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Label system, dictionaries, and audit evidence for harmonised over 133,000 feedstock items across major conversion technologies
No full textThis repository provides a large-scale, reproducibly labeled dataset of feedstock terms reported in the biomass and waste conversion literature. The dataset contains 133,000+ labeled feedstock items extracted from 121,000+ peer-reviewed studies. It is derived from upstream, review-based technology corpora hosted in DataverseNO, where feedstock descriptors were extracted from titles and abstracts and stored together with stable record identifiers and technology/corpus labels. In this release, the curated feedstock descriptor strings are converted into an atomic token-level representation using rule-based splitting, so that each row contains one feedstock item linked to its source record.
Each atomic feedstock item is labeled using a four-stage pipeline (L1–L4). L1 assigns two foundational attributes—material status and renewability—using controlled vocabularies and a deterministic-first decision hierarchy: curated dictionary matching, followed by explicit rules and text normalization, and finally a governed LLM-assisted resolver only for unresolved cases. L2 adds a hazardness triage label, focusing on waste- and by-product-related terms, using curated dictionaries and an external reference list aligned with the European List of Waste as a consistency aid (not as a regulatory classification). L3 applies a dedicated taxonomy for primary biomass items by assigning a primary domain and subcategory, while leaving non-primary items outside the taxonomy (taxonomy fields remain blank). L4 is a final quality-assurance stage applied after L1–L3 to ensure that equivalent feedstock terms receive consistent labels across all technology corpora when the datasets are combined.
The release is designed for reuse and computational reproducibility. It provides one labeled table per technology/corpus and a consolidated global dictionary with a consistent column structure. Versioned dictionaries, scripts, and audit artifacts are included to reproduce the labeling workflow and to document how each label set was produced. Consistency is supported through multi-layer validation and curation, including structured manual review, automated coverage and conflict audits, and cross-technology dictionary governance. Manual corrections are externalized into curated artifacts rather than overwriting output files. The dataset is intended for applications that require harmonized feedstock terminology across conversion pathways, including cross-technology feedstock mapping, harmonized inputs for modelling workflows, and comparative literature synthesis
Supplemental material for: Methane category, immune response, feed efficiency, and rumen microbial community in lactating dairy cows
No full textThe supplementary material provides information for the article published in Journal of Dairy Science, entitled "Methane category, immune response, feed efficiency, and rumen microbial community in lactating dairy cows". This study aims to assess relationships of enteric methane (CH4) yield (g/kg of dry matter intake (DMI)) with immune response, feed efficiency (energy corrected milk (ECM)/DMI), and rumen microbiome in dairy cows, both in early and in late lactation. The DMI, body weight, ECM yield, and CH4 emission were measured in respiration chambers in early (n = 20, 32 ± 7 days in milk (DIM)) and non-pregnant late lactating (n=14, 359 ± 90 DIM) multiparous Holstein cows. The in vitro immune response was studied in response to (1) lipopolysaccharide using whole blood, and (2) phytohemagglutinin and concanavalin A using peripheral blood mononuclear cells. The DNA was extracted from rumen content samples (esophageal tubing) for 16S rRNA microbial analysis. Cows were divided retrospectively into an equal number of cows with low (LMY) and high (HMY) CH4 yield within each lactation group
Replication dataset for: Large-Scale Hydrogen Explosion Experiments: Obstructed Releases in open atmosphere
No full textThis dataset includes results from large-scale hydrogen explosion experiments conducted in open atmospheric conditions during the 2024 and 2025 campaigns. The tests simulate delayed ignitions of high-pressure hydrogen jets, with variations in nozzle diameter, obstacle distance, and ignition location. Data from both obstructed and unobstructed releases are included, with recordings from high-speed cameras and high-frequency pressure sensors. Key findings address the impact of flow rates, obstacle placement, and ignition positioning on flame acceleration, overpressure, and explosion severity. The dataset serves as a critical resource for understanding hydrogen explosion behavior and improving safety designs
Replication Data for: Turbulence-induced anti-Stokes flow: experiments and theory
No full textThis set contains snapshots of the 2D velocity fields in a vertical- streamwise plane in the water phase of the recirculating water channel in Strømningsteknisk at NTNU with surface gravity waves traveling upstream on the flow. Particle image velocimetry (PIV) is used to capture the velocities. The set contains four different turbulent conditions (referred to as 2A, 2B, 3A and 3B) with different combinations of wave number (6-12 rad/m) and steepness (0.07-0.21) traveling on top. Measurements without waves are also captured. The dataset represents experiments 2 and 3 in the original article
Replication Data for: Phaeoviruses Present in Cultured and Natural Kelp Species, Saccharina latissima and Laminaria hyperborea (Phaeophyceae, Laminariales), in Norway
No full textThis dataset contains data associated with the manuscript titled "Phaeoviruses Present in Cultured and Natural Kelp Species, Saccharina latissima and Laminaria hyperborea (Phaeophyceae, Laminariales), in Norway.", part of the ViraICE project (NFR-314108).
The objective of the study was to determine the diversity, distribution, and prevalence of phaeoviruses in Norwegian kelps in the context of both coastal ecosystem management and food production in the aquaculture sector. To do so, we carried out a molecular analysis of cultured and wild samples of two economically important kelp species in Norway (Saccharina latissima and Laminaria hyperborea), along the Norwegian coast.
The dataset named "Kelp_sampling_data" contains all sampling information (date, location, depth, seawater temperature, salinity, etc) related to the two kelp species harvested from 2016 to 2022; as well as the extracted DNA concentration (eluted in two different tubes, DNA_1 and DNA_2) and PCR results against the Phaeoviral MCP gene. The following parameters are described:
- Sample
- Species
- Date
- Location
- Lat
- Long
- Sampling station
- Depth (m)
- Average temperature (Celsius)
- Salinity
- Dry weight (mg)
- DNA 1 (ng/ul)
- Volume (ul)
- DNA 2 (ng/ul)
- Volume (ul)
- Virus positive?
The total number of Phaoviral positive samples are as well described, per year and location/collector.
The dataset named "Kelp_sequencing_data" contains all information obtained by sequencing some of the PCR positive samples (number of reads, number of matches against a reference sequence list, number of viral variants found...). The following parameters are described:
- Sample ID
- Species
- Location
- Date
- ONT sequencing run ID
- ONT sequencing barcode
- # Sequences
- # Virus variants refined
- Virus variant (I, II, and/or III)
- Read matches against reference sequence
Replication Data for: Crude oil exposure during gametogenesis in the batch-spawning Atlantic cod (Gadus morhua): Effects on gametes and maternally exposed offspring development
No full textThis dataset includes data collected during a multigenerational crude oil exposure experiment involving Atlantic cod (Gadus morhua) broodstock. Mature cod in late gametogenesis were exposed for 20 days to either a crude oil water-soluble fraction or untreated seawater. After exposure, fish from both groups were repeatedly strip-spawned, and egg batches were fertilized in vitro using pooled sperm from control males. The embryos were then raised in clean seawater until hatching.
The dataset encompasses various types of data: housing conditions (temperature and oxygen saturation), mortality, and morphometric measurements of the parental generation. Additionally, it includes water chemistry analysis (polycyclic aromatic hydrocarbons and total extractable organic materials), as well as body burden analysis (polycyclic aromatic hydrocarbons and other crude oil-related organic compounds) in the eggs.
Sperm quality parameters and embryo data are also provided, including raising temperature, egg diameter, hatching success, morphology, axial deformation, and cardiotoxicity. This research was conducted at the Tromsø Aquaculture Research Station (Havbruksstasjonen i Tromsø AS, Kårvik) and the Centre for Marine Aquaculture (CAM, NOFIMA AS, Kraknes) and was approved by the Norwegian Animal Research Authority (ID 22461)
Supplementary dataset and reproducible codes for LLM-assisted mapping feedstocks of eight conversion technologies from over 121,000 studies
No full textThis dataset was developed to systematically characterise feedstock–technology relationships across eight major biomass conversion technologies by mining a large Scopus-derived bibliographic corpus (1887–2025; partial coverage for 2025). The workflow is LLM-assisted and fully reproducible, combining automated extraction of feedstock and technology phrases from bibliographic text fields (titles, abstracts, and keywords) with rule-based cleaning and a subsequent LLM-based validation step, followed by targeted manual curation for final release. The dataset is intended for use in technology landscape analyses, evidence synthesis, and comparative assessments of biomass conversion pathways, where consistent and traceable feedstock descriptors are required across a very large volume of studies.
A data descriptor titled "A large-scale, LLM-assisted and validated dataset of biomass and waste conversion technologies and feedstocks" with the following abstract will published based on this dataset:
Biomass, organic wastes and biogenic by-products are increasingly targeted for low-carbon fuels and value-added chemicals. However, strategic decision-making from a circular economy perspective requires a big-picture view of the relative significance of different conversion technologies in handling diverse feedstock portfolios, and no large-scale, cross-technology mapping of these portfolios is currently available. Thus, a literature-derived dataset was assembled, that links eight major waste-to-x valorisation technologies (gasification, pyrolysis, hydrothermal liquefaction, torrefaction, anaerobic digestion, aerobic digestion, fermentation and transesterification) to their reported feedstocks. Using the Scopus database, 121,365 records were retrieved with harmonised search strings, spanning publications from 1887 to 2025. This constrained yet scalable search strategy both facilitates automated extraction and validation and yields a rich dataset. Further, a large language model assisted workflow was implemented to extract candidate technology and feedstock phrases, followed by a two-level validation that combines rule-based cleaning with targeted LLM re-evaluation to minimise manual curation. The resulting dataset provides technology-specific, validated feedstock descriptors that supports comparative analyses and decision-support applications in a circular bioeconomy context
Replication Data for: Perceiving and identifying vowels in regional accents of English: Evidence from Dutch- and Spanish-speaking L2 listeners
No full textDataset abstract
This dataset contains the results of a study on cross-language and second-language vowel perception in Dutch-speaking and Spanish-speaking learners of English. The dataset includes both acoustic similarity predictions and behavioral data from two perceptual tasks.
For the acoustic comparisons, Linear Discriminant Analysis (LDA) models were trained on native vowel data from Dutch and Spanish speakers, recorded in earlier studies. The models were tested on English vowel tokens produced by speakers of Southern British English (S.Eng), Northern British English (N.Eng), and Australian English (AusE), and predict how similar these English vowels are to Dutch and Spanish vowels based on acoustic properties, such as formant frequencies and vowel duration.
In addition to these acoustic predictions, the dataset includes behavioral responses collected during two experimental sessions. In the first session, 40 L1 Dutch and 40 L1 Spanish participants completed (i) a demographic and language background questionnaire, (ii) a cross-language vowel categorization task consisting of 210 trials, and (iii) a general vocabulary test (LexTALE; Lemhöfer & Broersma, 2012). During the cross-language categorization task, participants listened to English vowels produced in the three accents and indicated which vowel from their native language was most similar to that vowel, followed by a goodness-of-fit rating (i.e., how good an example of that vowel the sound was). In the second session, the same participants completed a second-language vowel categorization task with the same 210 trials, in which they were asked to identify which English vowel they heard and to rate how good an example of that vowel it was.
The participants’ cross-language categorization responses were compared to the acoustic similarity scores from the LDA models, to assess how perceived (phonetic) similarity and acoustic similarity align. Participants' identification accuracy in the second-language task was analyzed using a mixed-effects logistic regression model. The repository includes all raw and processed data, the R code used for statistical analysis, and the model outputs.Article abstract
This study examines how L2 English listeners perceive and categorize vowels produced in three regional accents of English: Southern British (S.Eng), Northern British (N.Eng), and Australian English (AusE). Specifically, we investigate how L1 speakers of Belgian Dutch and European Spanish classify these vowels in terms of their native vowel categories, and how such perceptual classifications relate to acoustic similarity between L1-L2 vowels and L2 vowel identification accuracy. To quantify cross-language acoustic similarity and predict which L2 vowel contrasts would be perceptually challenging, Linear Discriminant Analysis (LDA) models were trained on Dutch and Spanish vowel data and tested on English vowel data. 40 Dutch-speaking and 40 Spanish-speaking participants then completed a cross-language categorization task and second-language vowel identification task using naturally produced /CVC/ syllables. The results demonstrate that LDA-based acoustic similarity
largely predicts cross-language perception, although certain vowel categorization
patterns point to differences in acoustic cue-weighting between the LDA models and
participants. Compared to Spanish listeners, Dutch listeners’ classifications showed
greater divergence from the LDA model, likely reflecting the denser vowel inventory of
Dutch and the resulting increase in category competition. Additionally, participants’
cross-language vowel categorization responses predicted their L2 vowel identification
accuracy. That is, L2 vowels consistently mapped onto a (single) different L1 category
with high goodness-of-fit were more likely to be identified correctly. Identification
accuracy was highest for S.Eng vowels, aligning with participants’ greater self-reported familiarity with that accent. Together, our findings highlight the complex interplay between cross-language similarity, vowel inventory and accent familiarity in shaping L2 perception. </p
Supporting Data for: Innovation through Intuition
No full textThis dataset contains 5 guided imagery exercises which are part of the mirco course "Innovation through Intuition" as to be published in the Publication Series from the University of South-Eastern Norway. These audio exercises are grounded in the Trilogos Method, a contemplative practice designed to support intuition, reflection, and actionable insight in research and development contexts. Each exercise addresses a distinct dimension of innovation processes. Developing New Ideas facilitates the emergence of novel and unconventional perspectives by engaging imaginative and intuitive capacities. Facing Unexpected Challenges supports participants in recognizing and constructively working through inner and outer obstacles that may hinder progress. Finding Vital Resources focuses on identifying and activating personal, relational, and contextual resources relevant to ongoing projects. Gaining Fresh Perspectives enables participants to reframe their work by adopting alternative viewpoints and uncovering overlooked aspects. Finally, Taking Next Steps translates intuitive insights into concrete, practical actions that can be implemented in academic or professional practice. Together, the five exercises form a coherent contemplative framework for fostering creativity, resilience, and reflective decision-making in complex research and development settings
Replication Data for: Interactive population effects of sublethal copper exposure and predation risk in a naturally stressful environment
No full textThe dataset contains data used in the study “Interactive population effects of sublethal copper exposure and predation risk in a naturally stressful environment
”. It contains experimental data from a mesocsom with the copepod Tigriopus brevicornis. The project was part of the MULTICOP project financed by the Norwegian Research Council (project number 301153). (2024-01-21)
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Methods
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We investigated the cumulative effects of copper and predation risk exposure on T. brevicornis over three generations. T. brevicornis is commonly found along European Atlantic shorelines and in high densities in tidal and splash water pools. The experiment was conducted at the University of Oslo Biological Research Station “Biologen” in Drøbak, Norway,. We established 36 populations by transferring 11 ovigerous T. brevicornis females from nearby splash pools into glass trays placed on the quay of the station’s harbor at th shoreline.
Two days before adding copepods, we filled each tray with 2.5 liters of seawater and their respective treatments: predation risk, copper (10 µg Cu L-1), combined, and control. Predation risk was simulated using fish kairomones. We incubated three-spined stickleback in seawater, similar to Lode et al. (2020). The 12-week experiment involved water and treatment renewals every 2 weeks. Before each renewal, we screened each microcosm for copepods (fewer than 10 or many) and other visible animals and debris. We sampled populations every 4th week by taking down 1/3 of the replicates, resulting in three independent replicates per timepoint and treatment. If possible, we randomly picked 100 individual late-stage copepodites and adults for pigment and stable isotope analysis. They were depurated in filtered seawater for two hours at ambient salinity. We then sampled adults for pigment analysis and stable isotope analysis. The remaining microcosm was filtered and preserved in 96% ethanol to determine T. brevicornis population density, structure, and abundances of other organisms. To analyze copepods’ Astaxanthin pigment content of individidual copepods, we used Thrane et al.’s (2015) spectrophotometric analysis. To calculate the specific Astaxanthin content, we used the ashfree dryweight derived from the length-weight regression for harpactcoids (Hopcroft et al., 1998). The δ15N and δ13C ratios of individual copepod samples were measured on a Thermo Fisher DeltaV Stable Isotope Mass Spectrometer configured with a Flash Elemental Analyzer Isolink system at the CLIPTlab of the Univeristy of Oslo.
References
Hopcroft, R.R., Lombard, D., Roff, J.C., 1998. Production of tropical copepods in Kingston Harbour, Jamaica: the importance of small species. Marine Biology 130, 593–604. https://doi.org/10.1007/s002270050281
Thrane, J.-E., Kyle, M., Striebel, M., Haande, S., Grung, M., Rohrlack, T., Andersen, T., 2015. Spectrophotometric Analysis of Pigments: A Critical Assessment of a High-Throughput Method for Analysis of Algal Pigment Mixtures by Spectral Deconvolution. PLOS ONE 10, e0137645. https://doi.org/10.1371/journal.pone.0137645
Lode, Torben, Jan Heuschele, Tom Andersen, Josefin Titelman, Ketil Hylland, and Katrine Borgå. 2020. Contrasting effects of predation risk and copper on copepod respiration rates. Environmental Toxicology and Chemistry, 39(9), pp.1765-1773. https://doi.org/10.1002/etc.4804.https://doi.org/10.1002/etc.4804.
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Datafiles
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MesocosmDataHeuscheleetal.csv
ID: unique mesocosm id
Counting.order: The order in which the samples were counted.
Copper: “Copper” indicates that the treatment had added copper at a concentration of 10 ug L-1, while “No copper” was not treated with copper.
Kairomone: “Kairomone” indicates that the smell of fish was added to the treatment, while “No kairomone” indicates the lack thereof.
Date: Sampling date as d/m/y
Month: Month
Day: Day in the year
MeanT: Average daily temperature of sampling day
maxT: maximum daily temperature of sampling day
minT: minimum daily temperature of sampling day
rangeT: daily temperature range of sampling day
ESDD needed to calculate accumulated extreme stress degree days.
ESDDaccum accumulated extreme stress degree days, i.e. days mesocosm inhabitants mesocosm likely experienced above 32 degrees.
filamentous_green_algae: amount of filamentous algae present in the mesocosms. None,Few,Many,Lots, “NA” indicates that it was not assessed
water_colour: Assessment of the color of the water in the mesocosm, “NA” indicates that it was not assessed.
salinity_psu: Salinity of the mesososm measured with a refractometer.
Nauplii: Number of Tigriopus brevicornis Nauplii
Copepodites: Number of Tigriopus brevicornis copepodites
Copepod.with.eggsac: Number of Tigriopus brevicornis females with eggsacs
Chironomide Number of Chironomides
Other Number of other animals (dead or alive), such as drowned bumblebees, etc.
Shorefly: Number of Ephydridae
Adults: Number of Tigriopus brevicornis adults
AllCopepodites: Sum of copepodites and adult copepods
Allcopepods: Sum of all copepod individuals
STRESS: Stress factor
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Concentration.animals.csv
Sample: MesocosmID
Date: Date of takedown
Month: Takedown month in the year
X: identifier
Sample.ID.new: name of the image the measurements were taken from
Imagenames: name of the image the measurements were taken from
AvgProsomeLength: prosome length in um
DWug:ash free dryweight calculated (ug)
uniqueID: unique ID of the individual
ng.well: nanogram astaxanthin in the well
Dataset: Indicating whether it is from actual animal measurements or not
Treatment: Treatment the animal was exposed to in the experiment
Plate: microwell plate id
ng.animal: ng astaxanthin per animal
Kairomone: “Kairomone” indicates that the smell of fish was added to the treatment, while “No kairomone” indicates the lack thereof.
Copper: “Copper” indicates that the treatment had added copper at a concentration of 10 ug L-1, while “No copper” was not treated with copper.
Censored: indicating whether the Astaxanthin value was below the assumed limit fo detection
AstaxanthinPerDW: Astaxanthin per animal dryweight / specific Astaxanthin mass (ng Astaxanthin per ug dry weight)
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StableIsotopeData.csv
ID: Mesocosm ID
Treatment: treatment coded as a four-level factor
Copper: “Copper” indicates that the treatment had added copper at a concentration of 10 ug L-1, while “No copper” was not treated with copper.
Kairomone: “Kairomone” indicates that the smell of fish was added to the treatment, while “No kairomone” indicates the lack thereof.
Date: Sampling date as d/m/y
Month: Sampling month
ID2: id specific to the stable isotope analysis
c13: delta 13C isotope value
%C: percent carbon
C Notes: annotation for the carbon values (all NA)
N15: delta 15N isotope value
%N: percent nitrogen
N Notes: annotation for the nitrogen values (all NA