cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7752175
title: On the Understandability of MLOps System Architectures: Dataset and Code

description: Title: On the Understandability of MLOps System Architectures: Dataset and Code

Authors: Stephen John Warnett; Uwe Zdun

About: This is the dataset and code artefact for the paper entitled "On the Understandability of MLOps System Architectures".

Paper Abstract: Machine Learning Operations (MLOps) is the practice of streamlining and optimising the machine learning (ML) workflow, from development to deployment, using DevOps (software development and IT operations) principles and ML-specific activities. Architectural descriptions of MLOps systems often consist of informal textual descriptions and informal graphical system diagrams that vary considerably in consistency, quality, detail, and content. Such descriptions only sometimes follow standards or schemata and may be hard to understand. We aimed to investigate informal textual descriptions and informal graphical MLOps system architecture representations and compare them with semi-formal MLOps system diagrams for those systems. We report on a controlled experiment with sixty-three participants investigating the understandability of MLOps system architecture descriptions based on informal and semi-formal representations. The results indicate that the understandability (quantified by task correctness) of MLOps system descriptions is significantly greater using supplementary semi-formal MLOps system diagrams, that using semi-formal MLOps system diagrams does not significantly increase task duration (and thus hinder understanding), and that task correctness is only significantly correlated with task duration when semi-formal MLOps system diagrams are provided.
description: This work was supported by: FFG (Austrian Research Promotion Agency) projects AMMONIS (no. 879705) and MODIS (no. FO999895431).
DOI: 10.5281/zenodo.7752176
title: On the Understandability of MLOps System Architectures: Dataset and Code

description: Title: On the Understandability of MLOps System Architectures: Dataset and Code

Authors: Stephen John Warnett; Uwe Zdun

About: This is the dataset and code artefact for the paper entitled "On the Understandability of MLOps System Architectures".

Paper Abstract: Machine Learning Operations (MLOps) is the practice of streamlining and optimising the machine learning (ML) workflow, from development to deployment, using DevOps (software development and IT operations) principles and ML-specific activities. Architectural descriptions of MLOps systems often consist of informal textual descriptions and informal graphical system diagrams that vary considerably in consistency, quality, detail, and content. Such descriptions only sometimes follow standards or schemata and may be hard to understand. We aimed to investigate informal textual descriptions and informal graphical MLOps system architecture representations and compare them with semi-formal MLOps system diagrams for those systems. We report on a controlled experiment with sixty-three participants investigating the understandability of MLOps system architecture descriptions based on informal and semi-formal representations. The results indicate that the understandability (quantified by task correctness) of MLOps system descriptions is significantly greater using supplementary semi-formal MLOps system diagrams, that using semi-formal MLOps system diagrams does not significantly increase task duration (and thus hinder understanding), and that task correctness is only significantly correlated with task duration when semi-formal MLOps system diagrams are provided.
description: This work was supported by: FFG (Austrian Research Promotion Agency) projects AMMONIS (no. 879705) and MODIS (no. FO999895431).
DOI: 10.5519/qd.dhzpc9ba
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (296 records)
DOI: 10.13140/rg.2.2.19171.73764
title: Modernist pavilion architecture from 1960-1980 in the Silesian province / Architektura pawilonowa z lat 1960 - 1980 na terenie województwa Śląskiego.
DOI: 10.5519/qd.qu0uksrv
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (296 records)
DOI: 10.6084/m9.figshare.25295539.v1
title: G by E interactions and yield stability in common bean genotypes

description: G EI
DOI: 10.6084/m9.figshare.25295539
title: G by E interactions and yield stability in common bean genotypes

description: G EI
DOI: 10.6084/m9.figshare.25295461.v1
title: Tucker-MMC: a new method to investigate the spatiotemporal mobility patterns and predictability of fake base stations

description: trajectories extracted from a crowdsourced spam message dataset and their understanding of mobility patterns and location prediction
DOI: 10.6084/m9.figshare.25295461
title: Tucker-MMC: a new method to investigate the spatiotemporal mobility patterns and predictability of fake base stations

description: trajectories extracted from a crowdsourced spam message dataset and their understanding of mobility patterns and location prediction
DOI: 10.5281/zenodo.10714988
title: MoMA Collection - Automatic Update

description: Temporary Description
DOI: 10.5281/zenodo.10714989
title: MoMA Collection - Automatic Update

description: Temporary Description
DOI: 10.34740/kaggle/dsv/7711229
title: OnlineFree
DOI: 10.34740/kaggle/dsv/7711228
title: AutoXGB
DOI: 10.5281/zenodo.10641289
title: Causal Learning at ESS: A Time Series Benchmark

description: The dataset is a benchmark intended for causal learning. It comprise control system data from the accelerator cryogenics plant at the European Spallation Source. The data was taken during three periods when the system was in steady state operation. There are 233 different process variables represented in the dataset. These arise from sensor measurements of physical quantities. Each measurement is indexed by a timestamp and have several metadata fields in addition to the value field. If you use the dataset, please cite this dataset as well as the paper S.W.Mogensen, K.Rathsman, P.Nilsson, Causal discovery in a complex industrial system: A time series benchmark, in Proceedings of the 3rd Conference on Causal Learning and Reasoning (CLeaR), 2024, Available: https://doi.org/10.48550/arXiv.2310.18654 The paper also contains a detailed description of the data and of the underlying system. More description, code, and help to get started can be found at https://soerenwengel.github.io/essdata

Note: Downloading the dataset can be slow. Therefore, we have published a reduced dataset containing one hour of operation data for testing and viewing the data. The reduced dataset is available from 10.5281/zenodo.10679737.
DOI: 10.5281/zenodo.10641290
title: Causal Learning at ESS: A Time Series Benchmark

description: The dataset is a benchmark intended for causal learning. It comprise control system data from the accelerator cryogenics plant at the European Spallation Source. The data was taken during three periods when the system was in steady state operation. There are 233 different process variables represented in the dataset. These arise from sensor measurements of physical quantities. Each measurement is indexed by a timestamp and have several metadata fields in addition to the value field. To ensure that you use the latest version of this dataset, please use this link: 10.5281/zenodo.10641289. If you use the dataset, please cite this dataset as well as the paper S.W.Mogensen, K.Rathsman, P.Nilsson, Causal discovery in a complex industrial system: A time series benchmark, in Proceedings of the 3rd Conference on Causal Learning and Reasoning (CLeaR), 2024, Available: https://doi.org/10.48550/arXiv.2310.18654 The paper also contains a detailed description of the data and of the underlying system.

Note: Downloading the dataset can be slow. Therefore, we have published a reduced dataset containing one hour of operation data for testing and viewing the data. The reduced dataset is available from 10.5281/zenodo.10679737.
DOI: 10.5281/zenodo.10709066
title: Causal Learning at ESS: A Time Series Benchmark

description: The dataset is a benchmark intended for causal learning. It comprise control system data from the accelerator cryogenics plant at the European Spallation Source. The data was taken during three periods when the system was in steady state operation. There are 233 different process variables represented in the dataset. These arise from sensor measurements of physical quantities. Each measurement is indexed by a timestamp and have several metadata fields in addition to the value field. If you use the dataset, please cite this dataset as well as the paper S.W.Mogensen, K.Rathsman, P.Nilsson, Causal discovery in a complex industrial system: A time series benchmark, in Proceedings of the 3rd Conference on Causal Learning and Reasoning (CLeaR), 2024, Available: https://doi.org/10.48550/arXiv.2310.18654 The paper also contains a detailed description of the data and of the underlying system. More description, code, and help to get started can be found at https://soerenwengel.github.io/essdata

Note: Downloading the dataset can be slow. Therefore, we have published a reduced dataset containing one hour of operation data for testing and viewing the data. The reduced dataset is available from 10.5281/zenodo.10679737.
DOI: 10.5281/zenodo.10334795
title: The official dataset of the paper "In vitro evaluation of enzymatically derived blackcurrant extract as prebiotic cosmetic ingredient: extraction conditions optimization and efect on cutaneous microbiota representatives" (https://doi.org/10.1186/s40538-023-00502-8)

description: This is the official repository of the paper "In vitro evaluation of enzymatically derived blackcurrant extract as a prebiotic cosmetic ingredient: extraction conditions optimization and effect on cutaneous microbiota representatives" (https://doi.org/10.1186/s40538-023-00502-8)
DISCLAIMER
The repository contains experimental data and is published for the sole purpose of giving additional background details on the respective publication "In vitro evaluation of enzymatically derived blackcurrant extract as a prebiotic cosmetic ingredient: extraction conditions optimization and effect on cutaneous microbiota representatives" (https://doi.org/10.1186/s40538-023-00502-8). See the README.txt file for more details.
DOI: 10.5281/zenodo.10334794
title: The official dataset of the paper "In vitro evaluation of enzymatically derived blackcurrant extract as prebiotic cosmetic ingredient: extraction conditions optimization and efect on cutaneous microbiota representatives" (https://doi.org/10.1186/s40538-023-00502-8)

description: This is the official repository of the paper "In vitro evaluation of enzymatically derived blackcurrant extract as a prebiotic cosmetic ingredient: extraction conditions optimization and effect on cutaneous microbiota representatives" (https://doi.org/10.1186/s40538-023-00502-8)

DISCLAIMER

The repository contains experimental data and is published for the sole purpose of giving additional background details on the respective publication "In vitro evaluation of enzymatically derived blackcurrant extract as a prebiotic cosmetic ingredient: extraction conditions optimization and effect on cutaneous microbiota representatives" (https://doi.org/10.1186/s40538-023-00502-8). See the README.txt file for more details.
DOI: 10.5281/zenodo.10715154
title: The official dataset of the paper "In vitro evaluation of enzymatically derived blackcurrant extract as prebiotic cosmetic ingredient: extraction conditions optimization and efect on cutaneous microbiota representatives" (https://doi.org/10.1186/s40538-023-00502-8)

description: This is the official repository of the paper "In vitro evaluation of enzymatically derived blackcurrant extract as a prebiotic cosmetic ingredient: extraction conditions optimization and effect on cutaneous microbiota representatives" (https://doi.org/10.1186/s40538-023-00502-8)

DISCLAIMER

The repository contains experimental data and is published for the sole purpose of giving additional background details on the respective publication "In vitro evaluation of enzymatically derived blackcurrant extract as a prebiotic cosmetic ingredient: extraction conditions optimization and effect on cutaneous microbiota representatives" (https://doi.org/10.1186/s40538-023-00502-8). See the README.txt file for more details.
DOI: 10.25442/hku.25295323
title: How a coastal megacity affects marine biodiversity and ecosystem function: Impacts of reduced water quality and other anthropogenic stressors

description: This is the data set in the published paper by Gotama et al. in Ecological Indicators. It includes environmental quality, ecosystem function, and species diversity and abundance data.
DOI: 10.25442/hku.25295323.v1
title: How a coastal megacity affects marine biodiversity and ecosystem function: Impacts of reduced water quality and other anthropogenic stressors

description: This is the data set in the published paper by Gotama et al. in Ecological Indicators. It includes environmental quality, ecosystem function, and species diversity and abundance data.
DOI: 10.5281/zenodo.10679736
title: Causal Learning at ESS: A Time Series Benchmark (reduced dataset)

description: A reduced dataset of the original dataset 10.5281/zenodo.10641289.

This dataset is indended for users to view and test a reduced dataset before downloading the original dataset. If you use any of the datasets, please site the paper 

S.W.Mogensen, K.Rathsman, P.Nilsson, Causal discovery in a complex industrial system: A time series benchmark, in Proceedings of the 3rd Conference on Causal Learning and Reasoning (CLeaR), 2024, Available: https://doi.org/10.48550/arXiv.2310.18654

The paper alos contains a detailed description of the data and of the underlying system.
DOI: 10.5281/zenodo.10679737
title: Causal Learning at ESS: A Time Series Benchmark (reduced dataset)

description: A reduced dataset of the original dataset 10.5281/zenodo.10641289.

This dataset is indended for users to view and test a reduced dataset before downloading the original dataset. If you use any of the datasets, please site the paper 

S.W.Mogensen, K.Rathsman, P.Nilsson, Causal discovery in a complex industrial system: A time series benchmark, in Proceedings of the 3rd Conference on Causal Learning and Reasoning (CLeaR), 2024, Available: https://doi.org/10.48550/arXiv.2310.18654

The paper alos contains a detailed description of the data and of the underlying system.
DOI: 10.6084/m9.figshare.11974515
title: Supplementary Table from Nearest vent, dearest friend: biodiversity of Tiancheng vent field reveals cross-ridge similarities in the Indian Ocean

description: Species presence and absence table used in the nMDS analysis.
DOI: 10.6084/m9.figshare.11974515.v1
title: Supplementary Table from Nearest vent, dearest friend: biodiversity of Tiancheng vent field reveals cross-ridge similarities in the Indian Ocean

description: Species presence and absence table used in the nMDS analysis.
DOI: 10.5281/zenodo.10708380
title: Spotter_III+mzml

description: Microspotter, Spotter III
DOI: 10.5281/zenodo.10708381
title: Spotter_III

description: Microspotter, Spotter III
DOI: 10.5281/zenodo.10715188
title: Spotter_III+mzml

description: Microspotter, Spotter III
DOI: 10.5281/zenodo.10612519
title: Data for: Erg Chech 002 Achondrite

description: Erg Chech 002 (EC 002) stands as the most ancient magmatic achondrite analyzed thus far, dating back 0.7–2.25 million years after the formation of Calcium-Aluminum-rich inclusions (CAIs). This meteorite presents a distinct igneous texture, characterized by coarse-grained orthopyroxene xenocrysts with a high Mg-number (atomic Mg/(Mg+Fe) × 100 = 80), believed to have originated from basaltic melts, embedded within an andesitic groundmass. Fine-grained pyroxene minerals surrounding the xenocrysts denote a contact zone between them and the groundmass. This repository encompasses both the chemical and isotopic data of the measured xenocrysts and minerals found in the contact zone and groundmass of EC 002.

Table A1 presents the raw major element concentrations (expressed as weight percent of their oxides) of the clinopyroxenes and orthopyroxenes. The mineral endmembers, namely enstatite (En)-Ferrosilite (Fs)- Wollastonite (Wo), are detailed in columns Q-S. Within EC 002, three generations of Cr-spinels have been identified based on their occurrences, with the major element concentrations documented in Table A2. Table A3 compiles the major element concentrations of the plagioclase minerals within EC 002, alongside the plagioclase endmembers, Anorthite (An)-Albite (Ab)- Orthoclase (Or), listed in columns N-P. The analyzed minerals encompass those hosted within the xenocrysts, and grains in the contact zone and the groundmass. Trace element concentrations (expressed in parts per million weight) in the xenocrysts and orthopyroxenes in the groundmass are documented in Table A4, while Table A5 provides the in-situ 18O/16O ratios of the measured pyroxene minerals, along with their En-Fs-Wo numbers.
DOI: 10.5281/zenodo.10612520
title: Data for: Erg Chech 0002 Achondrite Petrogenesis: Unveiling Hybrid Accretion Dynamics in the Early Solar System
DOI: 10.5281/zenodo.10612541
title: Data for: Erg Chech 002 Achondrite

description: Erg Chech 002 (EC 002) stands as the most ancient magmatic achondrite analyzed thus far, dating back 0.7–2.25 million years after the formation of Calcium-Aluminum-rich inclusions (CAIs). This meteorite presents a distinct igneous texture, characterized by coarse-grained orthopyroxene xenocrysts with a high Mg-number (atomic Mg/(Mg+Fe) × 100 = 80), believed to have originated from basaltic melts, embedded within an andesitic groundmass. Fine-grained pyroxene minerals surrounding the xenocrysts denote a contact zone between them and the groundmass. This repository encompasses both the chemical and isotopic data of the measured xenocrysts and minerals found in the contact zone and groundmass of EC 002.

Table A1 presents the raw major element concentrations (expressed as weight percent of their oxides) of the clinopyroxenes and orthopyroxenes. The mineral endmembers, namely enstatite (En)-Ferrosilite (Fs)- Wollastonite (Wo), are detailed in columns Q-S. Within EC 002, three generations of Cr-spinels have been identified based on their occurrences, with the major element concentrations documented in Table A2. Table A3 compiles the major element concentrations of the plagioclase minerals within EC 002, alongside the plagioclase endmembers, Anorthite (An)-Albite (Ab)- Orthoclase (Or), listed in columns N-P. The analyzed minerals encompass those hosted within the xenocrysts, and grains in the contact zone and the groundmass. Trace element concentrations (expressed in parts per million weight) in the xenocrysts and orthopyroxenes in the groundmass are documented in Table A4, while Table A5 provides the in-situ 18O/16O ratios of the measured pyroxene minerals, along with their En-Fs-Wo numbers.
DOI: 10.15468/h5wqjn
title: Gymnadenia conopsea (L.) R. Br. (Orchidaceae) in the Komi Republic

description: Gymnadenia conopsea (L.) R.Br. (Common fragrant orchid) is a boreal Eurasian species, one of the most common orchids in northern Europe. On the territory of the Komi Republic, the species is at the northern edge of its range; it is more common in the southern and southwestern areas of the region. It grows in bogs, damp meadows, grassy-sphagnum pine forests, in green moss grass and sphagnum spruce forests, wet grass mixed forests, and alder forests, as well as on limestone, marl, and gypsum outcrops with and without grass cover. G. conopsea is propagated mostly by seeds. The species is a highly specialized entomophylous plant attracting insects, mainly lepidoptera, by the color of corolla, nectar, and pleasant smell. The data set contains data on the distribution of G. conopsea in the Komi Republic, located in the European North-East Russia. In total, 311 localities of G. conopsea have been found within the borders of the Komi Republic, including 198 herbarium specimens and 113 occurrence records. The herbarium specimens are stored in the of Scientific Herbarium of the Institute of Biology Komi Science Centre (SYKO). The dataset includes 311 records. The point set was prepared with data obtained as a result of field studies of the authors and acquired from vascular plant collection of SYKO herbaria. Most of the occurrences’ descriptions included the following fields: "occurrenceID", "institutionCode", "basisOfRecord", "DatasetName", "eventDate", "year", "month", "day", "scientificName", "higherClassification", "kingdom", "phylum", "class", "order", "family", "genus", "specificEpithet", "scientificNameAuthorship", "taxonRank", "identifiedBy", "dateIdentified", "decimalLatitude", "decimalLongitude", "geodeticDatum", "coordinateUncertaintyInMeters", "verbatimCoordinateSystem", "georeferencedBy", "georeferencedDate", "continent", "country", "countryCode", "stateProvince", "county", "verbatimLocality", "language", "license", "collectionCode", "catalogNumber", "recordedBy", "otherCatalogNumbers", "associatedMedia". The work was carried out with the financial support of the project «Herbarium funds of the biological diversity of plants and fungi of the Collection Fund of the Komarov Botanical Institute, Russian Academy of Sciences: modernization, development and networking as a basis for fundamental research and improvement of genetic technologies» (Agreement No. 075-15-2021-1056 dated 09/28/2021).
DOI: 10.18141/1879673
title: Historic Submarine Landslides in the Northern Gulf of Mexico

description: This dataset provides a set of polygons representing the zone of depletion for historic submarine landslides (also referred to as mass transport deposits) within four regions of the US Exclusive Economic Zone in the northern Gulf of Mexico. Landslides were digitized by geologists and spatial scientists at the National Energy Technology Laboratory by visually interpreting landslide boundaries from a seismic-derived, high resolution bathymetric hillshade provided by the Bureau of Ocean and Energy Management (BOEM, 2017). A portion of the landslide features are derived from other spatial sources including the Seismic Water Anomalies dataset by BOEM (2016) as well as from McAdoo et al., 2000 and Twichell et al, 2005. The scale that landslides depletion areas can be interpreted at is limited by the spatial resolution of the gridded bathymetry, which is 12.192 meters (BOEM, 2017). For each landslide feature in the dataset, geometry metrics were calculated including geodesic area (km2) and geodesic perimeter (km) using the North America Albers Equal Area Conic projected coordinate system. The same geometry metrics were calculated for the four inventory regions.
DOI: 10.5281/zenodo.10079847
title: Pollen nutrients_FabianARuedenauer