cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25919/5d56963690f29
title: Parkes observations for project P1006 semester 2019APRS_13

description: We propose observations with the ultra-wide-bandwidth, low-frequency receiver installed at the Parkes telescope to carry out the first ultra-high time resolution, coherently de-dispersed search for pulsars in globular clusters. We have chosen the 11 most likely clusters for new discoveries. These clusters all have at least three pulsars already known allowing us to have a precise estimate of the pulsar dispersion measures and our observations will provide the first ultra-wide-bandwidth observation of these pulsars. Our observing strategy will enable us to search for extremely narrow pulsars and even pulsars with sub-millisecond periods.
DOI: 10.5281/zenodo.3369380
title: WikiPathways June 2019 Release - GPML and RDF files

description: Archive of the WikiPathways June 2019 GPML files for <em>Homo sapiens</em> and the GPMLRDF and WPRDF translations. The data is available as CCZero.
DOI: 10.5286/isis.e.rb1820398-3
title: PEG-Deep Eutectic Solvents for Nanoparticle Synthesis

description: Deep Eutectic Solvents (DES) are complexes of organic salts and neutral hydrogen bond donors. They are tuneable, low volatility liquids that are environmentally benign and which have been used for a variety of nanoparticle syntheses. Previously we have studied the pre-organisation of metal ions in a choline chloride:urea DES which allows growth of nanoparticles under lower temperature and less alkaline synthesis conditions than in water, and where addition of water gives some control over the particle morphology. We have used a DES based on a short polymeric species, polyethylene glycol; PEG200:urea and PEG200:thiourea to grow metal oxide and sulfide nanoparticles. Here we wish to probe interactions between the PEG and urea components to understand why this solvent has a lower viscosity than ChCl:urea and to determine how metal ions are organised by a multidentate polymer component.
DOI: 10.7910/dvn/qqza5e/3fqh55
title: J2243+2208_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/9mf77f
title: HD222582B_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/foecyy
title: J2305+4517_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/h3bj8w
title: J2302+4338_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/hcyeno
title: J2325+5308_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/lffxtp
title: J0018+4401E_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/libjik
title: J2254+6059_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/srsztd
title: LSPMJ0236+0652_tc.fits

description: :unav
DOI: 10.25345/c5z956
title: MassIVE MSV000084211 - VOCS from Dendrobatids from Colombia
title: Samples from extraction of volatile organic compounds from frogs using two sampling methods: in vivo and sampling from the skin and a DVB/CAR/PDMS-SPME fiber. Splitless injection mode using a desorption temperature of 250C. Separation was performed initiating to 40C for 3 min, and then increasing the temperature to 100C using a rate of 6C/min, afterwards incresing to 200C changing the rate to 4C/min, and finally increasing to 300C, using a rate of 20C/min, and maintaing to this temperature for 3 min. Analysis were performed in a GC HP 6890 Series equipped with an Agilent Mass Selective Detector 5973 (Agilent technologies, Palo Alto, CA, USA). Separation was performed on a BP-5 capillary GC column (30 m 0.25 mm 0.25 um, SGE, Austin, TX, USA) using helium as a carrier gas at a flow rate of 1.0 mL/min.
DOI: 10.5281/zenodo.3369373
title: Autobiographical memory data

description: Data from study examining the relationship between depressive symptoms and autobiographical memory valence and visual perspective.
DOI: 10.5281/zenodo.3369374
title: Autobiographical memory data

description: Data from study examining the relationship between depressive symptoms and autobiographical memory valence and visual perspective.
DOI: 10.5281/zenodo.3369379
title: WikiPathways June 2019 Release - GPML and RDF files

description: Archive of the WikiPathways June 2019 GPML files for <em>Homo sapiens</em> and the GPMLRDF and WPRDF translations. The data is available as CCZero.
DOI: 10.7910/dvn/qqza5e/0vaswn
title: J0028+5022_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/5ekcf4
title: J1836+1336_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/b3c0pm
title: J0214+1725_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/ildsr6
title: J2132+2433SW_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/jwhcsk
title: J0233+2455_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/tdansa
title: J2229+4128_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/wnnztu
title: J2132+2433NE_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/x5tb7t
title: J2217+1521_tc.fits

description: :unav
DOI: 10.34681/gnt1-nq40
title: National Survey of Current and Former Foster Parents, 1993

description: The purpose of the National Survey of Current and Former Foster Parents was to collect and analyze data from a nationally representative sample of current and former foster parents that would provide direction for future policy development. This study used a multistage stratified design where probability sampling was employed at each stage of the design. A mail/telephone survey was conducted of current and former foster parents in 16 counties in nine states. Based on lists provided by the counties, 1,572 current foster parents and 362 former foster parents received a questionnaire in the mail. Follow up post cards and telephone calls were made. The survey was designed to identify foster parent characteristics, the types of children for whom they provided care, the types of children they would be willing to care for in the future, and their interactions with the child welfare system. An overall response rate of 71% was achieved.
DOI: 10.34681/ngts-3h55
title: Runaway and Homeless Youth Management Information System (1997)

description: It is estimated that over a million young people run away or become homeless each year. These youth face increasingly complex issues, including substance abuse, physical and sexual abuse, and AIDS. The serious issues faced by these youths are coupled with funding constraints among almost all agencies providing services to this population.In 1974 the Family and Youth Services Bureau (FYSB) authorized funding to assist community based programs to serve youth who were not otherwise being served by traditional human service agencies. The funding was used for the operation of basic center programs which would provide support for runaway and homeless youth (RHY). The programs offered emergency shelter, crisis intervention services, and family reunification services. In 1988 the Transitional Living Program was introduced in order to provide services to older youth requiring assistance in becoming self-sufficient. While helping to support at-risk youth, the FYSB laws also mandate that certain data be regularly collected and reported. For example, FYSB supported agencies must report on the profile of the youth and families they serve, and provide an overview of the services which they deliver under their grant programs. In order to assist these grantees in their reporting responsibilities, FYSB funded the development of a Runaway and Homeless Youth Management Information System (RHY MIS). The RHY MIS was designed to provide comprehensive information on youth served, services provided, and programs which provide the services.The RHY MIS was designed, developed, and implemented by Information Technology International (ITI). Gradual implementation of the MIS began in 1992 with approximately 400 RHY grantee sites across the country. By 1995, virtually all existing grant programs had at least one staff member who had been trained and grantees were expected to use the MIS and submit data to FYSB on a quarterly basis. The fiscal year 1997 RHY MIS dataset contains data submitted during the federal fiscal year 1997. Data are included from participating agencies in 53 U.S. States and Territories. The dataset includes three files. A demographics file contains 84846 observations and 153 variables. Two additional files contain 68100 observations and a combined 235 variables pertaining to youth problems and services provided.
DOI: 10.7910/dvn/qqza5e/ceyd38
title: J0007+0800_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/iq1g0o
title: LSPMJ0045+0015N_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/le8bbz
title: J2117+6402_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/mxvtwh
title: J2215+6613_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/sseiuo
title: LSPMJ0255+2652W_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/ttgnvw
title: Gl53.1B_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/uqnv8y
title: J0103+6221_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/w2pwit
title: J0016+0507_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/zxdd5z
title: J2223+3227_tc.fits

description: :unav
DOI: 10.34681/jd5k-fs14
title: National Youth Victimization Prevention Survey, 1992-1994

description: There were two primary goals of the National Youth Victimization Prevention Study. One was to derive estimates of various forms of victimization among youths. The other was to obtain children’s assessments of the victimization prevention programs which many schools have begun offering over the past decade. Data were collected by telephone survey from 2000 children between the ages of 10 and 16 and their caretakers. Children were interviewed at two time points, the initial survey time and a 15 month follow-up. In addition to collecting basic demographic information, the survey asked children to recall details of victimizations personally experienced, respond to a test of knowledge about sexual victimization, recall the content of prevention programs to which they were exposed, render judgments regarding the usefulness of these programs, report on behavioral, social and psychological troubles (including offense behavior and substance abuse), and express opinions on a range of topics including the level of crime in their schools and in their neighborhoods, and reaction to the survey itself.
DOI: 10.7910/dvn/qqza5e/4uez0s
title: J2316+1937_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/8edgez
title: J2309+5506W_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/9wtfqv
title: J2146+3813_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/bktepb
title: J2040+6500_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/egmalo
title: J2001+0016_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/hhzyv5
title: J0212+0000_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/mnmgtj
title: J2147+5014_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/ugknzw
title: J1909+1740_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/vkol3c
title: J2116+2951E_tc.fits

description: :unav
DOI: 10.5281/zenodo.3370092
title: Expansion of coccidioidomycosis (Valley fever) endemic regions in the United States in response to climate change: projections of disease incidence

description: This file contains estimations of coccidioidomycosis (Valley fever) incidence data in cases per 100,000 population per year for the contemporary time period and projections throughout the 21st century in response to RCP4.5 and RCP8.5 climate scenarios, associated with the publication: Gorris, M. E., Treseder, K. K., Zender, C. S., and Randerson, J. T. (2019). Expansion of coccidioidomycosis endemic regions in the United States in response to climate change. <em>GeoHealth</em>. The data is reported for each county in the conterminous US with its associated FIPS code (Column 1), county name (Column 2), state FIPS code (Column 3), and state name (Column 4). Column 5 contains the estimation of mean annual Valley fever incidence averaged from 2000-2015. Column 6-8 contain the estimations of mean annual Valley fever incidence for the 11-year averages surrounding years 2035, 2065, and 2095 for RCP4.5 climate scenario. Likewise, Columns 9-11 contain the estimations of mean annual Valley fever incidence for the 11-year averages surrounding years 2035, 2065, and 2095 for the RCP8.5 climate scenario. Details about how the incidence data was calculated may be read in the Methods subsection of the paper under "Modeling of current and future mean annual Valley fever incidence". The data provided here was used to create Figure 7 and Supporting Information Figure S5. Counties that have non-zero incidence are considered endemic by our climate-constrained niche model, so this data may also be used to create portions of Figures 3, 4, and S3.
DOI: 10.5281/zenodo.3370093
title: Expansion of coccidioidomycosis (Valley fever) endemic regions in the United States in response to climate change: projections of disease incidence

description: This file contains estimations of coccidioidomycosis (Valley fever) incidence data in cases per 100,000 population per year for the contemporary time period and projections throughout the 21st century in response to RCP4.5 and RCP8.5 climate scenarios, associated with the publication: Gorris, M. E., Treseder, K. K., Zender, C. S., and Randerson, J. T. (2019) Expansion of coccidioidomycosis endemic regions in the United States in response to climate change. <em>GeoHealth</em>. The data is reported for each county in the conterminous US with its associated FIPS code (Column 1), county name (Column 2), state FIPS code (Column 3), and state name (Column 4). Column 5 contains the estimation of mean annual Valley fever incidence averaged from 2000-2015. Column 6-8 contain the estimations of mean annual Valley fever incidence for the 11-year averages surrounding years 2035, 2065, and 2095 for RCP4.5 climate scenario. Likewise, Columns 9-11 contain the estimations of mean annual Valley fever incidence for the 11-year averages surrounding years 2035, 2065, and 2095 for the RCP8.5 climate scenario. Details about how the incidence data was calculated may be read in the Methods subsection of the paper under "Modeling of current and future mean annual Valley fever incidence". The data provided here was used to create Figure 7 and Supporting Information Figure S5. Counties that have non-zero incidence are considered endemic by our climate-constrained niche model, so this data may also be used to create portions of Figures 3, 4, and S3.
DOI: 10.5281/zenodo.3370094
title: DWD European Weather 2

description: opendata.dwd.de - OpenData by Deutscher Wetter Dienst Conditions: https://www.dwd.de/EN/service/copyright/copyright_node.html dates and times are UTC.
DOI: 10.7910/dvn/qqza5e/92bpm4
title: J2151+1336_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/9wyqcc
title: J2148+0126_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/ae96e6
title: J2053+1037_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/eu57zx
title: J2152+2725_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/nuqnuy
title: J2057+2221_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/ojiejn
title: J2215+5440_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/sit7sy
title: J2224+5200_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/taywju
title: J2144+1703_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/upt9py
title: J2250+5136_tc.fits

description: :unav
DOI: 10.21227/nj20-bw32
title: Magnetic resonance spectroscopy data for GABA quantification using MEGAPRESS pulse sequence

description: Magnetic resonance spectroscopy (MRS) data for a series of GABA phantoms specifically designed to provide ground truth data for GABA quantification based on MRS data. The spectra were obtained using the WIP Siemens implementation svs-edit of the common edited spectroscopy MEGAPRESS sequence on a 3T Siemens Magnetom Skyra system installed in the Clinical Imaging Unit at Swansea University (UK).
DOI: 10.7910/dvn/qqza5e/1ccbjm
title: J1958+0955_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/7biph1
title: J2017+0559_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/7cyxqu
title: J0601+5935_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/dkfxp0
title: J1922+0702_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/hhj4vf
title: J0631+4129_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/k0yuwk
title: J1955+0624_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/khstik
title: J2040+1529_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/mb7nhe
title: J1916+0509_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/ryc69r
title: J0734+2220_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/0rgreu
title: J0358+1230_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/4myn5j
title: J0438+2813_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/byzznz
title: J0336+3118_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/chopsc
title: J0452+4042_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/d1ligl
title: J0336+0329_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/msuulf
title: J0407+1413W_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/o7lpwq
title: J0318+4240_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/rjynkb
title: J0257+1047_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/yr2y3f
title: J0559+5834_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/500z1c
title: J0253+1652_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/dbtcrx
title: J0018+2748_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/eixdxw
title: J1105+5005_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/qqokzu
title: J0223+2823_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/rafrbg
title: J0248+2704S_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/rkhd8u
title: J0153+4427_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/sjhpln
title: J0024+2626_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/sn7xeo
title: J0220+0258_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/tdmodq
title: J0024+3002_tc.fits

description: :unav
DOI: 10.5281/zenodo.3368392
title: Syntactical Carving of PNGs and Automated Generation of Reproducible Datasets

description: This is the dataset we used in the evaluation of our paper “Syntactical Carving of PNGs and Automated Generation of Reproducible Datasets”.
DOI: 10.5281/zenodo.3368393
title: Syntactical Carving of PNGs and Automated Generation of Reproducible Datasets

description: This is the dataset we used in the evaluation of our paper “Syntactical Carving of PNGs and Automated Generation of Reproducible Datasets”.
DOI: 10.5281/zenodo.3369659
title: Eco-evolutionary processes underlying early warning signals of population declines

description: Datasets for the paper appearing in Journal of Animal ecology : "Eco-evolutionary processes underlying early warning signals of population declines". Also GitHub repository link :https://github.com/GauravKBaruah/ECO-EVO-EWS-DATA
DOI: 10.5281/zenodo.3369660
title: Eco-evolutionary processes underlying early warning signals of population declines

description: Datasets for the paper appearing in Journal of Animal ecology : "Eco-evolutionary processes underlying early warning signals of population declines". Also GitHub repository link :https://github.com/GauravKBaruah/ECO-EVO-EWS-DATA
DOI: 10.7910/dvn/qqza5e/dtjlob
title: J2117+2053S_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/gzne2d
title: J2117+2053N_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/mj2l05
title: J2350+0956E_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/ommytp
title: J1100+3728_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/otncwo
title: J2311+0831_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/pugoem
title: J0744+0333_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/pyxf45
title: J2101+3314E_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/rlgssq
title: J2350+0956W_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/xr1dw3
title: J0709+0800_tc.fits

description: :unav
DOI: 10.18746/bmth.data.00000077
title: An RCT of individualised variations in the start position of the Closed-Kinetic Chain Upper Extremity Stability Test
DOI: 10.5281/zenodo.3368883
title: Collection of global datasets for the study of floods, droughts and their interactions with human societies

description: This is a collection of 124 global and free datasets allowing for spatial (and temporal) analyses of floods, droughts and their interactions with human societies. We have structured the datasets into seven categories: hydrographic baseline, hydrological dynamics, hydrological extremes, land cover & agriculture, human presence, water management, and vulnerability. Please refer to Lindersson et al. (in preparation) for further information about review methodology. The collection is a descriptive list, holding the following information for each dataset: Category<em> - as structured in Lindersson et al. (in preparation).</em> Sub-category<em>- as structured in Lindersson et al. (in preparation).</em> Abbreviation - <em>official or as specified in Lindersson et al. (in preparation).</em> Title <em>- full title of dataset.</em> Product(s)<em> - type of product(s) offered by the dataset.</em> Period<em> - time period covered by the dataset, not defined for all datasets.</em> Temporal resolution<em> - not defined for static datasets.</em> Angular spatial resolution<em> - only defined for gridded datasets.</em> Metric spatial resolution <em>- only defined for gridded datasets.</em> Map scale Extent<em> - geographic coverage of dataset given in latitude limits.</em> Description Creating institute(s) Data type<em> - raster, vector or tabular.</em> File format Primary EO type<em> - specifies if the product primarily is based on remote sensing, ground-based data, or a hybrid between remote sensing and ground-based data.</em> Data sources<em> - lists the data sources behind the dataset, to the extent this is feasible.</em> Data sources also in this table<em> - data sources that are also included as datasets in this collection.</em> Intentionally compatible with<em> - defines other datasets in this collection that the dataset is intentinoally compatible with.</em> Citation<em> - dataset reference or credit.</em> Documentation <em>- dataset documentation.</em> Web address<em> - dataset access link.</em> NOTE: Carefully consult the data usage licenses as given by the data providers, to assure that the exact permissions and restrictions are followed.
DOI: 10.5281/zenodo.3369906
title: weecology/portalPredictions 2019-08-16

description: Using various models to forecast abundances at Portal
DOI: 10.5281/zenodo.3369907
title: weecology/forecasts 2019-08-16

description: Archived forecasts for future analysis
DOI: 10.7910/dvn/qqza5e/1ywows
title: J0352+1701_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/kbjokl
title: J0540+0854_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/oxeew8
title: J0642+0334_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/p43mlt
title: J0431+5858W_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/q9tykj
title: J0200+1303_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/qg87hk
title: J0111+1526_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/sf3ath
title: J0503+2122_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/vseheu
title: J0544+0537_tc.fits

description: :unav
DOI: 10.7910/dvn/qqza5e/zcwvbd
title: J0144+1620_tc.fits

description: :unav