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Eco-ISEA3H, a machine learning ready spatial database for ecometric and species distribution modeling

Year of publication

2023

Authors

Mechenich, Michael Francis; Zliobaite, Indre

Organizations and authors

University of Helsinki

Zliobaite Indre

Mechenich Michael Francis

Publication type

Publication format

Article

Parent publication type

Journal

Article type

Original article

Audience

Scientific

Peer-reviewed

Peer-Reviewed

MINEDU's publication type classification code

A1 Journal article (refereed), original research

Publication channel information

Journal

Scientific data

Parent publication name

Scientific data

Volume

10

Issue

1

Article number

77

ISSN

2052-4463

​Publication forum

82577

​Publication forum level

1

Open access

Open access in the publisher’s service

Yes

Open access of publication channel

Fully open publication channel

Self-archived

Yes

License of the self-archived publication

CC BY

Other information

Fields of science

Computer and information sciences; Geosciences; Ecology, evolutionary biology

Publication country

United Kingdom

Internationality of the publisher

International

Language

English

International co-publication

No

Co-publication with a company

No

DOI

10.1038/s41597-023-01966-x

The publication is included in the Ministry of Education and Culture’s Publication data collection

Yes