cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21233/qnp1-zw55
title: Kogyae Plot 3 (Savannah plot) pollen surface sample dataset

description: Raw data for the Kogyae Plot 3 (Savannah plot) pollen surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/apxw-8j44
title: Rurzyca testate amoebae surface sample dataset

description: Raw data for the Rurzyca testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/dc97-hc69
title: Cheng et al. 2020 Site 204 pollen surface sample dataset

description: Raw data for the Cheng et al. 2020 Site 204 pollen surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.6084/m9.figshare.19407044
title: HL-60 H3K4me1

description: ChIP H3K4me1 HL-60<br>
DOI: 10.6084/m9.figshare.19407044.v1
title: HL-60 H3K4me1

description: ChIP H3K4me1 HL-60<br>
DOI: 10.21233/q7w1-td89
title: Surmene Agacbasi Yaylasi testate amoebae surface sample dataset

description: Raw data for the Surmene Agacbasi Yaylasi testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/f65q-xk88
title: Mauntschas testate amoebae surface sample dataset

description: Raw data for the Mauntschas testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.6084/m9.figshare.19407050
title: HL-60 H3K4me3

description: ChIP H3K4me3 HL-60<br>
DOI: 10.21233/csd5-sz29
title: Moss of Achnacree testate amoebae surface sample dataset

description: Raw data for the Moss of Achnacree testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/n8mg-1j67
title: Lej de Staz testate amoebae surface sample dataset

description: Raw data for the Lej de Staz testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/6x2q-wv15
title: Slieveanorra testate amoebae surface sample dataset

description: Raw data for the Slieveanorra testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/bsra-m380
title: Moss of Achnacree testate amoebae surface sample dataset

description: Raw data for the Moss of Achnacree testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/jgkt-mv66
title: SB-1, Hwy 38, Mill Creek pollen surface sample dataset

description: Raw data for the SB-1, Hwy 38, Mill Creek pollen surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.34740/kaggle/dsv/3348913
title: Russian Invasion of Ukraine
DOI: 10.21233/jhhw-r671
title: Laguna Rabadilla de Vaca charcoal dataset

description: Raw data for the Laguna Rabadilla de Vaca charcoal dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/d08j-8z32
title: Lej Marsch testate amoebae surface sample dataset

description: Raw data for the Lej Marsch testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/8qqr-gb76
title: SJ-14, Willow Creek Trail pollen surface sample dataset

description: Raw data for the SJ-14, Willow Creek Trail pollen surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/dhzq-ek06
title: Sigleo 1971 Grand Canyon Transect Site 5 pollen surface sample dataset

description: Raw data for the Sigleo 1971 Grand Canyon Transect Site 5 pollen surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/750d-s685
title: Kuivajärvi suo testate amoebae surface sample dataset

description: Raw data for the Kuivajärvi suo testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/102f-ct44
title: Man'inskii Khartym pollen dataset

description: Raw data for the Man'inskii Khartym pollen dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/094z-7r12
title: Mile 41, Buck Farm Canyon pollen surface sample dataset

description: Raw data for the Mile 41, Buck Farm Canyon pollen surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/9vg7-a861
title: Dwingeloo testate amoebae surface sample dataset

description: Raw data for the Dwingeloo testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.18739/a2dr2p96f
title: DataHawk2 Uncrewed Aircraft System data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign, A1 level

description: This dataset is derived from DataHawk2 fixed-wind uncrewed aircraft system (UAS) flights that were conducted in the central Arctic Ocean over sea ice during the MOSAiC expedition. The data include Universal Coordinated Time (UTC), aircraft position and attitude, atmospheric thermodynamic conditions (pressure, temperature, humidity) from various sensors, approximate brightness temperature of the surface and overlying atmosphere, and estimated horizontal winds. A flight flag is included to indicate when the aircraft is in flight. All the data have been synchronized and quality controlled, and are provided at their native frequency logged on board the aircraft’s secure digital (SD) card. Data interpolated to a common 10 hertz (Hz) clock are provided in the B1 level files, and are available in the Arctic Data Center at doi:10.18739/A2Z60C34R. Users are encouraged to primarily use the B1 level data for analysis. More information on the data and methods used for synchronization and quality control can be found in de Boer, G. R. Calmer, G. Jozef, J. Cassano, J. Hamilton, D. Lawrence, S. Borenstein, A. Doddi, C. Cox, J. Schmale, A. Preußer and B. Argrow (2021): Observing the Central Arctic Atmosphere and Surface with University of Colorado Uncrewed Aircraft Systems, Nature Scientific Data, in prep.
DOI: 10.21233/0n51-4d84
title: Bright 1966 Site 1 pollen surface sample dataset

description: Raw data for the Bright 1966 Site 1 pollen surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/n4t9-as33
title: Moss of Achnacree testate amoebae surface sample dataset

description: Raw data for the Moss of Achnacree testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/sz5w-qh52
title: Slieveanorra testate amoebae surface sample dataset

description: Raw data for the Slieveanorra testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/9f2w-2y22
title: Mauntschas testate amoebae surface sample dataset

description: Raw data for the Mauntschas testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/fpp9-b115
title: Makąty testate amoebae surface sample dataset

description: Raw data for the Makąty testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/9kam-nr66
title: Surmene Agacbasi Yaylasi testate amoebae surface sample dataset

description: Raw data for the Surmene Agacbasi Yaylasi testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/nn0n-xq90
title: Mile 137, Deer Creek above falls pollen surface sample dataset

description: Raw data for the Mile 137, Deer Creek above falls pollen surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/rckv-gq20
title: Surmene Agacbasi Yaylasi testate amoebae surface sample dataset

description: Raw data for the Surmene Agacbasi Yaylasi testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/gbfy-px52
title: Cheng Site 29X pollen surface sample dataset

description: Raw data for the Cheng Site 29X pollen surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/2fwt-rr02
title: Chlebowo testate amoebae surface sample dataset

description: Raw data for the Chlebowo testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/r1d3-m848
title: Salmisuo Mire testate amoebae surface sample dataset

description: Raw data for the Salmisuo Mire testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/b24g-3k26
title: South 7 testate amoebae surface sample dataset

description: Raw data for the South 7 testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.18739/a2930nw4f
title: Total Rebound: solid Earth isostatic response to the complete unloading of the Greenland and Antarctic Ice Sheets

description: The land surface beneath the Greenland and Antarctic Ice Sheets is isostatically depressed by the mass of the overlying ice. Here, we use an elastic plate model along with contemporary ice thickness and effective elastic thickness datasets to calculate the fully re-equilibrated flexural response of the solid Earth to the complete removal of the Greenland and Antarctic Ice Sheets. As well as the unloading of the modern ice sheet load, we account for water loading feedbacks and the ongoing rebound due to the remaining isostatic disequilibrium from the Last Glacial Maximum. We provide NetCDF grid files of the total solid Earth surface response. We also quantify the uncertainties in solid surface deformation associated with a suite of elastic and viscoelastic Earth models. The resulting rebound fields have a number of applications for studying regional geodynamics, landscape evolution, cryosphere dynamics and relative sea level change.
DOI: 10.18739/a2599z31n
title: Airborne Laser Altimeter, Global Positioning System (GPS), Inertial Measurement Unit (IMU) and Imagery Campaign of the Surging Negribreen Glacier, Svalbard, in July 2017 and July 2018

description: **Data files are available at: [https://arcticdata.io/data/10.18739/A2QF8JK7T/](https://arcticdata.io/data/10.18739/A2QF8JK7T/)** Negribreen, one of largest glaciers in Svalbard, began surging in 2016 and continues to move at relatively fast speeds through 2021. Negribreen has not surged since 1935-1936 and hence there is no modern study on its surge dynamics. A surge-type glacier cycles quasi-periodically between a long quiescent phase of normal flow and a short surge phase when ice speeds increase by a factor of 10-200 times that of quiescence. The rapid ice-acceleration leads to a viscous cycle of wide spread crevassing, rapid advance, and increased calving that lead to catastrophic ice loss and frontal retreat. During the peak surge period in the 2017, the ice loss from Negribreen is estimated to have contributed 5-1.0% of total annual global sea-level rise. During our project, we collected laser altimeter, Global Positioning System (GPS), Inertial Measurement Unit (IMU), image and video data from small helicopter, to obtain high-resolution elevation data suitable for process studies and to complement satellite data. This data package includes the field data from two of our campaigns in July 2017 (negri\\_2017) and July 2018 (negri\_2018). Within each of these subdirectories, are folders containing each our data sets for the given campaign: (1) The 400 hertz (Hz) raw 905 nanometer (nm) laser altimeter data from LaserTech's Universal laser System (ULS) along with an error logfile (laser), (2) Handheld image data from a Nikon D5100 (D5100), and two Nikon Coolpix cameras (L120-1 and L120-2), (3) 1-Hz GPS data from a simple USB-connected GPS receiver (button\_GPS), (4) 10-Hz raw and processed GPS data from a base (Trimble NetR9) and rover (Septentrio APS-3G) kinematic GPS system borrowed from UNAVCO (gps\_unavco) (2018 only), (5) 1-Hz IMU data from a LORD 3DM-GX5-15 Virtual Reference Unit (imu), (6) 2-Hz imagery from a GoPro Hero-5 mounted on the underside of the helicopter (gopro) (2018 only) and (7) Video data from an Aiptex video camera (video-aiptex) (2017 only). A README file is included at the top of the directory structure that specifies the data format for each data type. Each campaign consisted of two successful flights and each of the data subfolders above contain additional subfolders labeled Flight1 or Flight2. A data set may be missing data for a given flight due to instrument failure (e.g. IMU data for Flight1 in 2017 and GoPro imagery for Flight1 in 2018). We were not able to reach Negribreen during Flight 1 of 2018 due to an approaching storm, so instead we collected data from Hayesbreen and Peterman Glacier, which lie just south of Negribreen, but were not currently surging. Some flights include photographic documentation of Tunabreen and other glaciers along the transit flight to Negribreen.
DOI: 10.18739/a21j97878
title: Ice draft data from a mooring in Hudson Strait from September 2006 to August 2007

description: A mooring deployed in Hudson Strait between Big Island and Wales Island from September 2006 to August 2007 was equipped with an upward looking sonar (ULS) to measure sea ice draft. Hudson Strait is the main pathway of heat, mass, and freshwater exchange between Hudson Bay and the Arctic and North Atlantic Oceans. Hudson Strait inflow affects the physical and biogeochemical cycles and ecosystems of Hudson Bay. The ULS data were processed according to their manufacturer specifications.
DOI: 10.21233/6tfy-0a48
title: Lakkasuo testate amoebae surface sample dataset

description: Raw data for the Lakkasuo testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.18739/a2ws8hn1d
title: Ice draft data from a mooring in Hudson Strait from September 2005 to August 2006

description: A mooring deployed in Hudson Strait between Big Island and Wales Island from September 2005 to August 2006 was equipped with an upward looking sonar (ULS) to measure sea ice draft. Hudson Strait is the main pathway of heat, mass, and freshwater exchange between Hudson Bay and the Arctic and North Atlantic Oceans. Hudson Strait inflow affects the physical and biogeochemical cycles and ecosystems of Hudson Bay. The ULS data were processed according to their manufacturer specifications.
DOI: 10.18739/a2s17st6g
title: Ice draft data from two moorings in Hudson Strait from August 2008 to September 2009

description: Two moorings deployed across Hudson Strait between Big Island and Wales Island from August 2008 to September 2009 were equipped with upward looking sonars (ULS) to measure sea ice draft. Hudson Strait is the main pathway of heat, mass, and freshwater exchange between Hudson Bay and the Arctic and North Atlantic Oceans. Hudson Strait inflow affects the physical and biogeochemical cycles and ecosystems of Hudson Bay. One mooring was deployed near the southern coast to capture sea ice over the outflow. The other mooring was deployed on the northern side to capture the sea ice over the inflow. The ULS data were processed according to their manufacturer specifications.
DOI: 10.21233/cvg4-ep42
title: Wierzchołek testate amoebae surface sample dataset

description: Raw data for the Wierzchołek testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.48704/ird_kin4
title: KIn4
DOI: 10.21233/e9jv-c510
title: Railway testate amoebae surface sample dataset

description: Raw data for the Railway testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/jvhb-zm88
title: Espinosa de Cerrato charcoal dataset

description: Raw data for the Espinosa de Cerrato charcoal dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/3rwj-jk84
title: Saint-Momelin pollen dataset

description: Raw data for the Saint-Momelin pollen dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/3pb2-4576
title: Haskell Lake diatom dataset

description: Raw data for the Haskell Lake diatom dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/jjj7-7k58
title: Jinbei testate amoebae surface sample dataset

description: Raw data for the Jinbei testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/v4gq-9x61
title: Mukhrino testate amoebae surface sample dataset

description: Raw data for the Mukhrino testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/f48f-th33
title: Lake Whalom diatom surface sample dataset

description: Raw data for the Lake Whalom diatom surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/qhbq-m116
title: Biogradsko Forest Hollow #1 paleomagnetic dataset

description: Raw data for the Biogradsko Forest Hollow #1 paleomagnetic dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/n2e4-3t27
title: Urengoi-town testate amoebae surface sample dataset

description: Raw data for the Urengoi-town testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/2b17-7876
title: Squaw Lake pollen surface sample dataset

description: Raw data for the Squaw Lake pollen surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/spav-jq41
title: Huff Pond diatom surface sample dataset

description: Raw data for the Huff Pond diatom surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/e1gp-th58
title: Listvyanka-bog3 testate amoebae surface sample dataset

description: Raw data for the Listvyanka-bog3 testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/52fz-y469
title: Turkey Pond diatom surface sample dataset

description: Raw data for the Turkey Pond diatom surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/77fk-9v02
title: M77/2_056-3 pollen dataset

description: Raw data for the M77/2_056-3 pollen dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/m6t1-ad62
title: Listvyanka-bog3 testate amoebae surface sample dataset

description: Raw data for the Listvyanka-bog3 testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/mjrp-wa49
title: TangbeiB testate amoebae surface sample dataset

description: Raw data for the TangbeiB testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/2359-qf10
title: Queen Lake diatom surface sample dataset

description: Raw data for the Queen Lake diatom surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/7vvr-9p77
title: Hani testate amoebae surface sample dataset

description: Raw data for the Hani testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/k1nw-ms35
title: Payette Lake diatom surface sample dataset

description: Raw data for the Payette Lake diatom surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/3r3n-f824
title: Velsen Gildenlaan pollen dataset

description: Raw data for the Velsen Gildenlaan pollen dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.6084/m9.figshare.8206907
title: Relato I Encontro de Agrofloresta para Mulheres

description: Relato das experiências e aprendizados vivenciados no I Encontro de Agrofloresta para Mulheres <br>Local: Sítio Selva e Paz, cidade de Piraí do Norte - Bahia<br>Dias 24, 25 e 26 de maio de 2019<br>O Encontro foi organizado pelo MAIS e facilitado por Gudrun Götsch. Em anexo, está o arquivo intitulado:<br>- Relato I Encontro Agrofloresta Mulheres_Roberta Schardong_mai.2019<br>O relato resume e sistematiza as experiências e aprendizados durante o encontro e também os momentos especiais que o lugar proporciona. <br>Também estão, em anexo, as filmagens realizadas durante o Encontro por participantes que, gentilmente, compartilharam.<br>No dia 27 de maio, período da manhã, foi realizada visita à propriedade de Ernst Götsch que mostrou os estratos no ambiente de plantio de cacau e explicou a importância fundamental da criação de processos na agricultura sintópica. O momento foi filmado e os vídeos estão acima.
DOI: 10.21233/ep1t-p985
title: Bakchar mire testate amoebae surface sample dataset

description: Raw data for the Bakchar mire testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/07gd-9a67
title: TangbeiB testate amoebae surface sample dataset

description: Raw data for the TangbeiB testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/rd0c-a790
title: Bakchar mire2 testate amoebae surface sample dataset

description: Raw data for the Bakchar mire2 testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/ks5c-jb13
title: Listvyanka-bog4 testate amoebae surface sample dataset

description: Raw data for the Listvyanka-bog4 testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/qzwk-fd28
title: Gutian testate amoebae surface sample dataset

description: Raw data for the Gutian testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/44qf-kq73
title: Sandaohu testate amoebae surface sample dataset

description: Raw data for the Sandaohu testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/rrdm-bn33
title: Bakchar mire testate amoebae surface sample dataset

description: Raw data for the Bakchar mire testate amoebae surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/fc15-sy24
title: Armeña pollen dataset

description: Raw data for the Armeña pollen dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.5281/zenodo.6378876
title: Revisiting reopened bugs in open source software systems

description: Reopened bugs can degrade the overall quality of a software system since they require unnecessary rework by developers. Moreover, reopened bugs also lead to a loss of trust in the end-users regarding the quality of the software. Thus, predicting bugs that might be reopened could be extremely helpful for software developers to avoid rework. Prior studies on reopened bug prediction focus only on three open source projects (i.e., Apache, Eclipse, and OpenOffice) to generate insights. We observe that one out of the three projects (i.e., Apache) has a data leak issue -- the bug status of \textit{reopened} was included as training data to predict reopened bugs. In addition, prior studies used an outdated prediction model pipeline (i.e., with old techniques for constructing a prediction model) to predict reopened bugs. Therefore, we revisit the reopened bugs study on a large scale dataset consisting of 47 projects tracked by JIRA using the modern techniques such as SMOTE, permutation importance together with 7 different machine learning models. We study the reopened bugs using a mixed methods approach (i.e., both quantitative and qualitative study). We find that: 1) After using an updated reopened bug prediction model pipeline, only 34\% projects give an acceptable performance with AUC $\geqslant$ 0.7. 2) There are four major reasons for a bug getting reopened, that is, technical (i.e., patch/integration issues), documentation, human (i.e., due to incorrect bug assessment), and reasons not shown in the bug reports. 3) In projects with an acceptable AUC, 94\% of the reopened bugs are due to patch issues (i.e., the usage of an incorrect patch) identified before bug reopening. Our study revisits reopened bugs and provides new insights into developer's bug reopening activities.<br>