Digital data sources and methods for conservation culturomics.

0553262 - BC 2022 RIV US eng J - Článek v odborném periodiku
Correia, R.A. - Ladle, R. - Jaric, Ivan - Malhado, A.C.M. - Mittermeier, J.C. - Roll, U. - Soriano-Redondo, A. - Verissimo, D. - Fink, C. - Hausmann, A. - Guedes-Santos, J. - Vardi, R. - Di Minin, E.
Digital data sources and methods for conservation culturomics.
Conservation Biology. Roč. 35, č. 2 (2021), s. 398-411. ISSN 0888-8892. E-ISSN 1523-1739
Grant CEP: GA AV ČR(CZ) Fellowship J. E. Purkyně
Grant ostatní: AV ČR(CZ) Fellowship J. E. Purkyně
Program: Fellowship J. E. Purkyně
Institucionální podpora: RVO:60077344
Klíčová slova: digital content * data driven science * digital methods * human-nature interactions * research framework
Obor OECD: Biodiversity conservation
Impakt faktor: 7.563, rok: 2021
Způsob publikování: Open access
https://doi.org/10.1111/cobi.13706

Ongoing loss of biological diversity is primarily the result of unsustainable human behavior. Thus, the long-term success of biodiversity conservation depends on a thorough understanding of human-nature interactions. Such interactions are ubiquitous but vary greatly in time and space and are difficult to monitor efficiently at large spatial scales. However, the Information Age also provides new opportunities to better understand human-nature interactions because many aspects of daily life are recorded in a variety of digital formats. The emerging field of conservation culturomics aims to take advantage of digital data sources and methods to study human-nature interactions and thus to provide new tools for studying conservation at relevant temporal and spatial scales. Nevertheless, technical challenges associated with the identification, access, and analysis of relevant data hamper the wider adoption of culturomics methods. To help overcome these barriers, we propose a conservation culturomics research framework that addresses data acquisition, analysis, and inherent biases. The main sources of culturomic data include web pages, social media, and other digital platforms from which metrics of content and engagement can be obtained. Obtaining raw data from these platforms is usually desirable but requires careful consideration of how to access, store, and prepare the data for analysis. Methods for data analysis include network approaches to explore connections between topics, time-series analysis for temporal data, and spatial modeling to highlight spatial patterns. Outstanding challenges associated with culturomics research include issues of interdisciplinarity, ethics, data biases, and validation. The practical guidance we offer will help conservation researchers and practitioners identify and obtain the necessary data and carry out appropriate analyses for their specific questions, thus facilitating the wider adoption of culturomics approaches for conservation applications.
Trvalý link: http://hdl.handle.net/11104/0328241