this project) and are used as a baseline reference for the rest of the project. This datapackage contains the outputs for the PCR-GLOBWB hydrological model (globalhydrology.nl/research/models/pcr-globwb-2-0), which was developed at Utrecht University. See https://4dhydro.eu/catalog/ for links to outputs from other models. Outputs are formatted according to the 4dHydro working package 2 storage protocol. For more information, please contact Bram Droppers (b.droppers@uu.nl) or Niko Wanders (n.wanders@uu.nl).
DOI: 10.24416/uu01-ckb0mj
title: Responsive evaluation of "Pressure or Pleasure": a worksite mental health promotion intervention targeting younger employees 

description: Interviews; surveys; field notes
DOI: 10.24416/uu01-8qfvk8
title: PCR-GLOBWB experiment 1-0 output - 4dHydro working package 5 [UPDATED]

description: 4dHydro working package 5 is dedicated to provided a set of land-surface and hydrological model community outputs for several calibration/assimilation experiments. These experiments include simulations over different resolutions and calibration/assimilation with earth-observed (EO) satellite products. The aim of these experiments is to investigate the added value of EO products for hydrological simulations. This data package contains the outputs for the PCR-GLOBWB hydrological model (globalhydrology.nl/research/models/pcr-globwb-2-0), which was developed at Utrecht University. See https://opensciencedata.4dhydro.eu/ for links to outputs from other models. Outputs are formatted according to the 4dHydro working package 5 storage protocol. For more information, please contact Bram Droppers (b.droppers@uu.nl) or Niko Wanders (n.wanders@uu.nl).

A new version of this dataset was published and is available via; https://public.yoda.uu.nl/geo/UU01/8BVQCA.html