cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21942/uva.12608645.v1
title: Comparison microbiological indices in spontaneous voided urine or urine obtained from incontinence material

description: This dataset belongs to the PROGRESS study (diagnosing urine tract infections in elderly nursing home residents)<br>The data are for a comparison of urine culture and urine dipstick results in urine that is spontaneously voided or obtained from incontinence material. <br>Obtaining a urine specimen for diagnosis is often a challenge in this population. If urine obtained from incontinence material could be used instead, this would make it possible that UTI treatment is started more frequently based on a proper microbiological evidence, rather than empirically. <br>We performed a laboratory-based non-inferiority study comparing these two sources of urine with regards to the presence of uropathogens in the culture, the number of colony counts in the culture, and the semi-quantitive results of the dipstick test (leucocytes and nitrite).<br>Urine specimens were randomly sampled from routine specimens present in a single bacteriology laboratory in a tertiary hospital. Specimens were used within 24 hours of voiding. Remnants of the urine (10 ml) were poured on incontinence material, incubated for 3 hours, after which dissected material was added to 9 ml of sterile water, and vortexed for 10 seconds. Bacterial cultures were conducted using routine procedures in which bacterial growth was assessed after overnight incubation, and species were identified though Maldi-tof mass spectrometry. Dipstick analysis used Combur2 from Roche.<br>Data structureThe file is in a .cvs format outputted through STATA version 16.0. The dataset is organised in the long format. The variable “pair” links the two urine sources. <br>CodebookThe file is in a .xlsx format. It lists the variables present in the database with their type, description, categorisation, and additional comments where applicable.<br>
DOI: 10.21227/00m0-5w32
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/4m20-jr10
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.5281/zenodo.3930996
title: Preprocessing scripts and data for study: Identifying high-confidence capture Hi-C interactions using CHiCANE

description: Preprocessing scripts and processed data from CHi-C libraries generated from breast cancer cells (T47-D) and Megakaryoctye cells (MK).
DOI: 10.21227/1qsa-0j45
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/035k-at78
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/z6nf-r359
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/abhj-4876
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.15161/oar.it/30535
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: 10.21227/5qeb-9e13
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.5281/zenodo.3931501
title: CIMAS economic evaluation dataset. San Piero a Grado, Pisa

description: Dataset of economic parameters of a LTE conducted in San Piero a Grado, Pisa (Italy) (Italian language)
DOI: 10.5281/zenodo.3931500
title: CIMAS economic evaluation dataset. San Piero a Grado, Pisa

description: Dataset of economic parameters of a LTE conducted in San Piero a Grado, Pisa (Italy) (Italian language)
DOI: 10.21227/jrgj-t173
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/p0fb-bm82
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/2rfv-my21
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/t029-5e31
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/fq2d-4496
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/6jqm-1238
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/3jz1-qa36
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/kx9m-0e95
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/4jq8-aa15
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.15131/shef.data.12328226.v5
title: CoVid Plots and Analysis

description: # COVID-19Plots and analysis relating to the coronavirus pandemic. Includes five sets of plots and associated R code to generate them.1) HeatmapsUpdated every few days - heatmaps of COVID-19 case and death trajectories for Local Authorities (or equivalent) in England, Wales, Scotland, Ireland and Germany.2) All cause mortalityUpdated on Tuesday (for England & Wales), Wednesday (for Scotland) and Friday (for Northern Ireland) - analysis and plots of weekly all-cause deaths in 2020 compared to previous years by country, age, sex and region. Also a set of international comparisons using data from mortality.org3) ExposuresNo longer updated - mapping of potential COVID-19 mortality exposure at local levels (LSOAs) in England based on the age-sex structure of the population and levels of poor health.There is also a Shiny app which creates slightly lower resolution versions of the same plots online, which you can find here: https://victimofmaths.shinyapps.io/covidmapper/, on GitHub https://github.com/VictimOfMaths/COVIDmapper and uploaded to this record4) Index of Multiple Deprivation No longer updated - preliminary analysis of the inequality impacts of COVID-19 based on Local Authority level cases and levels of deprivation. 5) Socioeconomic inequalities. No longer updated (unless ONS release more data) - Analysis of published ONS figures of COVID-19 and other cause mortality in 2020 compared to previous years by deprivation decile.<br>Latest versions of plots and associated analysis can be found on Twitter: https://twitter.com/victimofmaths<br>This work is described in more detail on the UK Data Service Impact and Innovation Lab blog: http://lab.ukdataservice.ac.uk/2020/05/21/visualising-high-risk-areas-for-covid-19-mortality/<br>Adapted from data from the Office for National Statistics licensed under the Open Government Licence v.1.0.http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/<br>
DOI: 10.21227/5hmm-eb68
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/e691-eg73
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/rmf9-dn57
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/k94h-re16
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/h3jc-0v63
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/xcr4-ew52
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/szqy-6055
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.21227/ae5s-vv49
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.17876/rave/dr.6/fields/20030412_1047m24
title: RAVE Field 20030412_1047m24

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030419_1029m24
title: RAVE Field 20030419_1029m24

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030419_1231m34
title: RAVE Field 20030419_1231m34

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030419_1418m30
title: RAVE Field 20030419_1418m30

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030420_1051m27
title: RAVE Field 20030420_1051m27

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030420_1204m33
title: RAVE Field 20030420_1204m33

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030420_1353m32
title: RAVE Field 20030420_1353m32

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030420_1504m25
title: RAVE Field 20030420_1504m25

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030421_1138m31
title: RAVE Field 20030421_1138m31

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030421_1621m07
title: RAVE Field 20030421_1621m07

description: A field from the RAVE survey
DOI: 10.21227/bp8q-6t88
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.17876/rave/dr.6/fields/20030509_1042m11
title: RAVE Field 20030509_1042m11

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030509_1208m21
title: RAVE Field 20030509_1208m21

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030509_1345m21
title: RAVE Field 20030509_1345m21

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030510_1052m20
title: RAVE Field 20030510_1052m20

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030510_1201m27
title: RAVE Field 20030510_1201m27

description: A field from the RAVE survey
DOI: 10.21227/7982-2k31
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.17876/rave/dr.6/fields/20030510_1934m59
title: RAVE Field 20030510_1934m59

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030511_1512m17
title: RAVE Field 20030511_1512m17

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030518_1040m04
title: RAVE Field 20030518_1040m04

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030518_1430m16
title: RAVE Field 20030518_1430m16

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030518_1939m54
title: RAVE Field 20030518_1939m54

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030519_1101m15
title: RAVE Field 20030519_1101m15

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030519_1229m05
title: RAVE Field 20030519_1229m05

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030519_1634m02
title: RAVE Field 20030519_1634m02

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030609_1232m22
title: RAVE Field 20030609_1232m22

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030610_1431m23
title: RAVE Field 20030610_1431m23

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030610_1559m14
title: RAVE Field 20030610_1559m14

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030610_1929m76
title: RAVE Field 20030610_1929m76

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030610_2034m29
title: RAVE Field 20030610_2034m29

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030617_1247m17
title: RAVE Field 20030617_1247m17

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030617_1418m12
title: RAVE Field 20030617_1418m12

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030617_1543m18
title: RAVE Field 20030617_1543m18

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030617_1928m71
title: RAVE Field 20030617_1928m71

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030617_1944m48
title: RAVE Field 20030617_1944m48

description: A field from the RAVE survey
DOI: 10.21227/9a8z-cb17
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.17876/rave/dr.6/fields/20030617_2206m18
title: RAVE Field 20030617_2206m18

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030617_2227m08
title: RAVE Field 20030617_2227m08

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030618_1223m16
title: RAVE Field 20030618_1223m16

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030618_1437m09
title: RAVE Field 20030618_1437m09

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030618_1543m18
title: RAVE Field 20030618_1543m18

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030618_1928m71
title: RAVE Field 20030618_1928m71

description: A field from the RAVE survey
DOI: 10.21227/k1b6-je83
title: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"

description: Datasets and codes for "Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process"
DOI: 10.17876/rave/dr.6/fields/20030618_2058m55
title: RAVE Field 20030618_2058m55

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030618_2101m30
title: RAVE Field 20030618_2101m30

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030618_2227m08
title: RAVE Field 20030618_2227m08

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030619_1246m11
title: RAVE Field 20030619_1246m11

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030619_1408m19
title: RAVE Field 20030619_1408m19

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030619_1524m21
title: RAVE Field 20030619_1524m21

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030619_1621m07
title: RAVE Field 20030619_1621m07

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030619_1939m54
title: RAVE Field 20030619_1939m54

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030619_2019m48
title: RAVE Field 20030619_2019m48

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030619_2056m35
title: RAVE Field 20030619_2056m35

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030709_1343m27
title: RAVE Field 20030709_1343m27

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030709_1419m30
title: RAVE Field 20030709_1419m30

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030709_1929m76
title: RAVE Field 20030709_1929m76

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030709_2041m24
title: RAVE Field 20030709_2041m24

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030709_2206m18
title: RAVE Field 20030709_2206m18

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030710_1343m27
title: RAVE Field 20030710_1343m27

description: A field from the RAVE survey
DOI: 10.5281/zenodo.3931581
title: Rainfall-runoff data from an urban catchment in Luleå, Sweden.

description: Description and map of the catchment:<br> Broekhuizen, Ico, Günther Leonhardt, Jiri Marsalek, and Maria Viklander. “Event Selection and Two-Stage Approach for Calibrating Models of Green Urban Drainage Systems.” Hydrology and Earth System Sciences 24, no. 2 (February 26, 2020): 869–85. https://doi.org/10.5194/hess-24-869-2020. Rain gauge: Geonor T200B weighing bucket . Alter-type wind shield. Flow gauge: Teledyne ISCO 2150 Area-Velocity: acoustic Doppler for flow velocity, pressure transducer for water level. Additional information on field calibration checks of the rain gauge and laboratory testing of the same type of flow sensor:<br> Broekhuizen, Ico. “Uncertainties in Rainfall-Runoff Modelling of Green Urban Drainage Systems: Measurements, Data Selection and Model Structure.” Licentiate thesis, Luleå University of Technology, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-73367. Notes:<br> - The observations in this data set cover the snow-free parts of 2016-2019.<br> - For flow data, only observations &gt;= 1 l/s are provided. The authors would like to thank Helen Galfi, Ralf Rentz and Karolina Berggren for their work in the initial setup and maintenance of the field measurements.
DOI: 10.17876/rave/dr.6/fields/20030710_1431m23
title: RAVE Field 20030710_1431m23

description: A field from the RAVE survey
DOI: 10.5281/zenodo.3925024
title: Supporting data for "Reducing uncertainties in urban drainage models by explicitly accounting for timing errors in objective functions"

description: Supporting data for "Reducing uncertainties in urban drainage models by explicitly accounting for timing errors in objective functions" submitted to Water Resources Research. Contains: SWMM template files. Objective function values for all model runs. Jupyter Notebooks used to create figures and tables for the article. Copy of rainfall runoff data available from https://doi.org/10.5281/zenodo.3931582 For python implementations of the Hydrograph Matching Algorithm (Ewen 2011) see https://doi.org/10.5281/zenodo.3923792 Ewen, John. “Hydrograph Matching Method for Measuring Model Performance.” <em>Journal of Hydrology</em> 408, no. 1–2 (September 2011): 178–87. https://doi.org/10.1016/j.jhydrol.2011.07.038.
DOI: 10.5281/zenodo.3925023
title: Supporting data for "Reducing uncertainties in urban drainage models by explicitly accounting for timing errors in objective functions"

description: Supporting data for "Reducing uncertainties in urban drainage models by explicitly accounting for timing errors in objective functions" submitted to Water Resources Research. Contains: SWMM template files. Objective function values for all model runs. Jupyter Notebooks used to create figures and tables for the article. Copy of rainfall runoff data available from https://doi.org/10.5281/zenodo.3931582 For python implementations of the Hydrograph Matching Algorithm (Ewen 2011) see https://doi.org/10.5281/zenodo.3923792 Ewen, John. “Hydrograph Matching Method for Measuring Model Performance.” <em>Journal of Hydrology</em> 408, no. 1–2 (September 2011): 178–87. https://doi.org/10.1016/j.jhydrol.2011.07.038.
DOI: 10.17876/rave/dr.6/fields/20030710_1508m10
title: RAVE Field 20030710_1508m10

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030710_1930m65
title: RAVE Field 20030710_1930m65

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030711_2034m29
title: RAVE Field 20030711_2034m29

description: A field from the RAVE survey
DOI: 10.17876/rave/dr.6/fields/20030711_2101m30
title: RAVE Field 20030711_2101m30

description: A field from the RAVE survey