Keynote Speech 2: Blockchain based Data science and data engineering: (Human) Ecology in the Digital Age

Abstract

Many have extolled the virtues of the data age and encouraged the proliferation of data; from social media on mobile phones to direct sensor integration into distributed BLOB databases. Despite this ubiquity, ecologists typically collect data manually, with a note pad and pen, and this can lead to an array of practical complications; note pads get wet, lost, or damaged, writing is illegible, or spelling is incorrect. Should the notepad survive, the manual data must be transcribed, and is often then isolated in a project-specific dataset. Thanks to the open science movement, there is growing proliferation of environmental data, however project-level regional and sub-regional data remains fragmented, and is frequently un-verified, and asynchronous. Modern digital collection techniques such as UAV, IoT sensors, remote cameras, eDNA, and acoustic sensors, are assisting in mitigating the real-time issue and limited spatial scope of ecological and environmental data collection deployment at scale. These digital techniques can record huge volumes of data in a distributed way and allow the collection of nearreal time data across an entire region using various competitive agents. Despite these capacities however, this form of data is typically unstructured (collected by multiple parties, in multiple ways), isolated, and remains at the project level. For ecological and environmental data to be relevant and used to inform management decisions, it needs to have the following properties: validity, volume, velocity, variety, veracity, value, distribution, and be in near real-time. Blockchain represents a valuable opportunity in this space. With collaborators, we are developing a consolidated, tamper proof, generator-owned, data repository, which uses micropayments as an incentive-based system for collection, verification, indexing, and dissemination. This system provides micropayment access to volumes (or snippets) of high-quality data, which is verified, indexed and instantly auditable. It is proposed that this self-serve model of a data service will allow local, regional, and continental based environmental and ecological modelling and monitoring to proliferate beyond previous limitations and effectively address pressing global issues such as language, cultural, and biodiversity loss.Biography. Daniel Keane is a tropical ecologist, born and raised in the Wet Tropics region of Queensland, Australia. He is the co-founder and managing director of Predict Ecology, an environmental and ecological consulting firm with a focus on rigorous science, real-world data, and predictive modelling. During his career, Daniel has been involved with a variety of projects ranging from environmental surveys, mine closure and rehabilitation, tropical ecosystem restoration and conservation, and environmental modelling. Working in the resources, mining, and infrastructure sectors, he has unique insights into multi-discipline environmental management and sustainable development planning. Living in the Wet Tropics Area, Daniel developed appreciation ...