Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
9
datasets available to search
ShareScore release 0.9.0
Dataset results
9 results for “Interlaboratory study”
Interlaboratory study: Testing reproducibility of solid biofuels component identification using reflected light microscopy
<p><strong>Submitted data was used to write an article: </strong>Drobniak, A., Mastalerz, M., Jelonek, Z., Jelonek, I., Adsul, T., Andolšek, N., Ardakani, O.H., Congo, T., Demberelsuren, B., Donohoe, B.S., Douds, A., Flores, D., Ganzorig, R., Ghosh, S., Gize, A., Goncalves, P.A., Hackely, P., Hatcherian, J., Hower, J.C., Kalaitzidis, S., Kędzior, S., Knowles, W., Kuś, J., Lis, K., Lis, G., Liu, B., Luo, Q., Du, M., Mishra, D., Misz-Kennan, M., Mugerwa, T., O'Keefe, J., Park, J., Pearson, R., Petersen, H., Reyes, J., Ribeiro, J., Niedzwiedzkas, J.L., de la Rosa Rodriguez, G., Sosnowski, P., Valentine, B., Varma, A., Wojtaszek-Kalaitzidi, M., Xu, Z., Zdravkov, A., Ziemianin, K., Interlaboratory study: Testing reproducibility of biomass fuels component identification using reflected light microscopy. International Journal of Coal Geology 277, 104331. <a href="https://doi.org/10.1016/j.coal.2023.104331">https://doi.org/10.1016/j.coal.2023.104331</a>.</p> <p> </p> <p><strong>Funding acknowledgments: </strong>The project is co-financed by the Polish National Agency for Academic Exchange within the Polish Returns Programme (BPN/PPO/2021/1/00005/DEC/1), the National Science Center, Poland (2022/01/1/ST10/00024), and the research activities co-financed by the funds granted under the Research Excellence Initiative of the University of Silesia in Katowice, Poland. </p> <p> </p> <p><strong>Article Abstract: </strong>Considering global market trends and concerns about climate change and sustainability, increased biomass use for energy is expected to continue. As more diverse materials are being utilized to manufacture solid biomass fuels, it is critical to implement quality assessment methods to analyze these fuels thoroughly. One such method is reflected light microscopy (RLM), which has the potential to complement and enhance current standard testing, leading to improving fuel quality assessment and, ultimately, preventing avoidable air pollution. An interlaboratory study (ILS) was conducted to test the reproducibility of biomass fuels component identification using a reflected light microscopy technique. The exercise was conducted on thirty photomicrographs showing biomass and various undesired components (like plastics or mineral matter), which were purposely added (by the ILS organizers) to contaminate wood pellets and charcoal-based grilling fuels. Forty-six participants had various levels of difficulty identifying the marked components, and as a result, the percentage of correct answers ranged from 52.2 to 94.4%. Among the most difficult components to distinguish were petroleum products and inorganic matter. Various reasons led to the misidentification, including insufficient morphological descriptions of the components provided to participants, ambiguities of the nomenclature, limitations of the analytical and exercise method, and insufficient experience of the participants. Overall, the results indicate that RLM has the potential to enhance the quality assessment of biomass fuels. However, they also demonstrate that the petrographic classification used in this exercise requires further refinement before it can be standardized. While a new simplified classification of solid biomass fuels components was created as an outcome of this study, future research is necessary to refine the nomenclature, develop a microscopic morphological description of the components, and verify the accuracy of component identification with a follow-up ILS.</p>
Interlaboratory study for the evaluation of three microtiter plate-based biofilm quantification methods
<p>Data collected in the Print-aid interlaboratory study (ring trial) to evaluate the repeatability and reproducibility of three microtiter plate based methods: crystal violet, resazurin and plate counts. The files contain all the raw data collected for each laboratory as well as the tranformed data. Analysis and protocol details can be found in the following publication https://www.nature.com/articles/s41598-021-93115-w </p>
PQRI Elemental Impurity Interlaboratory Study Raw Data
<p>The pharmaceutical industry recently implemented a new paradign in drug product elemental impurity (EI) analysis in ICH Q3D Guidelines and USP General Chapters <232> and <233>, which allow for EI analysis by inductively coupled plasma-mass spectrometry (ICP-MS) and similar techniques. To date, there have been few systematic evaluations of laboratory performance on EI analysis in drug products due to a lack of standardized samples and ongoing efforts to adopt best practices. We organized an interlaboratory study to provide a data-driven way to address key technical challenges faced by laboratories during the implementation of EI regulations, including laboratory equipment, interference correction strategies, and the method of calculating the final concentrations.</p> <p>The data contained in this file includes the analytical results and characteristics for all participant laboratories in a format readable and analyzable by R. A manuscript describing the analysis of this data is in preparation, with a target submission date of October 2021.</p>
Data of the characterisation of conventional 87Sr/86Sr isotope ratios in cement, limestone and slate reference materials based on an interlaboratory comparison study
<p>This dataset represents the electronic supplementary material (ESM) of the publication entitled "Characterisation of conventional <sup>87</sup>Sr/<sup>86</sup>Sr isotope ratios in cement, limestone and slate reference materials based on an interlaboratory comparison study", which is published in Geostandards and Geoanalytical Research under the DOI: 10.1111/GGR.12517. It consists of four files. 'ESM_Data.xlsx' contains all reported data of the participants, a description of the applied analytical procedures, basic calculations, the consensus values, and part of the uncertainty assessment. 'ESM_Figure-S1' displays a schematic on how measurements, sequences and replicates are treated for the uncertainty calculation carried out by PTB. 'ESM_Technical-protocol.pdf' is the technical protocol of the interlaboratory comparison, which has been provided to all participants together with the samples and which contains bedside others the definition of the measurand and guidelines for data assessment and calculations. 'ESM_Reporting-template.xlsx' is the Excel template which has been submitted to all participants for reporting their results within the interlaboratory comparison. Excel files with names of the the structure 'GeoReM_Material_Sr8786_Date.xlsx' represent the <em>R</em><sub>con</sub>(<sup>87</sup>Sr/<sup>86</sup>Sr) data for a specific reference material downloaded from GeoReM at the specified date, e.g. 'GeoReM_IAPSO_Sr8786_20221115.xlsx' contains all <em>R</em><sub>con</sub>(<sup>87</sup>Sr/<sup>86</sup>Sr) data for the IAPSO seawater standard listed in GeoReM until 15 November 2022.</p>
Database of the RILEM TC 304-ADC interlaboratory study on mechanical properties of 3D printed concrete (ILS-mech)
<p>The RILEM TC 304-ADC has set up a large interlaboratory study on the mechanical properties of 3D printed concrete (ILS-mech). The study was prepared in 2022 by a preparation group leading to a Study Plan which the TC approved on 29 November 2022 (<a href="https://doi.org/10.14459/2023mp1705940">https://doi.org/10.14459/2023mp1705940</a>). The ILS-mech was performed in 2023. The data was collected using a pre-prepared spreadsheet template. For data management, a database was derived and set-up in openBIS. The underlying Postgres database of openBIS was exported to the here-published SQLite database for sharing without maintaining a server. The structure of the database is described in (<a href="https://doi.org/10.1617/s11527-025-02650-9">https://doi.org/10.1617/s11527-025-02650-9</a>). The results are discussed in three associated papers focusing on the overall outcomes and evaluation of the procedures (<a href="https://doi.org/10.1617/s11527-025-02686-x">https://doi.org/10.1617/s11527-025-02686-x</a>), the compressive test results (<a href="https://doi.org/10.1617/s11527-025-02688-9">https://doi.org/10.1617/s11527-025-02688-9</a>), and the tensile test results (<a href="https://doi.org/10.1617/s11527-025-02687-w">https://doi.org/10.1617/s11527-025-02687-w</a>).</p> <p>contact via freek.bos@tum.de</p>
Dataset for Surface Enhanced Raman Spectroscopy for quantitative analysis: results of a large-scale European multi-instrument interlaboratory study
<p>This dataset contains all the spectra used in "Surface Enhanced Raman Spectroscopy for quantitative analysis: results of a large-scale European multi-instrument interlaboratory study". Data are available in 2 different formats:</p> <p>- a compressed archive with 1 folder ("Dataset”) cointaining all the 3516 TXT files (1 file = 1 spectrum) uploaded by all participants (all spectra of the Interlaboratory study);</p> <p>- 1 single CSV file (“ILSspectra.csv”) with all the 3516 spectra uploaded by all participants in the form of a table. The data are structured as follow, with each row being 1 spectrum, preceded by metadata: "labcode", "substrate", "laser", "method", "sample", "type", "conc", "batch", "replica". Note that for those spectra starting after 400 cm-1 and/or ending before 2000 cm-1 missing values were expressed as NAs.</p>
Interlaboratory study to determine the reproducibility of toxicogenomics datasets
GEO Series GSE25936. Homo sapiens. 24 samples. Type: Expression profiling by array.
caArray_dobbi-00100: Interlaboratory comparability study of cancer gene expression analysis using oligonucleotide microarrays
GEO Series GSE68606. Homo sapiens. 137 samples. Type: Expression profiling by array.
REPARES interlaboratory study (ring test) on qPCR quantification of antibiotic resistance genes and other related genes in DNA isolated from sewage sludge and wastewater
<p>This dataset collects data on interlaboratory study (Ring test), performed within project REPARES in two phases (Ring test phase 1, Ring test phase 2). Sampling and analyses for phase 1 started on 25.2.2020 and for phase 2 on 27.9.2021. The sampling site was a wastewater treatment plant (> 100 000 inhabitants) in the Czech Republic.</p> <p>REPARES: Research platform on antibiotic resistance spread through wastewater treatment plants</p> <p>H2020-EU.4.b. ID 857552</p> <p>https://repares.vscht.cz/</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.