Canadian Forest Service Publications

Big data in forest bioeconomy: The good, the bad and the ugly. 2016. Mansuy, N. J-For. 5: 6-15.

Year: 2016

Issued by: Laurentian Forestry Centre

Catalog ID: 36536

Language: English

Availability: PDF (request by e-mail)

Mark record


The forest sector is expected to become an integral component of the emerging bioeconomy by offering unique advantages that can fulfill a number of economic, social, and environmental objectives. “Big Data” has emerged as a used to describe the use and benefits of unparalleled access to digital information that represents unprecedented opportunities for advancing science and supporting forest management through data-intensive approaches. This short paper puts into perspective the global challenge of acquiring and sharing multi-dimensional data, be they socio-economic or environmental in nature. Despite the explosion in environmental Big Data derived from global-scale forest monitoring, the deficit in social and economic data and the lack of their integration into a multi-dimensional decision-making system may limit the full potential of the forest’s contribution to the bioeconomy, including both marketed and non-marketed goods and services. In consequence, it is crucial to support sustainable forest management and flexible value chains with data-driven analyses and cross-disciplinary approaches, not only to boost the shift from traditional forestry towards the bioeconomy, but also to improve environmental, social, and economic sustainability in the forest sector.

Plain Language Summary

This study demonstrates the need for increased and more diverse forest-related data, both environmental and socioeconomic, as well as for continued data analysis so as to promote the contribution of forests to the bioeconomy. It is all the more important to pool and share these data as climate change and global needs for forest products will lead to increased pressure on forests.

This is not a comprehensive study of all the data available in the forest sector; rather, the author identifies the main fields for which data is lacking. The study also specifies the obstacles to acquiring and sharing data so that the information can be incorporated into decision-making processes.