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Supplementary code and data for LLM-based validation of a circular economy R-strategy dictionary
No full textDATASET MIGRATED FROM FIGSHARE: This dataset provides the code and example input–output files used for the LLM-assisted validation of a circular economy R-strategy keyword dictionary. It accompanies the manuscript on rule-based analysis of 500 circular economy definitions. The dataset does not include the full set of 500 circular economy definitions; it focuses specifically on the R-strategy keyword dictionary and its validation workflow, enabling other researchers to inspect, reuse, or adapt the dictionary and reproducibly apply the same validation procedure to their own keyword sets.</p
Does standardization matter? Evaluating the potential of the Common European Framework of Reference for Languages (CEFR) to foster labour market inclusion of immigrants (DISCEFRN): Vignette study dataset
No full textThis data contains the collected information of the survey experiment that was carried out within the DISCEFRN project (see metadata section Funding Information).
Within DISCEFRN, we combined web-scraped job vacancy data of the Norwegian labour market with a factorial survey experiment that exploits real-world variation in CEFR requirements within these ads (n vignette ratings= 10,495; n employers= 1,527) to examine whether fictitious applicants with a refugee background face less language-based discrimination on the individual level among employers who use standardized language requirements in their (real-world) ads compared to those that don’t. We thereby varied different applicant characteristics related to ethnic origin and to formal (CEFR certificate) and informal language indicators (e.g. spelling, argumentation, professional reference on unobservable relational skills) within vignettes and collected information on job-, firm- and employer characteristics (most notably attitudes towards different refugee groups) with standard survey items. This allowed us to assess whether CEFR requirements are primarily mitigating biased applicant evaluations that are related to language-based statistical/error discrimination (less relevance of informal language indicators), related to discrimination tastes (less relevance of group-related attitudes), or both.
This dataset contains all information on the survey experiment. It is a stand-alone dataset and contains all relevant data to re-produce associated publications (See metadata field on Publications) or be reused for other research interests. Yet, it can still be linked to additional DISCEFRN datasets, i.e. the web-scraped data set, that also holds information on those employers that did not participate in the survey experiment (https://doi.org/10.18710/K6WA0V).</p
Replication Data for: On the variation of ocean surface gravity wave characteristics with wind speed and direction: A case study from offshore Svalbard, Norway
No full textA dataset containing re-sampled data used to optain the results presented in the paper 'On the variation of ocean surface gravity wave characteristics with wind speed and direction: A case study from offshore Svalbard, Norway' publised in 2025. It contains processed strain data in strain unit, converted from the time-differentiated phase measured by an OptoDAS interrogator through a dark fiber in a submarine telecommunication cable. This fiber is trenched into soft sediments at 0-2 m below the seafloor from Longyearbyen to Ny-Ålesund in Svalbard, Norway. The raw data used in the analysis acquired from 2022-08-05 to 2023-09-17, and converted to strain data. To reduce file sizes, we resampled the raw data with a sample rate of 25 Hz, and are archived accordingly. As we have analysed a full year of data only a subset is archieved, but it is enough to recreate the major findings in the paper. The processed data are stored as structured arrays in MATLAB file format and as a matrix in csv files. This data set has no exact positioning data of the fiber optic cable, because they are proprietary to SIKT. However, an approximate cable position can be extracted from https://www.norgeskart.no/ and changing the base layer to 'Nautical charts overview'. Moreover, the distance of each recording channel along the cable from the shore (the fiber enters the fjord at roughly 4.2 km) is given in this data set
A dataset of 1500-word stories generated by gpt-4o-mini for 236 nationalities
No full textWe created a dataset of stories generated by OpenAI’s gpt-4o-miniby using a Python script to construct prompts that were sent to the OpenAI API. We used Statistics Norway’s list of 252 countries, added demonyms for each country, for example Norwegian for Norway, and removed countries without demonyms, leaving us with 236 countries. Our base prompt was “Write a 1500 word potential {demonym} story”, and we generated 50 stories for each country.
The scripts used to generate the data, and additional scripts for analysis are available at the GitHub repository https://github.com/MachineVisionUiB/GPT_storie
ELVHYS 4.1 Oxygen enrichment and condensed phase explosions
No full textThis dataset contains experimental data for an experimental campaign undertaken as part of the ELVHYS project No. 101101381, supported by the Clean Hydrogen Partnership and its members. HSE participation in Horizon Europe Project ELVHYS is supported by UKRI grant number 10070592. HSE participation is further supported by Lloyd’s Register Foundation. This dataset contains the data collected during project task 4.1: Condensed phase explosion tests from LH2 transfers system
Replication Data for: Long Non-Coding RNA Transcripts in Crucian Carp Brain – Annotation and Expression Patterns in Anoxia and Reoxygenation
No full textThe dataset contains the supplementary material that was created to identify and investigate long non-coding RNA (lncRNA) in the whole brain tissues of crucian carp (Carassius carassius), i.e. the annotation of lncRNAs with the four algorithms (FEELnc, CNCI, CPAT and CPC2), the result of differential expression analysis of the identified lncRNAs, and the characterization of predicted interaction partners and results from analysis of their differential gene expression. All raw RNA sequencing data are deposited in the NCBI Sequence Read Archive (SRA) under BioProject ID PRJNA386629 (http://www.ncbi.nlm.nih.gov/bioproject/386629). The genome sequence and annotation data were obtained from DataverseNO (https://doi.org/10.18710/GXMSUH). The scripts are available in the GitHub repository LncRNA (https://github.com/MagdalenaWinklhofer/LncRNA.git)
Background data for: An analysis of bar chart usage in corpus data visualization
No full textDataset description
This dataset contains information about the use of bar charts for corpus data presentation. It is based on a systematic review covering all papers (n = 1,183) published in five corpus-linguistic journals up to and including the year 2024 (International Journal of Corpus Linguistics, Corpus Linguistics and Linguistic Theory, Corpora, Research in Corpus Linguistics, and the International Journal of Learner Corpus Research). In total, the report pool includes n = 1,061 unique instances of bar charts, and the current dataset documents various properties of these diagrams, including information about their content (e.g. number and types of variables, number of levels per variable) and design (e.g. type of bar chart, scaling information, size, use of color). Further, information is provided about the frequency of use of different types of statistical graphs and statistical tables for each article (n = 1,183) in the report pool.Abstract: Related publication
A recent survey of graph usage in corpus-based research has shown that the bar chart is the most widely used graph type for corpus data presentation. Motivated by this finding, the present paper offers a systematic review of bar chart usage in corpus-based research articles. It covers all papers (n = 1,183) published in five corpus-linguistic journals up to and including the year 2024 (International Journal of Corpus Linguistics, Corpus Linguistics and Linguistic Theory, Corpora, Research in Corpus Linguistics, and the International Journal of Learner Corpus Research). The aim of this survey is to arrive at a better understanding of the kinds of visualization tasks imposed on bar charts. We observe that they most commonly show percentages or absolute/normalized frequencies, and that they are often used for relatively complex visualization tasks involving multiple variables and subgroups. The survey is carried out against the backdrop of known limitations of this graph type and design recommendations found in data visualization guidebooks. Our critical examination of diagrams pays attention to issues that compromise the ability of the viewer to accurately perceive patterns in the data, and minor issues that affect the efficiency of a display. These observations are then distilled into a set of concrete recommendations, which are grounded in current usage and the advice given in the data visualization literature.</p
Replication Data for: Argument structure constructions in competition: The Dat-Nom/Nom-Dat alternation in Icelandic
No full textThe current Icelandic dataset contains the replication data for Somers & Barðdal (2022) and Somers, Jenset & Barðdal (2024a). The data have also been used in Somers & Barðdal (2023), Somers, Jenset & Barðdal (2024b) and Elens, Somers & Barðdal (2024). The dataset, which has been compiled using the Icelandic Web 2020 corpus, or isTenTen20, contains 200 observations each for 15 Icelandic verbs, thus amounting to a total of 3,000 observations. The verbs in question belong to one of three syntactic classes: (1) Dat-Nom verbs, (2) Nom-Dat verbs and (3) Dat-Nom/Nom-Dat verbs. All tokens have been annotated for lemma, verb class and the internal order of the dative and the nominative arguments. In addition, each constituent, dative and nominative, has been annotated for (1) case, (2) (pro)nominality, (3) pronoun type (if applicable), (4) referentiality, (5) person, (6) number, (7) definiteness, (8) animacy and (9) length
Replication Data for: Field test of assumptions for using line transect distance sampling on rock ptarmigan
No full textLine transect distance sampling using pointing dogs, is an established survey method for willow ptarmigan and has also been proposed for monitoring of rock ptarmigan. In this study, we tested assumptions of line transect distance sampling that: (i) birds on the transect are detected with certainty and (ii) birds are detected at their initial location. We also investigated factors potentially influencing detection probability. We conducted field experiments in 2022 and 2023, by walking line transects while accompanied by a pointing dog, towards GPS-tagged rock ptarmigans. All rock ptarmigans within 0-30 m from the line transect were detected with 100% certainty. All birds were found close to their initial position, and most birds were passive (74%) as the surveyors approached. The best models to explain detection probability included the bird’s distance to the transect and the time of day an experiment was conducted. The distance to the transect had a strong negative effect, which is expected in line transect distance sampling designs. The time of day when conducting experiments also had a non-linear effect on detection probability, with lower detectability during midday compared to the morning and evening
Replication Data for: Mat-forming lichens support contrasting micro-arthropod density
No full textMat-forming lichens are important components of tundra and alpine vegetation, and affect soil microclimatic conditions, which in turn may influence micro-arthropod communities. Here, we compare the density of Collembola and Oribatida within lichen mats and their abundance in the underlying soil across four different mat-forming lichens at Finse, southern Norway. The lichen mats consisted of Alectoria ochroleuca, Cetraria islandica, Cladonia rangiferina/stygia, or Flavocetraria nivalis. We also measured soil element availability beneath the lichen mats