4.6 Article

Digital data sources and methods for conservation culturomics

Journal

CONSERVATION BIOLOGY
Volume 35, Issue 2, Pages 398-411

Publisher

WILEY
DOI: 10.1111/cobi.13706

Keywords

data‐ driven science; digital content; digital methods; human– nature interactions; research framework; ciencia guiada por datos; contenido digital; interacciones humano‐ naturaleza; marco de trabajo de investigació n; mé todos digitales; 数 据 驱 动 的 科 学 数 字 内 容 数 字 方 法 人 与 自 然 的 互 动 研 究 框 架

Funding

  1. Helsinki Institute of Sustainability Science (HELSUS)
  2. University of Helsinki
  3. Brazilian National Council for Scientific and Technological Development, CNPq [309980/2018-6, 309879/2019-1, 400325/2014-4]
  4. J. E. Purkyne Fellowship of the Czech Academy of Sciences
  5. GIF [I-2519-119.4/2019]
  6. European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program [802933]

Ask authors/readers for more resources

The ongoing loss of biological diversity is caused by unsustainable human behavior, making it crucial to have a thorough understanding of human-nature interactions for successful biodiversity conservation. The emerging field of conservation culturomics aims to utilize digital data sources and methods to study these interactions and provide tools for conservation at various scales. However, technical challenges related to data acquisition, analysis, and biases hinder the wider adoption of culturomics methods.
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.

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