Georgina Cherry


Data Scientist at vHive
BSc MSc MCLIP
9am-5pm, Monday to Friday

Biography

Areas of specialism

digital innovation; animal health; data management; information management; taxonomy; ontology; data science; information science; information retrieval

My qualifications

2013
MCLIP Chartered Member of CILIP
CILIP
2004
MSc Information Science
City University
2001
BSc Biochemistry (Toxicology)
University of Surrey

Previous roles

2017 - 2018
Marketing Data Manager
University of Surrey
2016 - 2017
Digital Content Assistant
University of Surrey
2012 - 2016
Taxonomy Specialist
Artesian Solutions
2016 - 2016
Product Marketer
Artesian Solutions
2008 - 2012
Information Manager
Hibu (Yell.com)
2004 - 2008
Information Officer
Council of Mortgage Lenders
2002 - 2003
Library Assistant
University of Surrey

Academic networks

    Research

    Research interests

    Research projects

    Georgina Cherry and Ruth Alafiatayo standing in front of a banner in Zoetis' diagnostic lab training centre in Lyon

    My publications

    Publications

    GEORGINA CHERRY, Nikolai Kazantsev, Andrea Wright, TRAVIS LEE STREET, Kevin Wells, ALASDAIR JAMES CHARLES COOK, Alan Brown (2022)SEMANTIC DATA INNOVATION HUBS: ANSWER AS A SERVICE

    The open data market size is estimated at €184 billion and forecast to reach between €199.51 and €334.21 billion in 2025. In this paper, we conceptualise the semantic data innovation platform, which will be able to answer inter-disciplinary questions via semantic reasoning over open data. We use 750 open animal healthcare datasets to exemplify this work, covering mainly poultry, swine, ruminants, and other livestock, which are complemented by open data from complementary domains, such as geographic location, medicine and virology. We aggregate the domain knowledge (classes) and enable the logical links (properties) between these classes. The prototype encapsulates the complexity of animal healthcare knowledge into ontology, which can answer complex questions using semantic reasoning on the datasets (answer-as-a-service).

    C Roberts, BRYONY ARMSON, D Bartram, Z Belshaw, Hannah Capon, GEORGINA CHERRY, Laura Gonzalez Villeta, SHONA LOUISE MCINTYRE, Isaac Odeyemi, ALASDAIR JAMES CHARLES COOK (2021)Construction of a Conceptual Framework for Assessment of Health-Related Quality of Life in Dogs With Osteoarthritis, In: Frontiers in Veterinary Science8741864 Frontiers Media S.A

    An owner's ability to detect changes in the behavior of a dog afflicted with osteoarthritis (OA) may be a barrier to presentation, clinical diagnosis and initiation of treatment. Management of OA also relies upon an owner's ability to accurately monitor improvement following a trial period of pain relief. The changes in behavior that are associated with the onset and relief of pain from OA can be assessed to determine the dog's health-related quality of life (HRQOL). HRQOL assessments are widely used in human medicine and if developed correctly can be used in the monitoring of disease and in clinical trials. This study followed established guidelines to construct a conceptual framework of indicators of HRQOL in dogs with OA. This generated items that can be used to develop a HRQOL assessment tool specific to dogs with OA. A systematic review was conducted using Web of Science, PubMed and Scopus with search terms related to indicators of HRQOL in dogs with osteoarthritis. Eligibility and quality assessment criteria were applied. Data were extracted from eligible studies using a comprehensive data charting table. Resulting domains and items were assessed at a half-day workshop attended by experts in canine osteoarthritis and quality of life. Domains and their interactions were finalized and a visual representation of the conceptual framework was produced. A total of 1,264 unique articles were generated in the database searches and assessed for inclusion. Of these, 21 progressed to data extraction. After combining synonyms, 47 unique items were categorized across six domains. Review of the six domains by the expert panel resulted in their reduction to four: physical appearance, capability, behavior, and mood. All four categories were deemed to be influenced by pain from osteoarthritis. Capability, mood, and behavior were all hypothesized to impact on each other while physical appearance was impacted by, but did not impact upon, the other domains. The framework has potential application to inform the development of valid and reliable instruments to operationalize measurement of HRQOL in canine OA for use in general veterinary practice to guide OA management decisions and in clinical studies to evaluate treatment outcomes.