cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17898/adp_dv_nlylfu
title: Evidenca območij z omejenimi možnostmi za kmetijsko dejavnost

description: Evidenca območij z omejenimi možnostmi za kmetijsko dejavnost je prostorska evidenca (vsebuje grafične sloje) in vsebuje območja, katerih raba zemljišč za kmetijsko dejavnost je omejena, t.j. na gorskih območjih, na območjih z naravnimi omejitvami in na območjih s posebnimi omejitvami, v Republiki Sloveniji. Kriterije za določitev območij z omejenimi možnostmi predpisuje predpis Evropske Unije, razvrstitev KMG v območja OMD pa predpiše minister. Evidenco ob vsakokratni spremembi potrdi Evropska komisija v okviru Programa razvoja podeželja. Namen evidence OMD je, da služi kot zakonodajni okvir za dodatne podpore območjem, kjer so prisotni višji stroški in/ali izguba dohodka, torej podpora kmetijskim zemljiščem zaradi omejitev na kmetijskih zemljiščih. Po začetni vzpostavitvi evidence v letu 2004, so sledile spremembe v letih 2007 in 2019. Grafični sloji so javno dostopni in na voljo za ponovno uporabo brez omejitev. Podatki so dostopni za vsa leta vodenja evidence, pri čemer se predlaga pozornost pri njihovi uporabi in interpretaciji. Pravna podlaga: Zakon o kmetijstvu (ZKme-1: http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO4716) in ostale Uredbe. Dostop do evidence OMD je mogoč preko Javni pregledovalnik grafičnih podatkov MKGP (http://rkg.gov.si/GERK/WebViewer/), kjer je eden izmed slojev. Prenos podatkov je možen preko MKGP portala https://rkg.gov.si/vstop/ oz. direktne povezave http://rkg.gov.si/GERK/documents/OMD_2019.rar; http://rkg.gov.si/GERK/documents/OMD_2007_2013.RAR
DOI: 10.17898/adp_dv_s6pnbm
title: Evidenca pridelovalcev in predelovalcev ekoloških kmetijskih pridelkov ali živil

description: Zbiranje podatkov v Evidenci pridelovalcev in predelovalcev ekoloških kmetijskih pridelkov ali živil je namenjeno spremljanju stanja na trgu, spremljanju pridelovalcev in predelovalcev, površin, količin, števila živali, kontrol, izdanih certifikatov, ... V evidenci se vodijo podatki o pridelovalcih in predelovalcih, o kontrolah, izdanih certifikatih in dovoljenja za izjeme od pravil ekološkega kmetovanja. Podatki v sedanji obliki so dostopni od leta 2007 (predtem le v sumarni obliki, t.j. od leta 2000 naprej). Pravna podlaga: a) Zakon o kmetijstvu (ZKme-1: http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO4716) in b) Pravilnik o ekološki pridelavi in predelavi kmetijskih pridelkov oziroma živil (http://www.pisrs.si/Pis.web/pregledPredpisa?id=PRAV13168) ter ostale Uredbe. Večina podatkov iz evidence je javno dostopnih (izjema le davčna in matična št., EMŠO in KMG-MID). Podatki so dostopni na spletni strani SURS-a in EUROSTA-a ter Ministrstva za kmetijstvo, gozdarstvo in prehrano.
DOI: 10.17898/adp_dv_dmru9l
title: Zbirka podatkov Mreže za podeželje

description: V Mreži za podeželje se združujejo organizacije in posamezniki, ki jih zanima razvoj podeželja. Mreža vzpostavlja in zagotavlja dvostransko komunikacijo med vsemi partnerji in lokalnim okoljem, z namenom spodbujanja mreženja z vidika izmenjave znanja in izkušenj preko dogodkov, ki jih organizira Mreža za podeželje, kakor tudi obveščanje ter širjenje informacij o Programu razvoja podeželja in Skupni kmetijski politiki. V ta namen se vodi Zbirka Mreže za podeželje, ki vsebuje osebne podatke vpisanih oseb, njihove kontaktne podatke in nekaj drugih podatkov (področje zanimanja npr. kmetijstvo, gozdarstvo, varstvo okolja, podjetništvo ...). V zbirko se osebe vpišejo na podlagi izpolnjene vloge za vpis, ki je dostopna na spletni strani Mreže (https://www.program-podezelja.si/sl/kaj-je-program-razvoja-podezelja-2014-2020/narocite-se-na-e-novice). Vsem registriranim članom se tedensko pošiljajo elektronske novice. Pravna podlaga: Zakon o kmetijstvu (ZKme-1: http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO4716) in ostale Uredbe.
DOI: 10.17898/adp_dv_gyscw9
title: Register kmetijskih gospodarstev

description: Register kmetijskih gospodarstev (RKG) je zbirka podatkov o kmetijskih gospodarstvih (KMG) v Sloveniji. Namen registra je vodenje podatkov o kmetijskih gospodarstvih, kar med drugim omogoča uveljavljanje raznih pravic, kot so npr. ukrepi kmetijske politike. V RKG se vpišejo KMG, ki morajo biti po predpisih vpisana v obvezne zbirke podatkov ministrstva (imetniki goveda, prašičev, drobnice, čebelarji, vinogradniki, …), uveljavljajo finančne podpore iz Zakona o kmetijstvu ali druge ukrepe kmetijske politike, so za opravljanje kmetijske dejavnosti vpisana v uradne evidence ali registre po drugih predpisih, imajo v uporabi najmanj en hektar zemljišč, ki po evidenci dejanske rabe kmetijskih in gozdnih zemljišč sodijo med kmetijska zemljišča ali 0,1 ha oljčnikov ali 0,2 ha intenzivnih sadovnjakov ali 0,1 ha jagodičja ali lupinarjev ali hmeljišče oz. tržijo pridelke, ki jih pridelujejo (lahko tudi razlogi, ki so navedeni v Zakonu o kmetijstvu (Zkme-1)). RKG se vodi v opisni in grafični obliki, vodijo ali prevzemajo se naslednji podatki: podatki o KMG: • naslov ali sedež KMG in nosilec KMG • kmetijska zemljišča v uporabi (GERK in BLOK) • podatki o trajnih nasadih • dopolnilne dejavnosti na kmetiji • podatki o planinah in skupnih pašnikih • drugi podatki iz 143. člena Zakona o kmetijstvu. Podatki v RKG se vodijo od leta 1998, GERK-i (zemljišča v uporabi KMG) pa od 2005 (slednji so za uporabnike dostopni od leta 2006). Pravna podlaga (najpomembnejša): a) Zakon o kmetijstvu (ZKme-1: http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO4716) in b) Pravilnik o registru kmetijskih gospodarstev (http://www.pisrs.si/Pis.web/pregledPredpisa?id=PRAV12579), ki zajema tudi povezavo do obrazcev, potrebnih za zbiranje podatkov.
DOI: 10.17898/adp_dv_ykslay
title: Evidenca dejanske rabe kmetijskih in gozdnih zemljišč

description: Evidenca dejanske rabe kmetijskih in gozdnih zemljišč (v nadaljevanju: Evidenca dejanske rabe) je enotna državna evidenca o dejanski rabi zemljišč. Primarno je namenjena ugotavljanju dejanskega stanja rabe zemljišč kot pogoja za izvajanje ukrepov skupne kmetijske politike Evropske unije. Posredno in neposredno se podatki Evidence dejanske rabe uporabljajo tudi pri določanju dejanske rabe na parcelo v zemljiškem katastru, višine katastrskega dohodka, odškodnine za spremembo namembnosti kmetijskih zemljišč, spremembe bonitete zemljišč, upravičenosti do socialnih podpor, za statistične analize, raziskave, ipd. Podatki o gozdu v Evidenci dejanske rabe se usklajujejo s podatki iz evidenc Zavoda za gozdove Slovenije. Evidenca se vodi v grafični obliki na osnovi ortofoto (skeniran ali digitalni letalski ali satelitski posnetek) in drugih virov. V evidenci se vodijo podatki za posamezni poligon dejanske rabe. Pravna podlaga: a) Zakon o kmetijstvu (ZKme-1: http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO4716) in b) Pravilnik o evidenci dejanske rabe kmetijskih in gozdnih zemljišč (http://www.pisrs.si/Pis.web/pregledPredpisa?id=PRAV9267). Zajem oz. razmejitev se izvede v skladu s takrat veljavno pravno podlago (pravilnik) ter podrobnejšimi navodili za zajem dejanske rabe (interpretacijski ključ). V pravilniku je tudi e-naslov, na katerem je objavljen Šifrant in opis vrst dejanske rabe kmetijskih in gozdnih zemljišč. Aktualni pravilnik in ključ sta dostopna na http://rkg.gov.si/GERK/. Na omenjeni spletni strani so v ESRI shape formatu javno dostopni aktualni, do 1 mesec stari podatki iz evidence in arhivski podatki (stanje evidence v letih 2002, 2005, 2009, 2012, 2014, 2017). Datoteke poleg omenjenih podatkov vsebujejo tudi šifrante, metodološka pojasnila ter še nekaj drugih prikazov. Pri uporabi podatkov, predvsem pri časovni primerjavi, je potrebno upoštevati omejitve, ki izhajajo iz sprememb metodologije, ki so vezane na spremembe pravilnika in/ali interpretacijskega ključa. Podatki med leti tako niso neposredno primerljivi.
DOI: 10.6084/m9.figshare.25037645.v5
title: Occurrence Records of Tropical Asian Butterflies: 1970 - 2024

description: Occurrence records of tropical Asia's butterflies collated from online databases and published literature. This dataset consists of 730,190 occurrence records for 3,752 species.Methods:We collected occurrence records for tropical Asian Papilionoidea (Lepidoptera: Nymphalidae, Papilionidae, Lycaenidae, Pieridae, Hesperiidae, Riodinidae)(-11.426 – 35.64 N, 67.588 – 174.990 E) for the years 1970-present. Records were extracted from the Global Biodiversity Information Facility on 15 April 2024. We included only presence records derived from human observation, preserved specimens, material samples, or literature, provided they had associated coordinates. We omitted all records with &gt;100,000 m coordinate uncertainty, so-called “fuzzy” taxon matches, and records for which the scientific name was missing or incomplete, unless nomenclature could be extracted using a BOLD identifier (boldsystems.org/). This resulted in a final number of GBIF records = 651,285.We also extracted data from the B2D2 Database of Butterflies for Borneo provided by JKH/the Darwin Initiative (n = 19,417) and a dataset for Bangladesh provided by SC (Chowdhury et al. 2021) (n = 18,278), and unpublished datasets from coauthors AN, DJL, LVV, TK, and YB (n = 13,993). To fill geographic gaps when all of these records were plotted, we conducted targeted searches of the published literature on Google Scholar (details below), resulting in an additional 27,217 records. Pre-1970 data were omitted where possible from all sources. Final binomial synonym harmonization, validation, and authority assignment were conducted by DJL using a taxonomic reference prepared by Gerardo Lamas (Lamas, 2015. Catalogue of the butterflies (Papilionidae). Available from the author.).For geographic regions with relatively few GBIF records (e.g., China, Myanmar, Thailand) and for species with &lt; 10 records, we conducted targeted literature searches using Google Scholar in English, simplified Chinese, and traditional Chinese (genus OR genus + species + country name). For all species records in published sources, we extracted coordinates, locality name, locality type (e.g., exact coordinates, city, national park, island, or province), country, and year of record (where available). If exact coordinates were not provided by the source, we used Google Earth Pro (v7.3.6.9345) to estimate the locality centroid for any record provided at the province level or below (e.g., national park or city). For records from islands ≤ 100 km in length or diameter (e.g, localities within the Philippines and Indonesia), we estimated the island or archipelago centroid. If a range of coordinates was provided (e.g., records from The Butterflies of Vietnam), coordinates within the range were chosen haphazardly by selecting a point within the range provided on Google Earth Pro. Data sources for all records are provided in the reference column (C) in Occurrence Records of Tropical Asian Butterflies: 1970-2024 and alphabetically in Data Sources for: Occurrence Records of Tropical Asian Butterflies: 1970-2024.
DOI: 10.15468/dl.5dfgw2
title: Occurrence Download

description: A dataset containing 649 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bombus ignitus Smith, 1869",
 "Country is Japan",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 649 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001410-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qu8bj6
title: Occurrence Download

description: A dataset containing 314 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Theobroma angustifolium DC."
 ]
}

 The dataset includes 314 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001412-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14680461
title: DAKAR chains and bestfits - fixed cosmo except A_ds

description: Chains and bestfit points for the dakar chains, when only varying A_ds and bias parameters in the combination of all redshift bins. The order and names of the parameters are:

['A', 'b1_z1p0', 'c2_z1p0', 'b1_z1p3', 'c2_z1p3', 'b1_z1p6', 'c2_z1p6', 'b1_z2p0', 'c2_z2p0']
DOI: 10.5281/zenodo.14680460
title: DAKAR chains and bestfits

description: Chains and bestfit points for the dakar chains.

They have the label 'PriorAonly' when only varying A_ds and bias parameters. The order and names of the parameters are:

['A', 'b1_z1p0', 'c2_z1p0', 'b1_z1p3', 'c2_z1p3', 'b1_z1p6', 'c2_z1p6', 'b1_z2p0', 'c2_z2p0']

They have the label 'PriorNone' when all parameters are varied, in which case, the parameter names I normally use are:

['w', 'wa', 'A', 'omch2', 'ombh2', 'h', 'logAs', 'ns',
 'b1_z1p0', 'c2_z1p0', 'b1_z1p3', 'c2_z1p3', 'b1_z1p6', 'c2_z1p6', 'b1_z2p0', 'c2_z2p0']For the cases with a single redshift bin, just remove the parameters that are not necessary.
DOI: 10.5281/zenodo.14891777
title: DAKAR chains and bestfits

description: Chains and bestfit points for the dakar chains.

They have the label 'PriorAonly' when only varying A_ds and bias parameters. The order and names of the parameters are:

['A', 'b1_z1p0', 'c2_z1p0', 'b1_z1p3', 'c2_z1p3', 'b1_z1p6', 'c2_z1p6', 'b1_z2p0', 'c2_z2p0']

They have the label 'PriorNone' when all parameters are varied, in which case, the parameter names I normally use are:

['w', 'wa', 'A', 'omch2', 'ombh2', 'h', 'logAs', 'ns',
 'b1_z1p0', 'c2_z1p0', 'b1_z1p3', 'c2_z1p3', 'b1_z1p6', 'c2_z1p6', 'b1_z2p0', 'c2_z2p0']For the cases with a single redshift bin, just remove the parameters that are not necessary.
DOI: 10.5281/zenodo.14891428
title: 57110.19.01 Prähistorisches Bergbaugebiet Weikersbach

description: The study area covers the districts of Harham and Weikersbach in Saalfelden am Steinernen Meer, extending from the Gröbenbach stream in the south to Weikersbach in the north and from the ridge between Durchenkopf (1,764 m) and Weikersbacher Köpfl (1,614 m) down to the valley floor. The slopes are largely covered with debris, with geological outcrops mainly found in large gullies, exposing Pinzgauer phyllites with hydrothermal pyrite mineralization containing varying copper concentrations.

Due to the steep terrain, the survey was conducted in October and November 2019 without a fixed grid. It confirmed four previously known sites (smelting and mining areas) and identified a new prehistoric smelting site (Obj. 04 – Schmelzplatz Gröbenbach) at 1,350–1,360 m altitude. The site was recognized by strong soil discoloration and sparse vegetation. A 6 m high slope revealed evidence of past smelting activities over a 25 m stretch, including slag processing remains, heat-reddened stones, and remnants of a smelting furnace disrupted by forest road construction. A complete slag cake from the furnace was recovered, along with a charcoal sample for dendrochronological analysis.

All documented smelting sites share characteristics with those in Viehhofen, showing evidence of multiple smelting processes and slag refining. The sites were recorded using GNSS, and representative finds were collected for further study (dendrochronology and radiocarbon dating).
DOI: 10.5281/zenodo.14891429
title: 57110.19.01 Prähistorisches Bergbaugebiet Weikersbach

description: The study area covers the districts of Harham and Weikersbach in Saalfelden am Steinernen Meer, extending from the Gröbenbach stream in the south to Weikersbach in the north and from the ridge between Durchenkopf (1,764 m) and Weikersbacher Köpfl (1,614 m) down to the valley floor. The slopes are largely covered with debris, with geological outcrops mainly found in large gullies, exposing Pinzgauer phyllites with hydrothermal pyrite mineralization containing varying copper concentrations.

Due to the steep terrain, the survey was conducted in October and November 2019 without a fixed grid. It confirmed four previously known sites (smelting and mining areas) and identified a new prehistoric smelting site (Obj. 04 – Schmelzplatz Gröbenbach) at 1,350–1,360 m altitude. The site was recognized by strong soil discoloration and sparse vegetation. A 6 m high slope revealed evidence of past smelting activities over a 25 m stretch, including slag processing remains, heat-reddened stones, and remnants of a smelting furnace disrupted by forest road construction. A complete slag cake from the furnace was recovered, along with a charcoal sample for dendrochronological analysis.

All documented smelting sites share characteristics with those in Viehhofen, showing evidence of multiple smelting processes and slag refining. The sites were recorded using GNSS, and representative finds were collected for further study (dendrochronology and radiocarbon dating).
DOI: 10.5281/zenodo.13928877
title: Dataset and code accompanying "On mature reflection: ozone damage can be detected in oak trees by hyperspectral reflectance".

description: Hyperspectral dataset and code accompanying the paper: 

On mature reflection: ozone damage can be detected in oak trees by hyperspectral reflectance.
DOI: 10.5281/zenodo.14328228
title: URGED: coefficients and projections of street green space and its heat reduction potential in world cities (pre-release version)

description: URGED: coefficients and projections of street green space and its heat reduction potential in world cities

Pre-release version, February 2025

Refer to the code repository on Github: https://github.com/giacfalk/URGED
DOI: 10.5281/zenodo.14328229
title: URGED: coefficients and projections of street green space and its heat reduction potential in world cities (pre-release version)

description: URGED: coefficients and projections of street green space and its heat reduction potential in world cities

Pre-release version, February 2025

Refer to the code repository on Github: https://github.com/giacfalk/URGED
DOI: 10.5281/zenodo.14856825
title: Dataset for Expanding the Space Biology Community: NASA Open Science Data Repository's Analysis Working Groups - Survey Report

description: This  dataset is an output of the project “A Philosophy of Open Science for Diverse Research Environments” (PHIL_OS) led by Sabina Leonelli, and the case study focused on the National Aeronautics and Space Administration (NASA) Open Science Data Repository (OSDR) led by Paola Castaño. The case study examines the data processing and sharing practices enabled by OSDR and the role of the Analysis Working Groups (AWGs) bringing together users of the data. The overall goal in this study is to shed light on how open science practices are transforming space biology, and the relationship between the repository’s goals of maximizing discovery and democratizing access. This dataset results from a survey conducted between 2023 and 2024 that aimed to characterize the AWG members in terms of their expertise, scientific interests, demographic characteristics, assessments of the repository, and experiences participating in the groups. The survey included 30 questions and 70 respondents completed it. 

This dataset consists of two parts. Part 1 covers questions A and B pertaining to informed consent, and questions that characterize the respondents (Questions 1-21, and 24-27). Part 2 features questions that involve respondents’ assessments, evaluations and/or feedback about OSDR (Questions 22-23 and 28-30). Responses are presented in a different order between the two parts to avoid potential identifiability of the respondents in relation to the views they express. 

The PHIL_OS has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 101001145). More information can be found at https://opensciencestudies.eu
DOI: 10.5281/zenodo.14856826
title: Dataset for Expanding the Space Biology Community: NASA Open Science Data Repository's Analysis Working Groups - Survey Report

description: This  dataset is an output of the project “A Philosophy of Open Science for Diverse Research Environments” (PHIL_OS) led by Sabina Leonelli, and the case study focused on the National Aeronautics and Space Administration (NASA) Open Science Data Repository (OSDR) led by Paola Castaño. The case study examines the data processing and sharing practices enabled by OSDR and the role of the Analysis Working Groups (AWGs) bringing together users of the data. The overall goal in this study is to shed light on how open science practices are transforming space biology, and the relationship between the repository’s goals of maximizing discovery and democratizing access. This dataset results from a survey conducted between 2023 and 2024 that aimed to characterize the AWG members in terms of their expertise, scientific interests, demographic characteristics, assessments of the repository, and experiences participating in the groups. The survey included 30 questions and 70 respondents completed it. 

This dataset consists of two parts. Part 1 covers questions A and B pertaining to informed consent, and questions that characterize the respondents (Questions 1-21, and 24-27). Part 2 features questions that involve respondents’ assessments, evaluations and/or feedback about OSDR (Questions 22-23 and 28-30). Responses are presented in a different order between the two parts to avoid potential identifiability of the respondents in relation to the views they express. 

The PHIL_OS has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 101001145). More information can be found at https://opensciencestudies.eu
DOI: 10.5281/zenodo.14891707
title: Dataset - The role of metal-organic-framework (MOF) in laccase immobilization for advanced biocatalyst formation for use in micropollutants removal

description: This work was supported by the National Science Centre, Poland under the research Grant number 2021/43/B/ST8/01854.
DOI: 10.5281/zenodo.14891708
title: Dataset - The role of metal-organic-framework (MOF) in laccase immobilization for advanced biocatalyst formation for use in micropollutants removal

description: This work was supported by the National Science Centre, Poland under the research Grant number 2021/43/B/ST8/01854.
DOI: 10.15468/dl.u8n3sa
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ficus trachycoma Miq."
 ]
}

 The dataset includes 13 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001416-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pbcgnm
title: Occurrence Download

description: A dataset containing 219 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bombus hypnorum (Linnaeus, 1758)",
 "Country is Japan",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 219 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001417-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8v3vm8
title: Occurrence Download

description: A dataset containing 5430 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Saga pedo (Pallas, 1771)"
 ]
}

 The dataset includes 5430 records from 260 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001418-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.