cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.888794
title: Lithology of sediment core XL, Xan de Llamas, Spain

description: This dataset was archived on 2018-04-04 from the EPD database (http://www.europeanpollendatabase.net).
DOI: 10.1594/pangaea.889475
title: Pollen profile GLENWEST, Glen West, United Kingdom

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2007
DOI: 10.1594/pangaea.889476
title: Pollen profile GRASPET, Graspet, France

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 1982
DOI: 10.1594/pangaea.888795
title: Lithology of sediment core YARNYSH3, Lake Yarnyshnoe, Russia

description: This dataset was archived on 2018-04-04 from the EPD database (http://www.europeanpollendatabase.net).
DOI: 10.1594/pangaea.888796
title: Lithology of sediment core ZANOGUTI, Taul Zanogutii, Romania

description: This dataset was archived on 2018-04-04 from the EPD database (http://www.europeanpollendatabase.net).
DOI: 10.1594/pangaea.889477
title: Pollen profile GWB, Beckton, United Kingdom

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2009
DOI: 10.1594/pangaea.889243
title: Pollen profile CAVALLAR, Bergeries de Cavallara, France

description: This dataset was archived on 2018-04-26 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 1971
DOI: 10.1594/pangaea.889479
title: Pollen profile HAYLEYWO, Hayley Wood, United Kingdom

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2012
DOI: 10.1594/pangaea.889480
title: Pollen profile HEINRICH, Heinrichswalder Damm, Germany

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 1968
DOI: 10.1594/pangaea.889481
title: Pollen profile HORST22, Horst, Germany

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2006
DOI: 10.1594/pangaea.889482
title: Pollen profile HUMELLES, Les Humelles, France

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 1999
DOI: 10.1594/pangaea.888798
title: Lithology of sediment core ZL11, Zibakenar Lagoon, Iran

description: This dataset was archived on 2018-04-04 from the EPD database (http://www.europeanpollendatabase.net).
DOI: 10.1594/pangaea.889247
title: Pollen profile CESARIU, Cesariu-Taga, Romania

description: This dataset was archived on 2018-04-26 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 1987
DOI: 10.1594/pangaea.889483
title: Pollen profile HUTTENDA, Hüttendamm, Germany

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 1968
DOI: 10.1594/pangaea.889486
title: Pollen profile IAZ, Iaz, Romania

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2013
DOI: 10.1594/pangaea.889487
title: Pollen profile ISPANI2, Ispani 2, Georgia

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2009
DOI: 10.1594/pangaea.889012
title: Age determination of sediment core CP14, Caspian Sea

description: This dataset was archived on 2018-04-23 from the EPD database (http://www.europeanpollendatabase.net).
DOI: 10.1594/pangaea.889013
title: Age determination of sediment core CP18, Caspian Sea

description: This dataset was archived on 2018-04-23 from the EPD database (http://www.europeanpollendatabase.net).
DOI: 10.1594/pangaea.889489
title: Pollen profile ZANOGUTI, Taul Zanogutii, Romania

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 1994
DOI: 10.5281/zenodo.10045454
title: Dataset of ICITS'24 - article "Ethics and AI in Higher Education: A Study on Students' Perceptions"

description: This dataset encompasses responses from first-year undergraduate students enrolled in an ICT program at Fluminense Federal University. The survey was completed by 61 students via an online platform between June 28th and July 4th, 2023. The findings were subsequently published in an article titled "Ethics and AI in Higher Education: A Study on Students' Perceptions" presented at the ICITS'24 conference.

 

Article abstract:This initial study investigates the complex ethical concerns surrounding the integration of artificial intelligence (AI) in education, with a particular focus on undergraduate students' perceptions of AI tools in their academic efforts. A notable issue is the educational application of these tools, coupled with a pressing need for comprehensive public policies that ensure ethics and privacy are protected. Through qualitative research involving 61 students in an Information and Communication Technology (ICT) course, we explored the teaching of ethics related to the use of AI tools in an academic context. Our findings reveal a tendency among students to favor commercial AI tools that are not tailored for educational use, pointing to a potential shortfall in the educational AI domain. This study underscores the importance of promoting critical thinking and the responsible use of AI tools in academic settings. However, it is crucial to conduct further research with university students and instructors to refine and improve educational frameworks utilizing AI tools.
DOI: 10.5281/zenodo.10048634
title: Dataset of ICITS'24 - article "Ethics and AI in Higher Education: A Study on Students' Perceptions"

description: This dataset encompasses responses from first-year undergraduate students enrolled in an ICT program at Fluminense Federal University. The survey was completed by 61 students via an online platform between June 28th and July 4th, 2023. The findings were subsequently published in an article titled "Ethics and AI in Higher Education: A Study on Students' Perceptions" presented at the ICITS'24 conference.

 

Article abstract:This initial study investigates the complex ethical concerns surrounding the integration of artificial intelligence (AI) in education, with a particular focus on undergraduate students' perceptions of AI tools in their academic efforts. A notable issue is the educational application of these tools, coupled with a pressing need for comprehensive public policies that ensure ethics and privacy are protected. Through qualitative research involving 61 students in an Information and Communication Technology (ICT) course, we explored the teaching of ethics related to the use of AI tools in an academic context. Our findings reveal a tendency among students to favor commercial AI tools that are not tailored for educational use, pointing to a potential shortfall in the educational AI domain. This study underscores the importance of promoting critical thinking and the responsible use of AI tools in academic settings. However, it is crucial to conduct further research with university students and instructors to refine and improve educational frameworks utilizing AI tools.
DOI: 10.1594/pangaea.889249
title: Pollen profile CHALKNAL, Chalkney wood, United Kingdom

description: This dataset was archived on 2018-04-26 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2012
DOI: 10.1594/pangaea.889019
title: Age determination of sediment core CP21, Caspian Sea

description: This dataset was archived on 2018-04-23 from the EPD database (http://www.europeanpollendatabase.net).
DOI: 10.1594/pangaea.889252
title: Pollen profile CHALKNVE, Chalkney wood, United Kingdom

description: This dataset was archived on 2018-04-26 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2012
DOI: 10.1594/pangaea.889254
title: Pollen profile CHAUMETE, La Chaumette, France

description: This dataset was archived on 2018-04-26 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 1978
DOI: 10.1594/pangaea.889492
title: Pollen profile KELLYSLO, Kelly's Lough, Ireland

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2007
DOI: 10.1594/pangaea.889255
title: Pollen profile CICA1, Cica Mica, Romania

description: This dataset was archived on 2018-04-26 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 1989
DOI: 10.1594/pangaea.889257
title: Pollen profile CICA1A, Cica Mica, Romania

description: This dataset was archived on 2018-04-26 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 1977
DOI: 10.1594/pangaea.889258
title: Pollen profile CICA1B, Cica Mica, Romania

description: This dataset was archived on 2018-04-26 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 1977
DOI: 10.1594/pangaea.889032
title: Age determination of sediment core TSCHEPPA, Lej da la Tscheppa, Switzerland

description: This dataset was archived on 2018-04-23 from the EPD database (http://www.europeanpollendatabase.net).
DOI: 10.1594/pangaea.889493
title: Pollen profile KHARINEI, Lake Kharinei, Russia

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2007
DOI: 10.1594/pangaea.889495
title: Pollen profile KHARTYM, Man'inskii Khartym, Russia

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2014
DOI: 10.1594/pangaea.889262
title: Pollen profile CLARABOG, Clara Bog, Ireland

description: This dataset was archived on 2018-04-26 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 1999
DOI: 10.1594/pangaea.889496
title: Pollen profile KHORPIYA, Khorpyia, Russia

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2007
DOI: 10.1594/pangaea.889497
title: Pollen profile KILCURLE, Kilcurley Wood, Ireland

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2012
DOI: 10.1594/pangaea.889498
title: Pollen profile KLUKVA, Klukva peatland, Russia

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2016
DOI: 10.1594/pangaea.889499
title: Pollen profile KUMATA1, Kumata, Bulgaria

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2015
DOI: 10.1594/pangaea.889500
title: Pollen profile WELSH, Ogof Draenen cave, United Kingdom

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2005
DOI: 10.1594/pangaea.889501
title: Pollen profile WILLIA17, William King Flour Mill, United Kingdom

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2014
DOI: 10.1594/pangaea.889502
title: Pollen profile WILLIA25, William King Flour Mill, United Kingdom

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2014
DOI: 10.1594/pangaea.889503
title: Pollen profile WTP, Woolwich Trade Park, United Kingdom

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 2009
DOI: 10.1594/pangaea.889504
title: Pollen profile VACCAJA1, Pozzine des bergeries de Vaccaja, France

description: This dataset was archived on 2018-05-03 from the EPD database. (http://www.europeanpollendatabase.net). Date analyzed: 1972
DOI: 10.1594/pangaea.888608
title: Lithology of sediment core MAI, El Maíllo mire, Spain

description: This dataset was archived on 2018-04-04 from the EPD database (http://www.europeanpollendatabase.net).
DOI: 10.1594/pangaea.888609
title: Lithology of sediment core MAKARX, Lake Makarovskoye, Russia

description: This dataset was archived on 2018-04-04 from the EPD database (http://www.europeanpollendatabase.net).
DOI: 10.1594/pangaea.888611
title: Lithology of sediment core MALIQS1, Lake Maliq, Albania

description: This dataset was archived on 2018-04-04 from the EPD database (http://www.europeanpollendatabase.net).
DOI: 10.1594/pangaea.888613
title: Lithology of sediment core MDOLGOE, Myshetskoe-Dolgoe, Russia

description: This dataset was archived on 2018-04-04 from the EPD database (http://www.europeanpollendatabase.net).
DOI: 10.1594/pangaea.888618
title: Lithology of sediment core ML9811, Lake Manyas, Turkey

description: This dataset was archived on 2018-04-04 from the EPD database (http://www.europeanpollendatabase.net).
DOI: 10.1594/pangaea.888621
title: Lithology of sediment core MONGANBO, Mongan Bog, Ireland

description: This dataset was archived on 2018-04-04 from the EPD database (http://www.europeanpollendatabase.net).
DOI: 10.15156/bio/sh460918.07fu
title: SH460918.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1828937.08fu
title: SH1828937.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1828938.08fu
title: SH1828938.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1828939.08fu
title: SH1828939.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh460919.07fu
title: SH460919.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh460920.07fu
title: SH460920.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh460921.07fu
title: SH460921.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1828940.08fu
title: SH1828940.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1828941.08fu
title: SH1828941.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.