Brandon Whitehead

Massey University campus

Te Papeioia Palmerston North, Manawatū

I’m an Earth and geospatial data scientist working at the intersection of data science, knowledge representation, and machine-aided discovery. Much of my work centers on making Earth and environmental data more findable, interoperable, and meaningful — for humans and machines — through the development of shared vocabularies and richer semantic models of domain knowledge..

I am an Environmental Data Scientist with the Manaaki Whenua group which is part of the relatively newly minted Bioeconomy Science Institute in Aotearoa New Zealand, where I lead work on custom generative AI tooling, NLP for metadata creation and data-munging, and semantic artifact development (i.e. vocabularies, thesauri, ontologies, etc.).

I like to think of myself as a knowmad (i.e. a nomadic knowledge worker). As such, I am a Fellow at the Ronin Institute for Independent Scholarship (RIIS) 2.0, reflecting a deep commitment to independent and globally distributed research. I’m also trying desperately to complete a PhD in the Department of Environmental Engineering Sciences at the University of Florida.

I have been an active contributor to broader Earth science related communities focusing on semantic web and open science for over a decade — co-founding EarthArXiv, co-chairing ESIP’s Semantic Technologies Committee and, more recently, its Soil Ontology and Informatics Cluster, and contributing to the SWEET ontology, among others. I am convinced the infrastructure of science matters as much as the discoveries it enables.

This site remains a work in progress.

selected publications

39 Hints to Facilitate the Use of Semantics for Data on Agriculture and Nutrition

Caterina Caracciolo, Sophie Aubin, Clément Jonquet, Emna Amdouni, Romain David, Leyla Garcia, Brandon Whitehead, Catherine Roussey, Armando Stellato, and Ferdinando Villa

Data Science Journal, Dec 2020

Abs DOI

In this paper, we report on the outputs and adoption of the Agrisemantics Working Group of the Research Data Alliance (RDA), consisting of a set of recommendations to facilitate the adoption of semantic technologies and methods for the purpose of data interoperability in the field of agriculture and nutrition. From 2016 to 2019, the group gathered researchers and practitioners at the crossing point between information technology and agricultural science, to study all aspects in the life cycle of semantic resources: conceptualization, edition, sharing, standardization, services, alignment, long term support. First, the working group realized a landscape study, a study of the uses of semantics in agrifood, then collected use cases for the exploitation of semantics resources – a generic term to encompass vocabularies, terminologies, thesauri, ontologies. The resulting requirements were synthesized into 39 “hints” for users and developers of semantic resources, and providers of semantic resource services. We believe adopting these recommendations will engage agrifood sciences in a necessary transition to leverage data production, sharing and reuse and the adoption of the FAIR data principles. The paper includes examples of adoption of those requirements, and a discussion of their contribution to the field of data science.
Global agricultural concept space: lightweight semantics for pragmatic interoperability

Thomas Baker, Brandon Whitehead, Ruthie Musker, and Johannes Keizer

npj Science of Food, Sep 2019

Abs DOI

Progress on research and innovation in food technology depends increasingly on the use of structured vocabularies—concept schemes, thesauri, and ontologies—for discovering and re-using a diversity of data sources. Here, we report on GACS Core, a concept scheme in the larger Global Agricultural Concept Space (GACS), which was formed by mapping between the most frequently used concepts of AGROVOC, CAB Thesaurus, and NAL Thesaurus and serves as a target for mapping near-equivalent concepts from other vocabularies. It provides globally unique identifiers, which can be used as keywords in bibliographic databases, tags for web content, for building lightweight facet schemes, and for annotating spreadsheets, databases, and image metadata using synonyms and variant labels in 25 languages. The minimal semantics of GACS allows terms defined with more precision in ontologies, or less precision in controlled vocabularies, to be linked together making it easier to discover and integrate semantically diverse data sources.
Harmonizing GCW Cryosphere Vocabularies with ENVO and SWEET. Towards a General Model for Semantic Harmonization

Ruth Duerr, Pier Luigi Buttigieg, Gary Berg Cross, Kai Lewis Blumberg, Brandon Whitehead, Nancy Wiegand, and Kate Rose

Data Science Journal, Sep 2024

Abs DOI

This paper presents the specific process used by members of the Earth Science Information Partners (ESIP) Semantic Harmonization Cluster, to harmonize cryospheric terms gathered by the Global Cryosphere Watch (GCW) with two leading semantic resources used in the Earth and Environmental science communities}—the Semantic Web for Earth and Environmental Terminology (SWEET) and the Environment Ontology (ENVO). This process led to updates to both ENVO and SWEET as well as the development of an alignment file relating cryospheric terms in ENVO to those in SWEET. In addition, we summarize several leading practices which may be applied to other projects/realms within Earth and Environmental science and perhaps beyond, as well as suggest a generalized process for doing so. This paper describes the history of the effort, the technical and decision-making processes used to resolve differences between semantic resources, and describes several issues encountered, with a focus on those that were addressed during the effort. Lessons learned, examples of the problems encountered and a summary of resulting leading practices growing out of this work is provided.
GCMD _enhanced_

Brandon Whitehead

Sep 2024

Abs DOI

First crack at detangling GCMD’s multiple dupilcate concepts