Statistics from all data on this dataverse

The Dodd-Frank Act imposes reporting requirements on US companies regarding supply chain links to conflict minerals. Previous research uses within-DRC (Democratic Republic of Congo) variation in the location of mineral mines to identify the Act’s effect on conflict. Due to the presence of spillovers, these previous studies may underestimate the effect. Moreover, the Act regulates reporting on minerals mined in the DRC and all surrounding countries. To fully evaluate this legislation, I estimate the effect on the prevalence of conflict events in the DRC and all covered countries. Difference-in differences estimates suggest that the unintended consequences of this legislation within the DRC are larger than previously reported and that there is no evidence of any effect within all covered countries pooled together. Supplemental analyses (i) investigate possible mechanisms that drive these results and (ii) find that suspending enforcement of the legislation is unlikely to reduce conflict in the DRC.

2025 HOBO data. Visit https://dataone.org/datasets/sha256%3Ad7cfc770e2d852452afe4b92adce2d63b7bcdef4b746e1a01627c3313e900215 for complete metadata about this dataset.

The database contains biological and ecological data from freshwater fish collected from 16 lake localities situated on the Finnmarksvidda highland plateau from 2005 to 2009. Fish sampling was carried out after standard protocols using multimesh gillnets in littoral, pelagic and profundal habitats. Parameters include species, morphotype of whitefish, habitat, length, weight, age, sex, maturation, parasite infection, diet, stable isotopes (including from invertebrates). The prime focus is on European whitefish (Coregonus lavaretus), the dominant fish species of most lakes, but samples have also been retreived from other species.

Ever need to help a researcher share and archive their research data? Would you know how to advise them on managing their data so it can be easily shared and re-used? This workshop will cover best practices for collecting and organizing research data related to the goal of data preservation and sharing. We will focus on best practices and tips for collecting data, including file naming, documentation/metadata, quality control, and versioning, as well as access and control/security, backup and storage, and licensing. We will discuss the library’s role in data management, and the opportunities and challenges around supporting data sharing efforts. Through case studies we will explore a typical research data scenario and propose solutions and services by the library and institutional partners. Finally, we discuss methods to stay up to date with data management related topics.

Data Documentation and Metadata session from the 2015 Virginia Data Management Bootcamp. Introduces non-structural (data dictionaries, read me files, code books) and structured ways (XML schemas) to document research data.

Data from lake sediment core scanning (optical, MS, X-ray, XRF) and AMS radiocarbon dating result certificates. Analysed in: Korsgaard et al.: Evidence of middle Holocene landslide-generated tsunamis recorded in lake sediments from Saqqaq, West Greenland, Natural Hazards and Earth Systems Science, 2024.

This is gravimetric and radiometric data for sediment cores collected in 2015 at Wax Lake Delta, USA

This dataset includes all biomarker (alkenone saturation – UK37, and alkane distribution) and geochemical (XRF – log(Br/Ti)) data presented in van der Bilt et al. 2025 – published in Nature Communications. The data derive from a lake sediment record from Svalbard – core HAP0212 (79 °N, 11 °E) – and were generated using gas chromatography (GC: alkenone and alkane data) and X-Ray Fluorescence (XRF) core scanning (log(Br/Ti)) at the geochemistry facility of the Lamont Doherty Earth Observatory (LDEO) and the EARTHLAB sediment facility at the University of Bergen (UiB), respectively. All of the provided data are shown in Figs. 2, 3, 4, and 5 of the paper. Additional details are found in the readme file.

Description: Greenland-wide dataset showing water level changes of 1,152 ice-marginal lakes from February 2003 to April 2023. The data is provided as a point shapefile and contains lake-specific characteristics, including: i) Lake ID, ii) estimated maximum and minimum water levels, and water level difference (dWL), iii) number of altimetry observations. Additionally, for all lakes experiencing glacial lake outburst floods (GLOFs), the dataset also includes: i) drainage year(s), ii) pre- and post-drainage water levels, iii) largest GLOF. Method: We use airborne and satellite altimetry observations from ATM, ICESat, and ICESat-2 to estimate water level changes of ice-marginal lakes (IMLs) in Greenland from February 2003 to April 2023. We utilize lake outlines from the mapping of Greenland conducted by The Danish Agency for Data Supply and Infrastructure (https://dataforsyningen.dk/data/4771) to spatially filter the altimetry observations. For each IML, we apply statistical filtering to remove outlying observations and subsequently calculate the maximum water level difference (dWL). All lakes with a dWL > 4m (n = 465) are manually inspected for GLOF behavior. For a complete description of the data processing, please refer to the corresponding paper: Dømgaard et al., 2024 (DOI: 10.1038/s43247-024-01522-4), Altimetry-based ice-marginal lake water level changes in Greenland

Source data and code share for Ribeiro et al. 2021 "Vulnerability of the North Water ecosystem to climate change", Nature Comunications 12: 4475

MEASURE Evaluation was contracted to conduct a performance evaluation of the Tibu Homa Project, which was implemented in the Lake Zone of Tanzania between March 2011–September 2015. The evaluation used a retrospective, mixed-methods approach. Data sources included a cross-sectional quantitative health facility survey, with both a facility checklist and observational data of health facility visits for children under five years old. Primary outcomes of the evaluation were indicators of quality of care, which are defined by the WHO Health Facility Survey (HFS) and include the Index of Integrated Assessment; correct classification; and correct treatment of cases observed or reviewed in patient records.

Replication Data for: Discovery of signatures of fatal neonatal illness in vital signs using highly comparative time-series analysis

NetCDF formatted output data from the TRAMS model simulations described in "Rafkin and Soto, 2020:Air-Sea Interactions on Titan: Lake Evaporation, Atmospheric Circulation, and Cloud Formation, Icarus".