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Dr Lucy Bastin - Aston University. Birmingham, , GB

Dr Lucy Bastin Dr Lucy Bastin

Reader, Computer Science | Aston University

Birmingham, UNITED KINGDOM

Dr Bastin's teaching includes data analytics, software engineering and professional aspects of computing.

Media

Publications:

Documents:

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Videos:

Mapping and Reliable Information: Lucy Bastin at TEDxBrum BES/CCI Symposium: Making a Difference in Conservation - Lucy Bastin

Audio/Podcasts:

Social

Biography

Dr Bastin is a Reader in the School of Engineering and Applied Science. Her teaching includes data analytics, software engineering and professional aspects of computing.

She is a highly interdisciplinary researcher and has developed an international collaboration network including microbiologists, primary care trusts and the Health Protection Agency, economists and social scientists, forensic linguists, protected area managers, conservation policy makers and local wildlife trusts.

Areas of Expertise (4)

Data Analytics

Software Engineering

Engineering

Applied Sciences

Accomplishments (1)

Finalist, Women in Tech Award

2021

Education (3)

University of Birmingham: PhD, Spatial Urban Ecology 1996

University of Leicester: MSc, Geographical Information Science 1995

University of Nottingham: BSc, Zoology 1991

Affiliations (1)

  • Fellow of the Higher Education Academy

Media Appearances (1)

Mapping and Reliable Information: Lucy Bastin at TEDxBrum

TEDx  online

2013-07-19

Lucy Bastin initially dropped out of University and stumbled onto a job creation scheme at the Birmingham and Black Country Wildlife Trust which inspired her with a love of urban wildlife habitats and an appreciation of their contribution to biodiversity. Subsequent attempts at higher education were more successful, and she is now a Senior Lecturer in Computer Science at the University of Aston, applying spatio-temporal analysis to ecological and environmental challenges such as conservation planning and disease monitoring. She has a particular interest in how data and scientific models can be shared over the Web to enable cross-disciplinary problem solving, and in the ways that we assess and evaluate the reliability of these shared resources.

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Articles (2)

Post-2020 Global Biodiversity Framework: Support and a Pathway for Inland Water Ecosystems in the ‘30 by 30’Target, Monitoring Framework and Implementation

The Nature Conservancy

2022 Key Recommendations: Explicit inclusion of inland water* ecosystems in the area-based conservation targets and indicators is critical to recover and safeguard the most threatened and least protected ecosystems and biodiversity on the planet. This briefing provides an overview of the evidence for this recommendation, a global baseline estimate of their current protection status and recommended pathways for inclusion, beginning with a call for the following changes to include inland waters in the final text of the Post-2020 Global Biodiversity Framework: An Information Document addressing these topics in detail will be produced in coordination with and for use by Parties and organizations in advance of COP15. The consortium of organizations supporting this brief is committed to operationalizing the recommendations outlined below.

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International Community Guidelines for Sharing and Reusing Quality Information of Individual Earth Science Datasets

OSF Preprints for Earth Science Information Partners (ESIP)

2022 Under the auspices of the Earth Science Information Partners (ESIP) and with collaboration among members of the ESIP Information Quality Cluster (IQC), the Barcelona Supercomputing Center (BSC) Evaluation and Quality Control (EQC) team, and the Australia/New Zealand Data Quality Interest Group (AU/NZ DQIG), a community effort has been undertaken by international Earth Science domain experts. The objective of this effort is to develop global community guidelines with practical recommendations to promote the representation, sharing and reuse of quality information at the dataset level, leveraging the experiences and expertise of a team of interdisciplinary domain experts and community best practices. The community guidelines are inspired by the guiding principles of findability, accessibility, interoperability, and reusability (FAIR) and aim to help stakeholders such as science data centers, repositories, data producers and publishers, data managers and stewards, etc., i) to capture, des.....

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