cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13145/bacdive162853.20250331.9.3
title: <i>Gluconobacter</i> <i>oxydans</i> (Henneberg 1897) De Ley 1961

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive162853.20251217.10
title: <i>Gluconobacter</i> <i>oxydans</i> (Henneberg 1897) De Ley 1961

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive162854.20241212.9.2
title: <i>Brevibacterium</i> <i>aurantiacum</i> Gavrish <i>et al.</i> 2005

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive162854.20251217.10
title: <i>Brevibacterium</i> <i>aurantiacum</i> Gavrish <i>et al.</i> 2005

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive162855.20241212.9.2
title: <i>Pediococcus</i> <i>pentosaceus</i> Mees 1934

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive162855.20251217.10
title: <i>Pediococcus</i> <i>pentosaceus</i> Mees 1934

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive162856.20250331.9.3
title: <i>Pseudomonas</i> <i>aeruginosa</i> (Schroeter 1872) Migula 1900

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive162856.20251217.10
title: <i>Pseudomonas</i> <i>aeruginosa</i> (Schroeter 1872) Migula 1900

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15468/dl.85t3b8
title: Occurrence Download

description: A dataset containing 22306 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry MULTIPOLYGON(((-57.992 -27.95655,-57.9959 -27.94029,-58.00186 -27.93952,-58.00352 -27.94017,-58.01832 -27.94243,-58.02441 -27.94893,-58.03435 -27.95108,-58.0334 -27.95551,-58.06803 -27.96263,-58.0692 -27.95824,-58.0765 -27.95974,-58.08382 -27.96104,-58.09526 -27.96431,-58.10919 -27.94776,-58.11545 -27.95205,-58.11429 -27.95348,-58.1153 -27.9542,-58.11255 -27.95756,-58.11446 -27.95892,-58.1105 -27.96377,-58.11348 -27.96572,-58.10353 -27.97796,-58.10372 -27.97828,-58.10439 -27.97749,-58.11202 -27.97646,-58.11806 -27.9713,-58.11886 -27.97028,-58.1205 -27.97227,-58.12208 -27.97665,-58.12645 -27.97964,-58.13225 -27.97834,-58.13307 -27.97589,-58.13812 -27.97568,-58.14106 -27.98068,-58.14184 -27.98201,-58.1419 -27.98489,-58.14136 -27.98679,-58.1416 -27.9914,-58.14235 -27.9927,-58.14483 -27.99377,-58.14652 -27.99561,-58.14526 -27.99702,-58.1461 -27.99734,-58.14564 -27.99791,-58.1531 -28.00565,-58.16037 -28.01468,-58.09455 -28.09652,-58.08151 -28.09143,-58.0763 -28.08875,-58.07138 -28.08574,-58.06047 -28.08098,-58.05582 -28.07752,-58.05049 -28.06788,-58.04661 -28.06333,-58.03309 -28.05304,-58.02444 -28.04522,-58.01947 -28.04263,-58.0137 -28.04093,-58.00706 -28.03787,-58.00293 -28.03589,-57.99688 -28.03401,-57.99111 -28.03272,-57.9869 -28.0319,-57.99649 -27.99536,-58.00109 -27.97781,-57.98578 -27.97079,-57.99032 -27.96406,-57.992 -27.95655)))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 22306 records from 97 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0079070-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13145/bacdive162857.20241212.9.2
title: <i>Leuconostoc</i> <i>mesenteroides</i> subsp. <i>sake</i> Katagiri <i>et al.</i>

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive162857.20251217.10
title: <i>Leuconostoc</i> <i>mesenteroides</i> subsp. <i>sake</i> Katagiri <i>et al.</i>

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive162858.20241212.9.2
title: <i>Pediococcus</i> <i>acidilactici</i> Lindner 1887

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15468/dl.kt94tn
title: Occurrence Download

description: A dataset containing 31272 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mozambique",
 "IucnRedListCategory is one of (CR, EN, VU, NT)",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 31272 records from 208 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014040-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28765646
title: Base de datos de Perfil de ácidos grasos de larvas de <i>Tenebrio molitor</i>

description: Se recolectó la data del perfil de ácidos grasos de larvas de<i> Tenebrio molitor</i> expresado en % de lípidos
DOI: 10.71802/v2apew8p
title: 2024_17 SlowScience - Cosa può accomunare acquacoltura, riso ed insetti? Scopriamolo insieme!

description: Gli attuali sistemi di allevamento del pesce sono poco sostenibili, una delle cause è il contenuto proteico dei mangimi. Al contempo l’industria agroalimentare, es. risicola, genera notevoli quantità di scarti e sottoprodotti. L’allevamento di insetti può riutilizzarli e valorizzarli per produrre proteine alternative per la troticoltura. Questo approccio innovativo è alla base del progetto newRIFF, i primi risultati e le prospettive verranno presentati e discussi.

__Jacopo Bacenetti__ (DSPA UNIMI), __Ilaria Biasato__ (DISAFA UNITO), __Francesco Gai__ (ISPA-CNR). 

Modera __Stefano Predieri__ (IBE-CNR).
DOI: 10.15468/dl.zwjupk
title: Occurrence Download

description: A dataset listing the 4137102 species recorded in GBIF matching the query:
{ }

 The dataset's 4137102 records were derived from 88091 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081535-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.71802/emknbkqx
title: 2024_02 SlowScience - DONNE DI MARE. UNA VITA PER LA SCIENZA

description: Non è trascorso tanto tempo da quando era consuetudine pensare che le donne a bordo delle imbarcazioni
 portasserosfortuna. Oggi una parte significativa della ricerca marina è portata avanti da donne. In mare per
 settimane o mesi contribuiscono in maniera sostanziale a nuove scoperte, a conoscere, comprendere e porsi
 domande nuove e trovare risposte inaspettate.

__Camilla Palmiotto__ (ISMAR CNR) e __Elisa Baldrighi__ (UNR-USA)
 Modera __Francesca Alvisi__ (ISMAR CNR)
DOI: 10.71802/sfyoym4u
title: 2024_03 SlowScience - ATLANTE DELLE TERRE La sensibilità materiale tra ricerca scientifica e poetica pittorica.

description: Una tavola rotonda che si propone, attraverso la presentazione del progetto Atlante delle Terre, di indagare vari aspetti della ricerca scientifica e artistica da una prospettiva filosofica. In questo senso, Atlante delle Terre propone possibilità di interazione tra queste branche del sapere alla ricerca della costruzione di una poetica basata su sedimenti marini provenienti da diverse parti del pianeta.
 La sensibilità del sedimento interpretato come materiale che ci permette di leggere il tempo e di dare spazio a un linguaggio artistico è posta in relazione a un presente in cui il fascino e la paura dell'intelligenza artificiale sono al centro del dibattito pubblico, e in cui al contempo gli esseri umani sono esposti al più grande consumo di immagini virtuali della storia.

 __Luca Bellucci__ (CNR), __Raffaele Milani__ (UNIBO), __Augusto Gadea__ (Artista)
DOI: 10.71802/al62fi2p
title: 2024_18 SlowScience - Eppure non doveva affondare: quando la scienza ha fatto male i conti

description: Come mai le uniche scienze esatte sono la matematica e il senno di poi?
Perché, quando tutto sembrava fatto a regola d'arte, qualcosa è comunque andato storto? Risponderemo a queste domande attraverso le vicende ora tragiche, ora comiche, che raccontano i più clamorosi fallimenti nella scienza e nella tecnologia. Per scoprire che la miglior arma per difendersi dalle cantonate non è (solo) fare scienza bene, ma farla tutti insieme.

__Devis Bellucci__ (UNIMORE)
DOI: 10.5281/zenodo.14396808
title: S121 | EAWAGBBD | Curated Transformation Reactions from Eawag-BBD

description: A set of hand-curated transformation reactions from the Eawag Biocatalysis/Biodegradation Database (Eawag-BBD) from the Eawag-BBD website, collated and curated by Emma Palm, Uni.lu. DOI:  10.1093/nar/gkp771, URL: https://eawag-bbd.ethz.ch/. Dataset DOI: 10.5281/zenodo.14396807.
DOI: 10.5281/zenodo.14396807
title: S121 | EAWAGBBD | Curated Transformation Reactions from Eawag-BBD

description: A set of hand-curated transformation reactions from the Eawag Biocatalysis/Biodegradation Database (Eawag-BBD) from the Eawag-BBD website, collated and curated by Emma Palm, Uni.lu. DOI:  10.1093/nar/gkp771, URL: https://eawag-bbd.ethz.ch/. Dataset DOI: 10.5281/zenodo.14396807.
DOI: 10.15468/dl.z9cjjq
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((90.04916299999999 25.187541, 89.971568 25.181964, 89.895904 25.165372, 89.82405300000001 25.138176, 89.75779900000001 25.101055, 89.69878300000001 25.054929, 89.648459 25.000945, 89.608065 24.940439, 89.578585 24.874912, 89.56073000000001 24.805982, 89.55492099999999 24.73535, 89.56128099999999 24.664758, 89.579634 24.595942, 89.60950800000001 24.530591, 89.650156 24.47031, 89.70056700000001 24.416573, 89.759496 24.370695, 89.825497 24.333796, 89.896953 24.306778, 89.97211900000001 24.290299, 90.04916299999999 24.284762, 90.12620699999999 24.290299, 90.201373 24.306778, 90.272829 24.333796, 90.33883 24.370695, 90.39775899999999 24.416573, 90.44817 24.47031, 90.48881799999999 24.530591, 90.518692 24.595942, 90.53704500000001 24.664758, 90.54340500000001 24.73535, 90.53759599999999 24.805982, 90.519741 24.874912, 90.490261 24.940439, 90.449867 25.000945, 90.39954299999999 25.054929, 90.34052699999999 25.101055, 90.27427299999999 25.138176, 90.202422 25.165372, 90.126758 25.181964, 90.04916299999999 25.187541))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081571-251120083545085/datasets/export for details.
DOI: 10.71802/4yz38gdt
title: 2024_19 SlowScience - Dancalia, tra storia e scienza : la nascita di un oceano

description: Luca Lupi ci condurrà in un viaggio affascinante in una regione unica al mondo trattando diverse tematiche dalla tettonica e la geografia della regione al processo di ominazione e della storia del popolo Afar.
Verranno presentate le esplorazioni geografiche e geologiche italiane nell’area, offrendo un inquadramento geologico complessivo.
Saranno approfonditi il vulcanismo sottomarino, il vulcano Erta Ale con i suoi suggestivi laghi di lava, la Piana del Sale e la singolare area di Dallol, mostrando i più recenti contributi scientifici in merito.

__Luca Lupi__
DOI: 10.15468/dl.a98rxy
title: Occurrence Download

description: A dataset containing 550 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Porthidium dunni"
 ]
}

 The dataset includes 550 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081570-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yfd476
title: Occurrence Download

description: A dataset containing 15605 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((106.19819 -5.7175,105.03508 -6.51887,105.25212 -7.54842,108.4465 -7.99363,110.62246 -8.41658,109.52613 -6.01245,106.19819 -5.7175))",
 "IucnRedListCategory is one of (CR, EN, VU, NT)",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 15605 records from 129 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081567-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ggu4uk
title: Occurrence Download

description: A dataset containing 7256854 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "Geometry POLYGON((52.49303 -33.29203,52.74971 -32.89069,52.87572 -32.68854,53.00016 -32.48543,53.12304 -32.28137,53.24434 -32.07636,53.36405 -31.87043,53.48218 -31.66358,53.5987 -31.45582,53.71362 -31.24718,53.82693 -31.03765,53.93862 -30.82725,54.04868 -30.616,54.16384 -30.39063,54.43521 -30,54.58999 -29.77335,54.75359 -29.53061,54.91567 -29.28685,55.07622 -29.04209,55.23523 -28.79632,55.39269 -28.54956,55.54861 -28.30181,55.70297 -28.0531,55.85576 -27.80342,56.00699 -27.55278,56.15664 -27.30121,56.30472 -27.0487,56.4512 -26.79527,56.5961 -26.54092,56.7394 -26.28567,56.88109 -26.02953,57.02117 -25.7725,57.15965 -25.5146,57.2965 -25.25584,57.42977 -25,57.55702 -24.75207,57.68908 -24.49083,57.8195 -24.22876,57.94828 -23.96589,58.0754 -23.70221,58.20087 -23.43774,58.32468 -23.17249,58.44682 -22.90647,58.56729 -22.63969,58.68609 -22.37215,58.80321 -22.10388,58.91864 -21.83488,59.03239 -21.56516,59.14444 -21.29473,59.25479 -21.02361,59.36344 -20.7518,59.47039 -20.47931,59.57562 -20.20616,59.65375 -20,59.75565 -19.72657,59.85616 -19.45165,59.95494 -19.17609,60.10583 -18.74432,60.80065 -15,61.72849 -10,62.65632 -5,62.8711 -3.84259,63.58416 0,64.38406 4.31061,64.63154 5,66.42641 10,67.71158 13.58012,68.67343 15,71.55322 19.25112,72.06053 20,55.32022 32.62662,55.15553 32.75084,43.2455 42.57583,42.66078 42.17519,39.5703 40.05764,39.51096 40,34.3639 35,29.21684 30,26.26024 27.12787,23.53391 25,18.46434 21.04327,17.45473 20,16.05376 18.55233,52.49303 -33.29203))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Passeriformes",
 "Year 2015-2024"
 ]
}

 The dataset includes 7256854 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081531-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.31028089.v1
title: Understanding fine-scale differences between satellite-derived and ground level temperature across urban landscapes - Dataset

description: Urban areas are emerging as significant hotspots of climatic risk, facing a combination of global temperatures rising, heat waves becoming more intense and severe, and urban heat islands already affecting citizens’ health. Nature-based solutions, such as Urban Forests (UFs), have demonstrated encouraging results in helping urban areas adapt to extreme heat challenges. However, most Urban Temperature studies are based on Land Surface Temperature detected from satellite sensors, which is an imperfect indicator of air temperature perceived by citizens. This study aims to evaluate how strongly Land Surface Temperature (LST) is related to air temperature (AirT), and to assess the strength of such relationship across a distance gradient from forested to built-up areas in an urban setting. We took spatially distributed measurements of AirT over 15 months (June 2023 to September 2024) at a height of 3 meters by deploying 169 AirT sensors across nine urban parks in the city of Milan, Italy. We compared each sensor measurements against LST recorded by Landsat for the same pixel and date and fitted regression models using the distance from forested areas as a co-predictor. We found that LST is not always a reliable predictor of AirT, but its error is highly predictable and dynamic. The bias reverses from an underestimation of AirT under cool conditions to a significant overestimation under hot conditions. The magnitude of this bias intensified with increasing LST and was strongly mediated by local microstructure and vegetation index (NDVI). LST displayed a systematically smaller bias relative to AirT when evaluated against sensors on artificial infrastructure compared to trees, reducing underestimation in cool conditions but intensifying overestimation during heat events.
DOI: 10.6084/m9.figshare.31028089
title: Understanding fine-scale differences between satellite-derived and ground level temperature across urban landscapes - Dataset

description: Urban areas are emerging as significant hotspots of climatic risk, facing a combination of global temperatures rising, heat waves becoming more intense and severe, and urban heat islands already affecting citizens’ health. Nature-based solutions, such as Urban Forests (UFs), have demonstrated encouraging results in helping urban areas adapt to extreme heat challenges. However, most Urban Temperature studies are based on Land Surface Temperature detected from satellite sensors, which is an imperfect indicator of air temperature perceived by citizens. This study aims to evaluate how strongly Land Surface Temperature (LST) is related to air temperature (AirT), and to assess the strength of such relationship across a distance gradient from forested to built-up areas in an urban setting. We took spatially distributed measurements of AirT over 15 months (June 2023 to September 2024) at a height of 3 meters by deploying 169 AirT sensors across nine urban parks in the city of Milan, Italy. We compared each sensor measurements against LST recorded by Landsat for the same pixel and date and fitted regression models using the distance from forested areas as a co-predictor. We found that LST is not always a reliable predictor of AirT, but its error is highly predictable and dynamic. The bias reverses from an underestimation of AirT under cool conditions to a significant overestimation under hot conditions. The magnitude of this bias intensified with increasing LST and was strongly mediated by local microstructure and vegetation index (NDVI). LST displayed a systematically smaller bias relative to AirT when evaluated against sensors on artificial infrastructure compared to trees, reducing underestimation in cool conditions but intensifying overestimation during heat events.
DOI: 10.15468/dl.bbas5x
title: Occurrence Download

description: A dataset containing 485 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chikungunya virus"
 ]
}

 The dataset includes 485 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081575-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18177143
title: Screenrecording and Transcript of an AI Session with ChatGPT-5 mini (OpenAI) on 5.01.2026 about birds on Pillar 43

description: This dataset contains 2 files: Screenrecording and Text transcription of  an AI Session with ChatGPT-5 mini (OpenAI) on 5.01.2026 about birds on Pillar 43 in Gobekli Tepe.

 

This session was initiated and guided by Anatolii Kharchenko. The dataset documents can be used for research and reference purposes.

Non-public link (originally cited): https://chatgpt.com/c/695c1841-8b24-8327-a2a1-d903a0da2d16 

Public link: https://chatgpt.com/share/695f9f89-7158-800d-9c86-f7b608465d84
DOI: 10.5281/zenodo.18177144
title: Screenrecording and Transcript of an AI Session with ChatGPT-5 mini (OpenAI) on 5.01.2026 about birds on Pillar 43

description: This dataset contains 2 files: Screenrecording and Text transcription of  an AI Session with ChatGPT-5 mini (OpenAI) on 5.01.2026 about birds on Pillar 43 in Gobekli Tepe.

 

This session was initiated and guided by Anatolii Kharchenko. The dataset documents can be used for research and reference purposes.

Non-public link (originally cited): https://chatgpt.com/c/695c1841-8b24-8327-a2a1-d903a0da2d16 

Public link: https://chatgpt.com/share/695f9f89-7158-800d-9c86-f7b608465d84
DOI: 10.15468/dl.a8xsbf
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((90.12904399999999 25.247372, 90.051411 25.241795, 89.97571000000001 25.225202, 89.903824 25.198007, 89.837538 25.160885, 89.778493 25.114759, 89.728146 25.060775, 89.687732 25.00027, 89.65823899999999 24.934743, 89.640376 24.865813, 89.63456499999999 24.795182, 89.640929 24.724591, 89.659291 24.655775, 89.68917999999999 24.590425, 89.729848 24.530144, 89.780283 24.476408, 89.83924 24.430531, 89.905272 24.393633, 89.97676199999999 24.366616, 90.051964 24.350137, 90.12904399999999 24.344599, 90.206124 24.350137, 90.281325 24.366616, 90.35281500000001 24.393633, 90.418847 24.430531, 90.477805 24.476408, 90.52824 24.530144, 90.568907 24.590425, 90.598797 24.655775, 90.617159 24.724591, 90.62352199999999 24.795182, 90.617712 24.865813, 90.59984900000001 24.934743, 90.57035500000001 25.00027, 90.52994200000001 25.060775, 90.479595 25.114759, 90.42054899999999 25.160885, 90.354263 25.198007, 90.282377 25.225202, 90.206677 25.241795, 90.12904399999999 25.247372))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081576-251120083545085/datasets/export for details.
DOI: 10.71802/lnl9h95t
title: 2024_20 SlowScience - I Viaggi di Isa: I deserti

description: Isabella Gioia fa ricerca nel campo della astrofisica extragalattica. Fa parte di associazioni professionali quali la International Astronomical Union e l' American Astronomical Society ed il suo nome appare nelle liste ISI degli scienziati più citati al mondo (http://hcr3.isiknowledge.com/). Nel 2004 ha ricevuto dall’allora presidente della Repubblica italiana Carlo Azeglio Ciampi l'onoreficenza di Grande Ufficiale Ordine al Merito della Repubblica Italiana per meriti scientifici.
Tra le sue grandi passioni, oltre all'Astrofisica, ci sono la fotografia e i viaggi. Ha visitato oltre 100 paesi al mondo e realizzato migliaia di foto, passando nell'arco di decenni e oceani dai rullini fotografici al digitale e affinando col tempo le tecniche.

 __Isabella Maria Gioia__ (INAF - IRA)