cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48443/fdfd-d514
title: Chemical properties of surface water (DP1.20093.001)
title: RELEASE-2024

description: This data product contains the quality-controlled, native sampling resolution data from NEON's surface water chemistry sampling protocol. Subsamples are analyzed at NEON domain headquarters for alkalinity and acid neutralizing capacity (ANC); other subsamples are sent to external facilities for a broad suite of analytes, including dissolved and total nutrients and carbon, cations and anions, and general chemistry. For additional details, see the user guide, protocols, and science design listed in the Documentation section in this data product's details webpage.

Latency:
The expected time from data and/or sample collection in the field to data publication is as follows, for each of the data tables (in days) in the downloaded data package. See the Data Product User Guide for more information.

swc_domainLabData: 60

swc_externalLabData: 150

swc_fieldData: 30

swc_fieldSuperParent: 30

swc_externalLabSummaryData: 14
description: Grab samples of surface water at NEON aquatic sites are collected in streams and rivers 15- 26 times per year and 12 times per year in lakes. In streams and rivers, 12 samples are collected at regular intervals during the sampling season while the remaining 14 are collected on an irregular basis to capture major flow events. In lakes samples are collected approximately monthly and to capture ice-on and ice-off events. The field protocol used by NEON for collecting surface water chemistry samples follows the general requirements set forth by the 2011 USGS National Water-Quality Assessment (NAWQA) Program and the Arctic LTER standard operating procedures (SOP). Sample handling and preparation portions of this protocol follow the general requirements set forth by the USGS National Water-Quality Assessment (NAWQA) Program (USGS 2006). Instrumentation:
DOI: 10.48443/vdp2-fc93
title: Coarse downed wood bulk density sampling (DP1.10014.001)
title: RELEASE-2024

description: The Coarse Downed Wood bulk density sampling data product contains the quality-controlled, native sampling resolution volume, mass and calculated bulk density data from cross-sectional disks cut from downed logs at each of NEON's terrestrial sites at which qualifying logs are present. Disks are preferentially collected from logs that fall into the most abundant 'decayClass x sizeCategory x taxonID' combinations, as informed by the Coarse Downed Wood survey data product. In addition to bulk density from each collected disk, log-level decay, size category and taxonID information is also recorded for each log from which disks are sampled. Data are reported per disk per log, and when multiple disks are collected from the same log, multiple records will exist in the data. Logs are typically associated with a plotID, and disks may also be collected from logs that fall outside of NEON plots. For additional details, see the user guide, protocols, and science design listed in the Documentation section in this data product's details webpage.

Latency:
The expected time from data and/or sample collection in the field to data publication is as follows, for each of the data tables (in days) in the downloaded data package. See the Data Product User Guide for more information.

cdw_densitydisk: 105

cdw_densitylog: 105

cdw_identificationHistory: 7
description: Coarse Downed Wood bulk density samples are collected from terrestrial sites with qualifying logs where repeat CDW Survey sampling is performed. CDW Bulk Density sampling is implemented twice per site, the first time within the first three years of data collection at a site, and the second time 5-6 years after the first sampling event. When possible, the same logs are targeted for sampling at both sampling time points. Sampling may occur in up to 20 Distributed Plots and all Tower Plots, and unlike all other NEON TOS sampling, collection of disks may also occur outside of NEON plot boundaries, due to the sparsely distributed nature of target logs. Logs sampled for bulk density are parsed into five decay categories that broadly match existing USFS definitions, three size categories (2-5 cm, 5-10 cm, and greater than 10 cm diameter), and are identified to the highest taxonomic resolution possible according to the USDA Plants database. The bulk density sampling effort is inherently variable from site to site, as it is driven by the number of 'decayClass x sizeCategory x taxonID' (DST) combinations, which is strongly dependent on site-level tree diversity. For each site, sampling is considered complete once all rank-ordered DSTs that cumulatively make up 80% of the total tallies have been sampled. Target disk sample size per DST is n=10 for DSTs &gt;= 10 cm diameter, and n=5 for DSTs &lt; 10 cm diameter. Instrumentation:
DOI: 10.5281/zenodo.10580316
title: THE ESSENCE AND NECESSITY OF START UP PROJECTS
DOI: 10.5281/zenodo.10580317
title: THE ESSENCE AND NECESSITY OF START UP PROJECTS
DOI: 10.6084/m9.figshare.24881472
title: Srour et al_Exploring the Potential of Roadside Plantation for Carbon Sequestration Using Simulation in Southern Quebec, Canada

description: Data for the article Exploring the Potential of Roadside Plantation for Carbon Sequestration Using Simulation in Southern Quebec, Canada. Submitted to the journal Forests in December 2023.
DOI: 10.6084/m9.figshare.24881472.v1
title: Srour et al_Exploring the potential of roadside afforestation for carbon sequestration: A comparison of simulated plantations with natural vegetation in southern Quebec, Canada.

description: Data for the article Exploring the potential of roadside afforestation for carbon sequestration: A comparison of simulated plantations with natural vegetation in southern Quebec, Canada. Submitted to the journal Forests in December 2023.
DOI: 10.6084/m9.figshare.24881472.v2
title: Srour et al_Exploring the Potential of Roadside Plantation for Carbon Sequestration Using Simulation in Southern Quebec, Canada

description: Data for the article Exploring the Potential of Roadside Plantation for Carbon Sequestration Using Simulation in Southern Quebec, Canada. Submitted to the journal Forests in December 2023.
DOI: 10.48443/depk-z490
title: Coarse downed wood log survey (DP1.10010.001)
title: RELEASE-2024

description: The Coarse Downed Wood log survey data product contains the quality-controlled, native sampling resolution data from in-situ tallies and measurements of downed logs from each of NEON's terrestrial sites at which qualifying logs are present. Qualifying logs are tallied within each plot according to the Line Intercept Distance Sampling (LIDS) method, and additional diameter, length and decay class characteristics are measured for each tallied log. Data are reported per log per plot, and when forked logs are tallied, additional diameter data are reported for each qualifying log fork. For additional details, see the user guide, protocols, and science design listed in the Documentation section in this data product's details webpage.

Latency:
The expected time from data and/or sample collection in the field to data publication is as follows, for each of the data tables (in days) in the downloaded data package. See the Data Product User Guide for more information.

cdw_fieldtally: 30

cdw_tally_identificationHistory: 7
description: Coarse Downed Wood tallies are performed at least once at all sites at which logs greater than or equal to 2 cm diameter exist. Additional surveys are performed at 5 year intervals at each site if initial LIDS estimates of CDW volume are non-zero. Sampling occurs in n=20 randomly selected Distributed Plots at the site scale, and also in Tower Plots established within the airshed of the NEON Tower. Within each plot, 3 randomly oriented transects are established, and transect lengths vary dynamically by site according to F-values selected to enable tallying of 7-10 qualifying logs per plot. Tallied logs are parsed into three size categories (2-5 cm, 5-10 cm, and greater than 10 cm diameter), five decay categories that are broadly matchable to existing USFS definitions, and are identified to the highest taxonomic resolution possible according to the USDA Plants database. Instrumentation:
DOI: 10.48443/pz65-4645
title: Continuous discharge (DP4.00130.001)
title: RELEASE-2024

description: This data product describes the volume of water flowing through a stream or river cross-section during a given period of time. For each NEON stream or river site, site-specific stage-discharge rating curve equations are derived from point observations of gauge height and discharge. Continuous sensor measurements of surface water pressure are used to derive water column height. The rating curve equations are applied to water column height to derive continuous stream discharge.

Latency:
Data collected in any given month are published during the second full week of the following month.
description: NEON calculates continuous stream discharge in all rivers and wadeable stream sites within the Observatory. Stream discharge data are calculated using pressure of surface water L0 data (DP0.20016; the raw, level 0 inputs used to calculate Elevation of surface water, DP1.20016), stream discharge rating curve data (DP4.00133), gauge height data (DP1.20267.001) and geolocation information. Continuous discharge data are reported once per minute. Instrumentation: Level TROLL 500
DOI: 10.48443/vct8-pr05
title: Depth profile at specific depths (DP1.20254.001)
title: RELEASE-2024

description: This data product contains the quality-controlled, native sampling resolution data from NEON's Depth profile at specific depths data collection. Depth profile data are collected along with any other sampling protocol in the water column (e.g., phytoplankton, zooplankton, or surface water chemistry). Depth profile data include water temperature, conductivity, and dissolved oxygen data collected every 0.5 m through the water column using a handheld probe. Depth profile data are only collected at the deepest location of the lake near the buoy, or near the river buoy. These data not only provide metadata to accompany the sampling modules, but also inform sampling depths based the thermocline, if present, for water chemistry and associated analytes, surface water microbes, and phytoplankton sampling. Depth profiles are collected year-round, including under ice at northern sites, a minimum of 12 times per year. For additional details, see the user guide, protocols, and science design listed in the Documentation section in this data product's details webpage.

Latency:
The expected time from data and/or sample collection in the field to data publication is as follows, for each of the data tables (in days) in the downloaded data package. See the Data Product User Guide for more information.

dep_profileData: 30

dep_profileHeader: 30
description: Depth profile data are collected during sample collection for any protocol that samples the water column in a lake or river (phytoplankton, zooplankton, pelagic surface water microbes, and pelagic surface water chemistry), and may be collected opportunistically during other sampling visits to lake and river sites. Measurements are collected only near the buoy sensors in lakes and rivers, and data are collected year-round, including under ice. Measurements of water temperature, conductivity, and dissolved oxygen are collected every 0.5 m through the water column, with larger intervals (1.0 m) in the hypolimnion of deep lakes. Data are collected a minimum of 12 times per year. Instrumentation: YSI Pro2030
DOI: 10.5066/p9e3jnpi
title: USGS National and Global Oil and Gas Assessment Project—West-Central Coastal Province (Africa) Presalt: Assessment Unit Boundaries, Assessment Input data, and Fact Sheet Data Tables

description: This data release contains the boundaries of assessment units, assessment input data, and resulting fact sheet data tables for the assessment of undiscovered oil and gas resources in the presalt reservoirs of the West-Central Coastal Province of Africa. The Assessment Unit is the fundamental unit used in the National and Global Oil and Gas Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is defined within the context of the higher-level Total Petroleum System. The Assessment Unit is shown herein as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as source rock, timing, migration pathways, trapping mechanism, and hydrocarbon type. The Assessment Unit boundary is defined geologically as the limits of the geologic elements that define the Assessment Unit, such as limits of reservoir rock, geologic structures, source rock, and seal lithologies. Machine-readable tables are provided that contain the input and results for each assessment unit summarized in the USGS Fact Sheet. Methodology of assessments are documented in USGS Data Series 547 for continuous assessments (https://pubs.usgs.gov/ds/547) and USGS DDS69-D, Chapter 21 for conventional assessments (https://pubs.usgs.gov/dds/dds-069/dds-069-d/REPORTS/69_D_CH_21.pdf). See supplemental information for a detailed list of files included this data release.
DOI: 10.48443/jbb9-2t38
title: Digital hemispheric photos of plot vegetation (DP1.10017.001)
title: RELEASE-2024

description: This data product contains the quality-controlled, native sampling resolution field data and 180 degree hemispherical images that enable ground-based calculation of Leaf Area Index (LAI) and/or Plant Area Index (PAI). For forests, both upward-facing photos of canopy vegetation, and photos of understory vegetation are collected. For shorter-stature ecosystems, only downward-facing images of 'understory' vegetation are collected, where 'understory' is defined to include all vegetation. Photos are acquired with a full-frame DSLR camera equipped with a fisheye lens, and are provided in RAW image format. For additional details, see the user guide, protocols, and science design listed in the Documentation section in this data product's details webpage.

Latency:
The expected time from data and/or sample collection in the field to data publication is as follows, for each of the data tables (in days) in the downloaded data package. See the Data Product User Guide for more information.

dhp_perimagefile: 60

dhp_perplot: 60
description: Digital Hemispheric Photos (DHPs) of plot vegetation are collected every five years from twenty randomly selected Distributed Plots, and collection from these plots is timed such that DHPs are acquired within a one month window that also includes a NEON AOP remote-sensing flight over the site. Ground collection of DHPs and the AOP flight are both timed to co-occur with the window of peak greenness according to a 10 year average of the MODIS-EVI greenness index. To better frame the window of peak green in a given year, DHPs are also collected from three Tower Plots on a two week interval, from leaf-out to senescence. Within each plot, photo points are arranged according to the shape of a square cross, oriented in alignment with the cardinal axes, and with points spaced every 4 meters. At each photo point within the plot, photos of understory vegetation are acquired, with 'understory' defined as vegetation typically less than 2 meters height. In grasslands and scrublands, the understory is therefore the only vegetation photographed. When an overstory is present, i.e. vegetation greater than 2 meters height, photographs of overstory are also acquired at each photo point. Overstory images are typically acquired in the crepuscular hours of the day, when direct sunlight is not illuminating the foliage, and may also be acquired when it is overcast such that the sun does not cast a shadow. Understory images are typically acquired during daylight hours. Instrumentation: Full-frame Nikon DSLR (D750/D800/D810 model) equipped with a 16 mm Nikkor full-frame fisheye lens
DOI: 10.25810/k55w-7a04.69
title: World Radio Coverage of Climate Change or Global Warming, 2000-2023 - December 2023

description: The Media and Climate Change Observatory Data monitors 130 sources (across newspapers, radio and TV) in 59 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.5281/zenodo.10211522
title: Generativity and Profitability on B2B Innovation Platforms: A Simulation-based Theory Development

description: This registry includes three documents with helpful information about our simulation model and the data it generates:



Pseudocode: This document displays the pseudocode of our simulation model.

Data: In this document, you will find all the data generated from 264,600 simulation runs (see Table 2 in the paper). The data is created using the model's baseline values for all its components (see the third column in Appendix A of the paper).

Sensitivity Analysis: This document provides the generated data for sensitivity analysis, including all the tested values for the model's components (see the fourth column in Appendix A of the paper). Unlike the Data file (see Table 2 in the paper), in the Sensitivity Analysis, we only tested specific values of experimentally manipulated variables to avoid computational burdens for the simulation.



We tested low (= 5), medium (= 11), and high (= 16) levels of complexity of market opportunities (CMO).

We tested production mechanisms (TM) and transaction mechanisms (TM) from 0.1 to 0.9 in intervals of 0.1.




NOTE: Transparency materials are provided for the benefit of readers. MISQ’s responsibilities are limited to ensuring that the minimum materials required for transparency are provided and that the materials are organized and presented in a high-quality manner (see: https://misq.umn.edu/research-transparency). The materials are not subject to peer review and MISQ bears no responsibility for their use.
DOI: 10.5281/zenodo.10211523
title: Generativity and Profitability on B2B Innovation Platforms: A Simulation-based Theory Development

description: This registry includes three documents with helpful information about our simulation model and the data it generates:



Pseudocode: This document displays the pseudocode of our simulation model.

Data: In this document, you will find all the data generated from 264,600 simulation runs (see Table 2 in the paper). The data is created using the model's baseline values for all its components (see the third column in Appendix A of the paper).

Sensitivity Analysis: This document provides the generated data for sensitivity analysis, including all the tested values for the model's components (see the fourth column in Appendix A of the paper). Unlike the Data file (see Table 2 in the paper), in the Sensitivity Analysis, we only tested specific values of experimentally manipulated variables to avoid computational burdens for the simulation.



We tested low (= 5), medium (= 11), and high (= 16) levels of complexity of market opportunities (CMO).

We tested production mechanisms (TM) and transaction mechanisms (TM) from 0.1 to 0.9 in intervals of 0.1.




NOTE: Transparency materials are provided for the benefit of readers. MISQ’s responsibilities are limited to ensuring that the minimum materials required for transparency are provided and that the materials are organized and presented in a high-quality manner (see: https://misq.umn.edu/research-transparency). The materials are not subject to peer review and MISQ bears no responsibility for their use.
DOI: 10.48443/69rp-5y44
title: Dissolved gases in surface water (DP1.20097.001)
title: RELEASE-2024

description: This data product contains the quality-controlled, native sampling resolution data from NEON's surface water dissolved gas sampling protocol. Water samples are equilibrated with air in the field. Samples of reference air (pre-equilibration) and equilibrated air (post-equilibration) are sent to external facilities for analysis to determine carbon dioxide, methane, and nitrous oxide concentrations in the gas samples. Data users should refer to the user guide for dissolved gases in surface water ([`NEON_dissolvGasInWater_UserGuide`](http://data.neonscience.org/api/v0/documents/NEON_dissolvGasInWater_userGuide_vA)) for suggestions on how to calculate dissolved concentrations of carbon dioxide, methane, and nitrous oxide in the surface waters from which samples were collected using Henry's Law and mass balance equations. For additional details, see the user guide, protocols, and science design listed in the Documentation section in this data product's details webpage.

Latency:
The expected time from data and/or sample collection in the field to data publication is as follows, for each of the data tables (in days) in the downloaded data package. See the Data Product User Guide for more information.

sdg_externalLabData: 120

sdg_externalLabSummaryData: 14

sdg_fieldData: 30

sdg_fieldDataAir: 30

sdg_fieldDataProc: 30

sdg_fieldSuperParent: 30
description: The dissolved gas sampling protocol is completed in conjunction with the water chemistry and aquatic stable isotope protocol. Grab samples of surface water at NEON aquatic sites are collected in streams 26 times per year and 12 times per year in lakes. In streams, 12 samples are collected at regular intervals during the sampling season, while the remaining 14 are collected on an irregular basis to capture major flow events. In lakes, samples are collected approximately monthly and to capture ice-on and ice-off events. For more information see [NEON.DOC.001199](http://data.neonscience.org/api/v0/documents/NEON.DOC.001199vK). Instrumentation:
DOI: 10.48443/9x25-d396
title: Dust and particulate size distribution (DP1.00017.001)
title: RELEASE-2024

description: By deploying optical particulate matter analyzers at a total of 6 sites across three Domains (10, 13, and 15) NEON’s aim is to help the scientific community gain insight on the regional dust transport across the Rocky Mountain region. Aerosol dust can be composed of numerous inorganic and organic elements; everything from biological components such as pollen to the byproducts of incomplete combustion.

Latency:
Data collected in any given month are published during the second full week of the following month.
description: The particulate size analyzer has two main components, the DustTrak sensor (TSI DustTrak 8533EP) and its supporting infrastructure, which shelters the sensor from the environment, and provides an flow rate for the sampler that complies with EPA recommendations. Instrumentation: TSI DustTrak model: 8533EP
DOI: 10.6084/m9.figshare.25103003.v2
title: DLBCL transcriptomics data

description: Transcriptomics dataset of 344 formalin-fixed paraffin-embedded (FFPE) tissue samples from patients with Diffuse large B-cell lymphoma (DLBCL). Gene Expression profiles of 145 target genes was done using the NanoString nCounter technology (NanoString Technologies, Seattle, WA). For details see:Staiger, A.M., Altenbuchinger, M., Ziepert, M. <i>et al.</i> A novel lymphoma-associated macrophage interaction signature (LAMIS) provides robust risk prognostication in diffuse large B-cell lymphoma clinical trial cohorts of the DSHNHL. <i>Leukemia</i> <b>34</b>, 543–552 (2020). https://doi.org/10.1038/s41375-019-0573-y