cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15482/usda.adc/30161443.v1
title: Data from: Grazing and Cover Crop Effects on Soil Health During Transition to Organic Production

description: Incorporation of grazed cover crops in cropping systems can improve soil. However, information concerning how cover crops and livestock grazing interact during transitions to organic crop production is limited. An experiment was conducted to quantify soil responses to cover crops and grazing during a transition to organic crop production on a Tally sandy loam near Mandan, ND USA. Main-plot factors included grazing vs. no grazing, while split plot factors included six cropping treatments (soil-building cover crop mix, pollinator cover crop mix, weed suppression cover crop mix, multipurpose cover crop mix, annual crop rotation, and perennial forage biculture). Treatments were replicated four times. Soil samples were collected from 0-10 and 10-30 cm depths at the beginning and end of a 3-year organic transition period. Soil samples were evaluated for soil bulk density, soil pH, nitrate-N, available phosphorus, potassium, total soil nitrogen, soil organic carbon, and wet aggregate stability. Soil pH was estimated from a 1:1 soil-water mixture. Soil nitrate-N was determined from 1:10 soil-KCl (2 M) extracts using cadmium reduction followed by a modified Griess-Ilosvay method. Plant-available soil P was estimated by bicarbonate extraction. Exchangeable K was estimated by atomic absorption spectrometry. Total soil carbon and nitrogen were determined by dry combustion. Wet aggregate stability was analyzed for the 0-10 cm soil depth using the 1-2 mm aggregate fraction. Values for soil properties were incorporated into a soil quality index using the Soil Management Assessment Framework. Data may be used to understand soil responses to grazed and ungrazed cover crops under rainfed conditions in a semiarid continental climate. Related USDA soil types include Baggs, Baxton, Belain, Bitterroot, Chincap, Hopley, Mott, Panguitch, Relan, Vebar, and Victor.
DOI: 10.3535/k5c-dp8-lpc
title: Argynnis paphia (Linnaeus, 1758)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/nx6-z53-15r
title: Autographa Hübner, 1821

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/0k6-s3k-p50
title: Argynnis paphia (Linnaeus, 1758)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/dsz-zf4-cp7
title: Zophodia convolutella Hübner, 1796

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.17632/25r6txd45n.6
title: Provenance Modelling of Fossil Dinosaur Bones Using Geochemistry and Machine Learning: Source Data

description: The data presented here support the research paper “Provenance Modelling of Fossil Dinosaur Bones Using Geochemistry and Machine Learning”, intended for a submission to "Palaeoworld".

The dataset contains trace elements concentrations from fossil dinosaur bones from the Upper Cretaceous Nemegt and Djadokhta formations. 
For the analytical purposes, the dataset was divided into two subsets: the first one consisting of long bones (tibiae, femora, radii and humeri) and the other including trabecular bones (ribs and vertebrae) and metatarsals. Locality labels were used to train and evaluate several machine learning classifiers (logistic regression, random forest, AdaBoost, XGBoost) to assess the potential of bone geochemistry for provenance prediction. Feature selection was conducted on the best-performing models to identify the elements contributing the most to the model performance. These results were compared with those obtained using Linear Discriminant Analysis. 

The data are provided in CSV format in the “Data” folder. The folder “Plots and figures” contains the figures used in the manuscript, including the plots. The folder “Supplementary files” contains additional files. These files are:
- interactive HTML plot ("Element profiles.html") showing the all the concentration profiles across each analysed sample, including the ones measured along several profiles
- concentration profiles presented in a PDF file ("All profiles.pdf")
- XLSX file with the statistical summary of the data ("Data description WK.xlsx")
- LDA scalings in CSV file ("LDA scalings.csv")
- The tables comparing predictions and performance of the algorithms using test part of each subset ("Predictions and accuracy.xlsx")
Besides that, the Jupyter Notebook with data analysis is also provided ("Bones from Gobi - loc prediction.ipynb").
DOI: 10.3535/7x8-tmr-kj9
title: Sideridis (Heliophobus) reticulata Goeze, 1781

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/56d-xey-4dc
title: Xestia (Megasema) ashworthii Doubleday, 1855

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/zha-fps-7j2
title: Xestia (Megasema) ashworthii Doubleday, 1855

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15483/3006213
title: Baseline vs. DER Scenario

description: Projections and associated uncertainty estimates are generated for a variety of user-selectable EV charging sessions, electricity tariffs, subsidy levels, revenue schemes, charging station configurations, and on-site solar and/or storage options. The outputs are presented in CHIP's web portal browser in the form of easily interpretable graphics (interactive graphs and bar charts) that facilitate convenient comparison among different scenarios to aid decision-making. The user should bring assumptions for modeling on simulation planning horizon, number of EV charging sessions per year, electricity costs (energy and demand charge rates; flat versus time-of-use rate), site capital costs (equipment for EV chargers and transformer), solar PV, and battery energy storage (kW).
DOI: 10.3535/n08-91n-29b
title: Hydraecia micacea Esper, 1789

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/w5r-brv-ec9
title: Agriphila tristellus [Denis & Schiffermüller], 1775

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/1nw-7e4-mpv
title: Sphrageidus similis (Fuessly, 1775)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/vl3-zam-4na
title: Agriphila tristellus [Denis & Schiffermüller], 1775

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/7je-2hd-n7l
title: Athetis (Hydrillula) Tams, 1938

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/8hz-78a-d0k
title: Autographa Hübner, 1821

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/a5c-ype-r2s
title: Callophrys rubi (Linnaeus, 1758)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/pc0-9ef-f8b
title: Lasionycta Aurivillius, 1892

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/rw9-9a8-n0z
title: Lycaena Fabricius, 1807

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/zsy-dqk-hq4
title: Scopariinae

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/scd-gek-hzz
title: Zophodia convolutella Hübner, 1796

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/vdy-pmk-pz4
title: Diarsia dahlii Hübner, 1813

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/1ym-5yv-yac
title: Sideridis (Heliophobus) reticulata Goeze, 1781

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/2kn-ksn-34q
title: Gonepteryx rhamni (Linnaeus, 1758)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/vmr-qrk-mg1
title: Cyaniris semiargus (von Rottemburg, 1775)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.17632/nd7tjv2rc3
title: OARL-ABC

description: Online Adaptive Reinforcement Learning and Approximate Bayesian Computation (OARL-ABC) for Real-Time Long-Term Calibration of Rotordynamic Models: Supplementary experimental results and data
DOI: 10.3535/5ad-wat-hs3
title: Anarta (Calocestra) melanopa Thunberg, 1791

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/jfn-b9p-j3c
title: Acronicta (Subacronicta) megacephala ([Denis & Schiffermüller], 1775)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.17632/nd7tjv2rc3.1
title: OARL-ABC

description: Online Adaptive Reinforcement Learning and Approximate Bayesian Computation (OARL-ABC) for Real-Time Long-Term Calibration of Rotordynamic Models: Supplementary experimental results and data
DOI: 10.3535/7nl-43z-ztv
title: Diarsia dahlii Hübner, 1813

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/sz9-4cm-h22
title: Chilo phragmitella Hübner, 1805

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.17632/2hs2mwy6fx
title: Vandenbergetal2025_RawData

description: Source data files for vandenberg et al 2025 "Efficacy of Clearflow treatment technologies in the treatment of mining effluent: Field-level testing at a coal mine"
DOI: 10.3535/lvq-2kt-s2s
title: Diarsia dahlii Hübner, 1813

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/x5t-bjv-hkb
title: Lasionycta Aurivillius, 1892

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/6wp-x9e-d27
title: Gonepteryx rhamni (Linnaeus, 1758)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.17632/2hs2mwy6fx.1
title: Vandenbergetal2025_RawData

description: Source data files for vandenberg et al 2025 "Efficacy of Clearflow treatment technologies in the treatment of mining effluent: Field-level testing at a coal mine"
DOI: 10.3535/bje-c1l-5tz
title: Xanthia (Cirrhia) Hübner, 1816

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/gnm-8k2-0e2
title: Lycaena phlaeas (Linnaeus, 1761)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/1j3-zws-7wp
title: Fabriciana adippe ([Denis & Schiffermüller], 1775)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/hcl-c0k-ys6
title: Catoptria permutatellus Herrich-Schäffer, 1849

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/zt0-bey-2dc
title: Zophodia convolutella Hübner, 1796

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/was-kfh-zts
title: Cucullia umbratica (Linnaeus, 1758)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/3c4-cg5-4fn
title: Oeneis jutta Hübner, 1806

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/3fd-1hz-0c8
title: Erebia lappona Thunberg, 1791

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.17632/69s3nh72rr
title: Sugarcane Disease Image Dataset

description: It was developed to support research related to the identification of diseases in the leaves of the sugarcane plant using image-based machine learning and deep learning techniques. The hypothesis is that specific features causing distinguishable variations in the color and texture patterns of leaves, along with structural deformity, are sufficient for models to accurately classify diseases.

There are three classes in this dataset: Healthy, Red Rot, and White Leaf. Healthy leaves appear uniformly green without visible damage. Red Rot images show reddish-brown lesions and discoloration that are usually the result of fungal infection. White Leaf samples display pale or whitish chlorotic leaves associated with phytoplasma infection. These clear visual differences illustrate the point that disease types can be diagnosed through image analysis and form a basis for the hypothesis that such patterns may effectively be learned by machine learning models.

The images were collected directly from the sugarcane fields of Maharashtra, India, using a mobile phone camera under natural daylight. Each image is manually reviewed to ensure its clarity before labeling according to references in agricultural diseases. Natural variation of field conditions-such as lighting conditions, leaf angles, backgrounds, and disease severity-has been captured in the dataset.

The dataset can be interpreted by researchers as a practical, field-collected resource suitable for training classification models, analyzing visual disease characteristics, and developing automated crop monitoring systems. This dataset can be used for CNN training, transfer learning, studies on image segmentation, or any plant disease detection pipeline. Users may apply some preprocessing steps such as resizing or normalization before training a model. Overall, the dataset forms a very reliable base for computer vision–based agricultural disease research.
DOI: 10.3535/hqh-t7y-2js
title: Sideridis (Heliophobus) reticulata Goeze, 1781

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/lay-7yt-y50
title: Glaucopsyche alexis (Poda, 1761)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/8sm-6ma-lkn
title: Acronicta (Subacronicta) megacephala ([Denis & Schiffermüller], 1775)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/bdq-c2m-8qr
title: Xestia (Megasema) c-nigrum (Linnaeus, 1758)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.17632/69s3nh72rr.1
title: Sugarcane Disease Image Dataset

description: It was developed to support research related to the identification of diseases in the leaves of the sugarcane plant using image-based machine learning and deep learning techniques. The hypothesis is that specific features causing distinguishable variations in the color and texture patterns of leaves, along with structural deformity, are sufficient for models to accurately classify diseases.

There are three classes in this dataset: Healthy, Red Rot, and White Leaf. Healthy leaves appear uniformly green without visible damage. Red Rot images show reddish-brown lesions and discoloration that are usually the result of fungal infection. White Leaf samples display pale or whitish chlorotic leaves associated with phytoplasma infection. These clear visual differences illustrate the point that disease types can be diagnosed through image analysis and form a basis for the hypothesis that such patterns may effectively be learned by machine learning models.

The images were collected directly from the sugarcane fields of Maharashtra, India, using a mobile phone camera under natural daylight. Each image is manually reviewed to ensure its clarity before labeling according to references in agricultural diseases. Natural variation of field conditions-such as lighting conditions, leaf angles, backgrounds, and disease severity-has been captured in the dataset.

The dataset can be interpreted by researchers as a practical, field-collected resource suitable for training classification models, analyzing visual disease characteristics, and developing automated crop monitoring systems. This dataset can be used for CNN training, transfer learning, studies on image segmentation, or any plant disease detection pipeline. Users may apply some preprocessing steps such as resizing or normalization before training a model. Overall, the dataset forms a very reliable base for computer vision–based agricultural disease research.
DOI: 10.3535/svd-yt1-7tw
title: Anarta (Calocestra) melanopa Thunberg, 1791

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/yl6-ccs-hyr
title: Oeneis jutta Hübner, 1806

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/zza-m17-w66
title: Agriphila tristellus [Denis & Schiffermüller], 1775

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/qa3-deq-7xn
title: Anarta (Calocestra) melanopa Thunberg, 1791

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/ras-6mp-bd7
title: Lasionycta Aurivillius, 1892

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/3kk-cyy-n73
title: Apamea (Apamea) oblonga (Haworth, 1809)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/kht-bfv-57y
title: Zophodia convolutella Hübner, 1796

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/dj8-fss-tff
title: Lycia hirtaria (Clerck, 1759)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/kwr-tqk-p0k
title: Platytes alpinella Hübner

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/ny9-67k-rzs
title: Parascotia fuliginaria (Linnaeus, 1761)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/amm-en4-g0d
title: Papilio machaon Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/cmj-7tc-s28
title: Indalia lutarella (Linnaeus, 1758)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/eaq-a46-8hv
title: Xestia (Xestia) sexstrigata Haworth, 1809

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/eej-e4j-9w6
title: Parascotia fuliginaria (Linnaeus, 1761)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/5m9-njx-2k9
title: Cyaniris semiargus (von Rottemburg, 1775)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/qbz-rk4-jnz
title: Amphipoea fucosa Freyer, 1830

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.17026/ar/5xkrqi
title: PAN-00114658 - coin/coin-related, Vespasianus (69-79) / Titus (79-81), dupondius/as

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00114658&lt;/p&gt;
description: Modified: 2025-08-26T08:38:19+02:00
DOI: 10.3535/20m-dz3-gg0
title: Xestia (Pachnobia) laetabilis Zetterstedt, 1839

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/n7g-n8c-j35
title: Lycaena phlaeas (Linnaeus, 1761)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.17632/tjjf39mjng
title: Hidden Alpha Repository

description: Code and data
DOI: 10.3535/558-9fs-vrg
title: Lycaena Fabricius, 1807

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/pbg-jgk-qv0
title: Hydraecia micacea Esper, 1789

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.5281/zenodo.17421725
title: Reproducible Research Platform Demo Project Player Bundle

description: Reproducible Research Platform Project Demo

A small study estimating the population growth rate from microscopy images using basic image analysis.

Overview

This RRP project repository is a simple demonstration project that illustrates how to mounted data from the research data management system (RDMS) openBIS ELN-LIMS. In our example micrsocpy data is managed in the RDMS and annotated with respective metadata. Using their permID the data is directly available in the RRP project for analysis and our mini study.

The main outcome of this example is:



How to perform a small study within RRP with the example of determining the population growth rate from microscopy images. The data originates from [1], and results are compared to [2].


Features



Integration with RRP and openBIS ELN--LIMS: Mounts data (microscopy) form the research data management system openBIS in RRP for direct use.

Reproducible workflow: Notebook documents interaction with data.

Visualization: Generates visualizations of the results.


Installation

 

Prerequisites



Local Docker installation.


Steps



Download and extract the .zip file

Run the play script for your operating system



Linux / macOS: play

Windows: play.bat or play.ps1




Usage

In RRP open and run the Jupyter notebook run_demo_analysis.ipynb

Workflow Overview



Reproducible workflow: Run the mini study.

Visualization: Results such as segmentation masks, number of cells, report are stored in the RRP result folder.


Directory Structure



├── .binder/ # Environment specifications, Python version, packages etc.
├── .rrp/ # Specification of required data from RDMS openBIS ELN-LIMS (Microscopy data)
├── resources # Folder containing references and splash image.
├── LICENSE # License
├── README.md # This file
└── run_demo_analysis.ipynb # Notebook demonstrating mounted data.


Contributing

We welcome contributions to improve this repository! Please follow these steps:



Fork the repository.

Create a new branch for your feature or bug fix.

Submit a pull request with a clear description of your changes.


Authors and acknowledgment



Andreas P. Cuny, ETH Zurich initial implementation


License

This project is licensed under the Apache 2.0 License. See LICENSE file for details.

Copyright © 2020-2025 ETH Zurich, Andreas P. Cuny, D-BSSE, CSB Group

References

1: Cuny, A. P., Ponti, A., Kündig, T., Rudolf, F. & Stelling, J. Cell region fingerprints enable highly precise single-cell tracking and lineage reconstruction. Nat. Methods 2021.10.26.465883 (2022) doi:https://doi.org/10.1038/s41592-022-01603-2.

2: Petersen, J. & Russell, P. Growth and the environment of Schizosaccharomyces pombe. Cold Spring Harb. Protoc. 2016, 210–226 (2016) doi:https://doi.org/10.1101/pdb.top079764.