432 research outputs found
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Data of oxygen reduction reaction on AgPd nanocatalysts prepared by galvanic exchange
No full textThis dataset contains the data presented in the figures of published paper
"Oxygen reduction reaction on AgPd nanocatalysts prepared by galvanic exchange" published in Applied Surface Science 636 (2023) 157859. https://doi.org/10.1016/j.apsusc.2023.157859
This dataset contains data for Figures 4-6
Sweden: Bibliographical database of Swedish journalism and media research related to risks and opportunities for deliberative communication (2000–2020)
No full textThe dataset is produced within the framework of the HORIZON 2020 project called MEDIADELCOM (Critical Exploration of Media Related Risks and Opportunities for Deliberative Communication: Development Scenarios of the European Media Landscape) in 2021-2022.
The dataset is one of the 14 single-country data sets included in the consolidated file of country data sets (with 5623 entries), all in msw.xlsx format. All tables are searchable by 20 variables: full reference, year of publication, national/international publication, language, country the publication deals with, time of empirical data gathering, type of publication, open access/not OA, where referenced, focus on journalism domain, focus on media-related competences domain, focus on media usage patterns domain, focus on legal and ethical regulations domain, type of the approach, original key words, main topic, comments, country.
As the data has been gathered specifically about the research done in four mentioned domains concerning potential ROs emanating from the news media development for deliberative communication, this database does NOT cover ALL the academic publications in the fields of media and journalism research. Consequently, the above-mentioned conditions limit the generalizations and comparisons based on the current database
Germany: Bibliographical database of German journalism and media research related to risks and opportunities for deliberative communication (2000–2020)
No full textThe dataset is produced within the framework of the HORIZON 2020 project called MEDIADELCOM (Critical Exploration of Media Related Risks and Opportunities for Deliberative Communication: Development Scenarios of the European Media Landscape) in 2021-2022.
The dataset is one of the 14 single-country data sets included in the consolidated file of country data sets (with 5623 entries), all in msw.xlsx format. All tables are searchable by 20 variables: full reference, year of publication, national/international publication, language, country the publication deals with, time of empirical data gathering, type of publication, open access/not OA, where referenced, focus on journalism domain, focus on media related competences domain, focus on media usage patterns domain, focus on legal and ethical regulations domain, type of the approach, original key words, main topic, comments, country.
As the data has been gathered specifically about the research done in four mentioned domains concerning potential ROs emanating from the news media development for deliberative communication, this database does NOT cover ALL the academic publications in the fields of media and journalism research. Consequently, the above-mentioned conditions limit the generalizations and comparisons based on the current database
Dataset on stable isotope measurements of Estonian medieval and early modern human bones
No full textAndmekogu sisaldab Eesti kesk- ja varauusaegsetest inimluudest tehtud stabiilsete isotoopide analüüsi tulemusi. Andmestik koosneb ühest tabelifailist, mis sisaldab tulemusi ja andmete koondstatistikat, ning ühest analüüsi aruandest, mis kirjeldab metoodikat. Andmed on kogutud Tallinna Ülikoolis ajaperioodil 2019-2022 osana projektist PRG29.This dataset contains stable isotope measurements analysed from Estonian medieval and early modern human bones. The dataset consists of one spreadsheet file and one text file (report). Spreadsheet file contains the results of the analysis and summary statistics. Text file consists of methodological description. It is being made public to act as supplementary data for publication. These data were collected and compiled at Tallinn University during the period of 2019-2022 as part of the project PRG29
DigiEfekt: looduspädevus (science competance)
No full textREADME-fail (ing k) on leitav DigiEfekti kollektsiooni “Koondfaili” juurest.Looduspädevuse andmekogu on osa DigiEfekti (DIGIVARA5) koondandmekogust. Andmekogu koosneb kolmest tabelist (“science_3_data”; “science_6_data”; “science_9_data”), kus on esitatud 3., 6. ja 9. klassi õpilaste sügisese ja kevadise andmekogumise andmed, sh konstruktispetsiifilised tunnused. Koodiraamat on lisatud andmefailidesse teisele lehele ("Codebook"). Lisatud on uuringu instrumente ja tulemusi kirjeldav põhiuuringu raport (“science_report_est”). Looduspädevuse testiga hinnati loodusteaduste õpitulemusi viie kirjeldatava tunnuse lõikes neljal erineval tasemel. Viis hinnatavat tunnust olid analüüsioskused, kavandamisoskused, tõlgendamisoskused, uurimuslikud teadmised ja ainealased teadmised. 3. klassis kasutati ülesandeid alg-, kesk- ja kõrgtasemel ning 6. ja 9. klassis kesk-, kõrg- ja tipptasemel. Tasemed on omavahel kooliastmeti võrreldavad.[ENG] The science competence data set is part of the Digiefekt project (DIGIVARA5) aggregated data set. The data set comprises three tables (“science_3_data”; “science_6_data”; “science_9_data”) that present the third-, sixth- and ninth-grade students’ data from the autumn and spring data collection rounds, incl. the construct-specific variables. The codebook is found on the second sheet of the data files ("Codebook"). There is also the main study report on the study instruments and results (“science_report_est”). The science competence test was used to assess students’ study results in Science across five describable variables on four different levels. The five variables assessed were the following: analysis skills, planning skills, interpretation skills, inquiry knowledge and subject knowledge. In the third grade, basic-, medium- and high-level assignments were used; in the sixth and ninth grade, the assigments were on medium, high and advanced levels. The levels are comparable across stages of study.Raporti soovituslik viide eestikeelses allikas: Pedaste, M. (2022). DigiEfekti põhiuuringu tulemuste raport – looduspädevus. Tartu Ülikool. http://doi.org/10.23673/re-410Raporti soovituslik viide ingliskeelses allikas: Pedaste, M. (2022). DigiEfekti põhiuuringu tulemuste raport – looduspädevus. [Report of the DigiEfekt project – science competence]. University of Tartu. http://doi.org/10.23673/re-41
Dataset on zooarchaeological records of Estonian medieval and early modern mammal remains
No full textThis dataset contains data collected during the analyses of archaeological mammal remains from 37 medieval and early modern sites in Estonia. The dataset consists of four tables: 1) information on archaeological sites, 2) identifications, 3) cattle metacarpal morphometrics, 4) stable isotope data. It is being made public both to act as supplementary data for the research project PRG29 and for the publication Rannamäe, E. & Aguraiuja-Lätti, Ü. 2023. Zooarchaeology of livestock and game in medieval and early modern Estonia. Estonian Journal of Archaeology, 27, 3S, 50–82, https://doi.org/10.3176/arch.2023.3S.03
Eesti taskuhäälingukorpus
No full textKorpus koosneb eesti taskuhäälingusaadetest ja nende transkriptsioonidest. Korpuses on kokku 10 633 episoodi 184 erinevast taskuhäälingust, kogukestusega 10 918 tundi, mis on salvestatud vahemikus 2018–2022. Salvestused on transkribeeritud Tallinna Tehnikaülikooli automaatse kõnetuvastusega ning tekstid on automaatselt morfanalüüsitud EstNLTK-ga. Kokku on korpuses 85 miljonit sõna. Korpus on kogutud andmekaeveks teadustöö eesmärgil. Korpus on koostatud veebikraapimismeetodil, siia on valitud erinevaid eestikeelseid podcaste, mida kajastavad portaalid podcastid.ee ja podcast.ee. Korpus on valminud koostöös Tartu Ülikooli ning Tallinna Tehnikaülikooliga projektide EKKD93 "Suuline eesti keel arvudes" ja EKKD117 "Suuline eesti keel arvudes II" (Haridus- ja Teadusministeeriumi programm "Eesti keel ja kultuur digiajastul") raames.This corpus consists of Estonian podcasts and their transcriptions. There is a total of 10 633 episodes from 184 different podcasts with total duration of 10 918 hours. The recordings are made between 2018-2022. The recordings are automatically transcribed with TalTech ASR system and morphologically analysed with EstNLTK. The text corpus consists of 85 million words in total. The corpus has been collected for academic data mining purposes using web scraping. The collection contains a selection of Estonian podcasts that are indexed by the portals podcastid.ee and podcast.ee. The corpus has been created by University of Tartu in cooperation with Tallinn University of Technology (TalTech) and Estonian Public Broadcasting (ERR) in the project EKKD93 "Basic statistics of spoken Estonian" and EKKD117 "Basic statistics of spoken Estonian II" (Ministry of Education and Research program "Estonian Language and Culture in the Digital Age")
N2 adsorption isotherm data of briquettes made from red and white clays with sand and chalk tempers fired at 600 and 800 °C
No full textN2 adsorption isotherm data of clay briquettes made from red and white clay with sand and chalk tempers fired at 600 and 800 °C. N2 adsorption isotherms of bulk sand and briquettes made from bulk white and red clay fired at 600 °C. N2 adsorption isotherms of 3 equivalent composition red clay briquettes with 50% sand temper and each measured 2 times for statistical analysis. All data files include pore size distributions obtained by fitting to the NLDFT model for pillared clays
The high-resolution topsoil plant-available phosphorus map of Estonia
No full textThe high-resolution (1:10,000) hybrid topsoil plant-available phosphorus map was produced by combining: (a) arable-land polygons with the median topsoil P value, (b) the machine learning bagging model based predicted values for agricultural lands with missing or limited sampling data, and (c) the two-parameter soil–land use ordination matrix-based model values for forests, wetlands and peat extraction sites.
Soil phosphorus data available for agricultural soils were obtained from the PANDA database, which contains regular soil monitoring and voluntary soil sampling data by farmers. The database contains soil sampling data collected from agricultural lands for the period 2005–2021 and is managed by the Centre of Estonian Rural Re-search and Knowledge. For this period in the PANDA database, there are data about 387,904 composite soil samples all over Estonia, including topsoil phosphorus content (mg/kg). Composite soil samples in the PANDA database were collected by licensed personnel following the same prescribed sampling strategy (prescribed sampling route and sampling density, depth, and volume) and analyzed in the same laboratory using the Mehlich-3 method.
There are no similar comprehensive topsoil phosphorus content databases for other land-use categories available in Estonia. Comparable values of topsoil phosphorus content for other land-use types (forest, wetland, peat extraction areas, and quarries) by soil types were searched through a literature review of scientific papers, reports, the Estonian Environmental Monitoring System database, and supplemented by original unpublished datasets of the authors. Topsoil P concentration in the forest and peatland soil samples collated from multiple studies and literature sources were determined with various methods (Aqua Regia, Olsen, and Kjeldahl), and, thus, conversion coefficients based on Kulhánek et al., 2009 and Wolf and Baker, 1985 were used to convert phosphorus content to the same level with the Mehlich-3 method prior to statistical analysis.
We used more than 388,000 topsoil plant-available phosphorus (P) samples to study spatial and temporal variability and land-use effect on soil P content. We developed a mapping approach based on existing databases of soil, land-use, and fragmentary soil P measurements by land-use classes to provide spatially explicit high-resolution estimates of topsoil P at the national level.
The topsoil P content (mg/kg) for each soil–land use unit of eight agricultural land-use categories (permanent grassland, fallow, cultivated grassland, permanent cultures, cereals, legumes, technical cultures, and vegetables) were based on the observed polygon median topsoil P content value if a particular soil–land use unit had sufficient number of sampling data in PANDA database to calculate the median value. The bagging model predicted topsoil P values were used in agricultural land where sampling data were limited or missing. The remaining three non-agricultural land-use types (forest, wetland, and peat extraction area) were based on the ordination model results.
Detailed description of data and methods is provided in: Kull, A.; Kikas, T.; Penu, P.; Kull, A., 2023. Modeling Topsoil Phosphorus — From Observation-Based Statistical Approach to Land-Use and Soil-Based High-Resolution Mapping. Agronomy, 12, x.Modelleeriti mulla künnikihi taimedele omastatava fosfori (P) sisaldust (mg/kg). P modelleerimiseks kasutati PANDA andmebaasist pärit põllumajanduslikel maadel 2005-2020 mõõdetud mulla künnikihi P sisalduse andmeid. P mõõtmisi tehti ICP seadmega Melichi (M3) süsteemi järgi. Mulla P sisaldust seletavate tunnustena kasutati EstSoil-EH andmebaasis sisalduvaid mulla karakteristikuid, maakasutust (PRIA põllumassiividel kasvatavate kultuuride andmeid, lisaks EELIS andmebaasist looduslikke rohumaid (poollooduslikud kooslused) ja ETAKist metsi ja märgalasid. Seletavate tunnustena kasutati ka pinnakatte settetüüpe ning asukoha XY ja Z koordinaate (kõrgused pärinesid Maa-ameti 10 m lahutusvõimega LiDAR kõrgusmudelist). Ordinatsioonimeetodi puhul järjestati kõik esinevad mullad ja maakasutusklassid P sisalduse mediaanväärtuse alusel suuremast väiksemani ning interpoleeriti programmis Surfer (Radial Basis, Multiquadratic meetodiga) väärtuspind, mis iseloomustab P sisaldust erinevate mulla ja maakasutuse klasside kombinatsioonide korral ning annab pideva väljana väärtused ka mõõtmisandmetega katmata mulla ja maakasutusklasside kombinatsioonidele. Lisaks PANDA andmebaasist pärinevatele P andmetele kasutati ordinatsioonipinna loomisel ka teiste uuringute käigus mõõdetud ja kirjanduses avaldatud P mõõtmise tulemusi metsa ja märgalade muldade kohta. Saadud tulemused omistati mullakaardi ja maakasutuse kihi lõikamisel saadud mulla-maakasutuse polügonidele. Kirjeldava statistika andmed näitasid, et mulla ja maakasutuse mõju mulla P sisaldusel on oluline, aga kirjeldab ära ainult ligi 20% varieeruvusest. Suurema kirjeldusvõimega mudeli loomiseks kasutati masinõppe meetodit Bagging (Bootstrap Aggregation) statistikaprogrammis R ja paketti Baguette. Bagging mudelis kasutati seletavate tunnustena eelpool nimetatud EstSoil-EH mullakaardi andmeid, maakasutust, pinnakatte settetüüpe ja P mõõtmispunkti XYZ koordinaate. Bagging mudeli tulemuste täpsuse hindamiseks võrreldi omavahel bagging mudeli loomisest välja jäänud nn testandmetele (25% P mõõtmispunktidest) prognoositud P väärtusi samade punktide mõõdetud väärtustega ja saadi tulemuseks R2 = 0,54. Loodud bagging mudeli põhjal prognoositi P väärtused üle Eesti mulla-maakasutuse polügonidesse. Kuna mõõtmisi oli tehtud ainult põllumajanduslikel aladel, siis looduslikel aladel ei olnud mudeli tulemused piisavalt usaldusväärsed. Polügonides, kuhu jäi piisavalt määratud P väärtusi, asendati bagging mudeli prognoositud P väärtus polügoni tegeliku mõõdetud P mediaanväärtusega. Loodusliku maakasutusega aladel (mets, märgala) asendati bagging mudeli poolt prognoositud P väärtused ordinatsioonimudeli poolt prognoositud väärtustega, kuna ordinatsioonimudel sisaldas ka kirjandusest pärinevaid andmeid metsade ja märgalade P väärtuste kohta erinevatel mullatüüpidel
Italy: Bibliographical database of Italian journalism and media research related to risks and opportunities for deliberative communication (2000–2020)
No full textThe dataset is produced within the framework of the HORIZON 2020 project called MEDIADELCOM (Critical Exploration of Media Related Risks and Opportunities for Deliberative Communication: Development Scenarios of the European Media Landscape) in 2021-2022.
The dataset is one of the 14 single-country data sets included in the consolidated file of country data sets (with 5623 entries), all in msw.xlsx format. All tables are searchable by 20 variables: full reference, year of publication, national/international publication, language, country the publication deals with, time of empirical data gathering, type of publication, open access/not OA, where referenced, focus on journalism domain, focus on media related competences domain, focus on media usage patterns domain, focus on legal and ethical regulations domain, type of the approach, original key words, main topic, comments, country.
As the data has been gathered specifically about the research done in four mentioned domains concerning potential ROs emanating from the news media development for deliberative communication, this database does NOT cover ALL the academic publications in the fields of media and journalism research. Consequently, the above-mentioned conditions limit the generalizations and comparisons based on the current database