research outputs

2025

1. Interoperable and Federated Vocabulary Services

   Clement Jonquet, Brandon Whitehead, Nicholas Car, Alexandra Kokkinaki, Rob Atkinson, Christelle Pierkot, Naouel Karam, John Graybeal, and Megan Wong

   In SciDataCon 2025, Oct 2025

   Abs

   SciDataCon 2025 Programme Daily programme schedules for SciDataCon 2025 have been published. IDW 2025 full programme can be consulted at: https://idw2025.org/program-at-a-glance/ About SciDataCon SciDataCon 2025 is an integral part of International Data Week 2025 taking place in Brisbane, Australia, 13-16 October 2025. SciDataCon is organized by the International Science Council (ISC)’s two data bodies: CODATA (the ISC’s Committee on Data) and the World Data System (WDS). SciDataCon is the...

2. Towards Place-Based Semantics for Polar Research: Uplifting the SCAR Gazetteer as a Foundation for Data Integration

   Brandon Whitehead

   In Polar Data Forum VI, Oct 2025
3. Unifying Historical Antarctic Biogeographic Data using SCAR Gazetteer and a Discrete Global Grid System

   Brandon Whitehead and Charles Lee

   In Polar Data Forum VI, Oct 2025
4. SoilDRaH: Soil data rescue and harmonization

   Katherine Todd-Brown, Layla Kalandjian, Colby Green, Savannah Scott, Mirah Blanchard, Brandon Whitehead, and Vaasuki Marupaka

   Oct 2025

2024

1. 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, Oct 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.

2. Aotearoa New Zealand Standard Land Use Classification (NZSLUC)

   Richard Law, Brandon Whitehead, and James Ardo

   Jul 2024

   DOI
3. GCMD _enhanced_

   Brandon Whitehead

   Jul 2024

   Abs DOI

   First crack at detangling GCMD’s multiple dupilcate concepts

4. Brandon Whitehead - History of People of ESIP

   Brandon Whitehead

   Aug 2024

   Abs

   Brandon Whitehead is a participant in the Earth Science Information Partners (ESIP) community. The interview is part of a series, gathered in July 2024, to share stories about ESIP, different careers in Earth science data, and interdisciplinary collaborations.

5. An Unexpected Journey

   Brandon Whitehead

   Jul 2024

2023

1. The BioWhere Project: Unlocking the Potential of Biological Collections Data

   Kristin Stock, Kalana Wijegunarathna, Christopher B. Jones, Hone Morris, Pragyan Das, David Medeckyj-Scott, and Brandon Whitehead

   GI_Forum, Jul 2023

   https://doi.org/10.1553/giscience2023_01_s3

   Abs DOI

   Vast numbers of biological specimens (e.g. flora, fauna, soils) are stored in collections globally. Many of these have only a natural-language location description, such as ‘200ft above and south of main highway, 1.1 miles west of Porters Pass’, and numerical coordinates are unknown. The BioWhere project is pioneering methods to automatically determine the geographic coordinates (georeferences) of complex location descriptions. Particular challenges are posed by the variable accuracy of recent and historical data that might be used to train models to predict geographic coordinates from the natural-language descriptions; by the presence of historical place names in the descriptions that are not stored in existing gazetteers; and by the vague and context-sensitive nature (e.g. above, on, south of) of the descriptions. We are addressing these challenges by extending the latest transformer-based deep learning models to parse locality descriptions, and to build models for specific spatial terms that incorporate geographic context and data quality to more accurately predict georeferences. We also describe a gazetteer that contains enriched cultural content to support georeferencing of historical records, and to serve as a store of New Zealand Māori cultural knowledge for future generations.

2. Data sharing and ontology use among agricultural genetics, genomics, and breeding databases and resources of the AgBioData Consortium

   Jennifer L Clarke, Laurel D Cooper, Monica F Poelchau, Tanya Z Berardini, Justin Elser, Andrew D Farmer, Stephen Ficklin, Sunita Kumari, Marie-Angélique Laporte, Rex T Nelson, Rie Sadohara, Peter Selby, Anne E Thessen, Brandon Whitehead, and Taner Z Sen

   Database, Jul 2023

   Abs DOI

   Over the last couple of decades, there has been a rapid growth in the number and scope of agricultural genetics, genomics and breeding databases and resources. The AgBioData Consortium (https://www.agbiodata.org/) currently represents 44 databases and resources (https://www.agbiodata.org/databases) covering model or crop plant and animal GGB data, ontologies, pathways, genetic variation and breeding platforms (referred to as ‘databases’ throughout). One of the goals of the Consortium is to facilitate FAIR (Findable, Accessible, Interoperable, and Reusable) data management and the integration of datasets which requires data sharing, along with structured vocabularies and/or ontologies. Two AgBioData working groups, focused on Data Sharing and Ontologies, respectively, conducted a Consortium-wide survey to assess the current status and future needs of the members in those areas. A total of 33 researchers responded to the survey, representing 37 databases. Results suggest that data-sharing practices by AgBioData databases are in a fairly healthy state, but it is not clear whether this is true for all metadata and data types across all databases; and that, ontology use has not substantially changed since a similar survey was conducted in 2017. Based on our evaluation of the survey results, we recommend (i) providing training for database personnel in a specific data-sharing techniques, as well as in ontology use; (ii) further study on what metadata is shared, and how well it is shared among databases; (iii) promoting an understanding of data sharing and ontologies in the stakeholder community; (iv) improving data sharing and ontologies for specific phenotypic data types and formats; and (v) lowering specific barriers to data sharing and ontology use, by identifying sustainability solutions, and the identification, promotion, or development of data standards. Combined, these improvements are likely to help AgBioData databases increase development efforts towards improved ontology use, and data sharing via programmatic means.Database URL  https://www.agbiodata.org/databases

3. Enabling flexibility and connectivity in land-use classification for state of the environment soil quality monitoring

   Jo Cavanagh and Brandon Whitehead

   Jul 2023
4. Representing Fifty Years of Biogeographical Knowledge for Spatially Explicit Ecological Modeling

   Charles K. Lee, Brandon Whitehead, Alejandra Verde, and Fraser Morgan

   In XIII SCAR Biology Symposium, Aug 2023

   Abs

   To generate projections of Antarctic biogeographic patterns following environmental changes driven by a warming climate, spatially explicit ecological models that incorporate biogeographic processes such as dispersal are required. These models, in turn, require spatially and taxonomically consistent representations of extant biogeography that can rationally and consistently express spatial uncertainty, most commonly done using geographic coordinates. However, civilian-use Global Positioning System (GPS) equipment was not widely available until the late 1990s, and the inclusion of GPS coordinates for sampling sites in scientific publications remains inconsistent today. We devised a system for capturing and representing biogeographical information extracted from almost 5,000 scientific publications since the 1970s that is spatially explicit yet accounts for heterogeneous uncertainties in how geographical locations were recorded in the publications. Critically, this system must be capable of defining spatial geometry using location names since only a small minority of the data sources contained GPS coordinates while accounting for the divergent area sizes associated with location names (e.g., Spaulding Pond vs. Taylor Valley). Our geometric system is based on a hierarchical discrete global grid of hexagons, which allows easy approximation of radiuses, simplifying analyses and smoothing over gradients. As biogeographic data are imported into the system, they are assigned to appropriately sized grid cells, and the probabilities of the taxa’s occurrence at various grid cell sizes are calculated; occurrences reported in multiple publications are considered to adjust their probabilities and spatial uncertainties. For ecological modeling, the system outputs biogeographical data as probabilities of occurrence for each taxon across all grid cells at a designated resolution while keeping track of the provenance and original spatial resolution of the data points. Importantly, our discrete global grid design can capture sub-cm spatial resolution, laying a foundation for incorporating ultra-high-resolution data sets (e.g., RPAS hyperspectral surveys).

2022

1. Semantic Web for Earth and Environmental Terminology (SWEET)

   Lewis John McGibbney, Brandon Whitehead, Carlos A. Rueda-Velásquez, Ruth Duerr, Jan Martin Keil, Gary Berg-Cross, Kate Rose, dr-shorthair, smrgeoinfo, graybeal, pbuttigieg, charlesvardeman, ashepherd, esip, nicholascar, ignazio1977, cmungall, esip-lab, and bradh

   Jul 2022
2. Developments and Open Challenges of Information Model for Global Soil Information System

   T. Řezník, K. Schleidt, R. Baritz, J. Bulens, E. Eberhardt, B. Kempen, J. Kozel, D. Medeckyj-Scott, A. Ritchie, L.M. Sousa, Y. Yigini, F. Van Egmon, R. Vergas, B. Whitehead, P. Wilson, R. Palma, B. Janiak, D. Moshou, G. Zhang, A.M. Mouazen, M. Konecny, L. Herman, K. Charvat, J. Smejkal, and T.K. Alexandridis

   Jul 2022

   Abs

   Our presentation summarises the developments towards an information model that is intended as an exchange mechanism between the Global Soil Information System and third party (soil) information systems. This information model, developed under the auspices of the Food and Agriculture Organization of the United Nations (FAO) and the Global Soil Partnership, (1) follows FAO Guidelines for Soil Description and (2) further evolves concepts originating from ISO 28258:2013 - Soil quality standard, ISO 19156:2011 - Observations and measurements, SOSA-SSN and GeoSPARQL. Previous national and international initiatives were discussed and incorporated where appropriate, e.g. ANZSoilML, INSPIRE, the Open Geospatial Consortium Soil Interoperability Experiment and the Federation of ESIP Soil Ontology and Informatics Cluster. The achievements are publicly available under an open license and presented as a series of UML class diagrams, XML schemas and, thanks to an EU-China research & innovation project, also in the form of a network of OWL ontologies providing the base for the publication of linked data related to soil and land use. Special attention is aimed at open challenges at both levels, technical and organisational.

3. Earth and Space Science Informatics Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

   D.J. Hills, J.E. Damerow, B. Ahmmed, N. Catolico, S. Chakraborty, C.M. Coward, R. Crystal-Ornelas, W.D. Duncan, L.N. Goparaju, C. Lin, Z. Liu, M. K. Mudunuru, Y. Rao, R.J. Rovetto, Z. Sun, B.P. Whitehead, L. Wyborn, and T. Yao

   Earth and Space Science, Apr 2022

   Publisher: John Wiley & Sons, Ltd preprint: https://www.essoar.org/doi/abs/10.1002/essoar.10508448.1

   Abs DOI

   Abstract This article is composed of three independent commentaries about the state of ICON principles (Goldman et al., 2021a) in Earth and Space Science Informatics (ESSI) and includes discussion on the opportunities and challenges of adopting them. Each commentary focuses on a different topic: (Section 2) Global collaboration, cyberinfrastructure, and data sharing; (Section 3) Machine learning for multiscale modeling; (Section 4) Aerial and satellite remote sensing for advancing Earth system model development by integrating field and ancillary data. ESSI addresses data management practices, computation and analysis, and hardware and software infrastructure. Our role in ICON science therefore involves collaborative work to assess, design, implement, and promote practices and tools that enable effective data management, discovery, integration, and reuse for interdisciplinary work in Earth and space science disciplines. Networks of diverse people with expertise across Earth, space, and data science disciplines are essential for efficient and ethical exchanges of FAIR research products and practices. Our challenge is then to coordinate the development of standards, curation practices, and tools that enable integrating and reusing multiple data types, software, multi-scale models, and machine learning approaches across disciplines in a way that is as open and/or FAIR as ethically possible. This is a major endeavor that could greatly increase the pace and potential of interdisciplinary scientific discovery.

4. Land-use classification for state of the environment soil quality monitoring and reporting

   JE Cavanagh and Brandon Whitehead

   Jun 2022

   Envirolink Grant: 2222-GSDC170

2021

1. Automated Georeferencing of Antarctic Species

   Jamie Scott, Kristin Stock, Fraser Morgan, Brandon Whitehead, and David Medyckyj-Scott

   In 11th International Conference on Geographic Information Science (GIScience 2021) - Part II, Jun 2021

   ISSN: 1868-8969

   DOI
2. SWEET Governance and Roadmapping: Survey Results

   Brandon Whitehead

   Jul 2021
3. SWEET Overview

   Brandon Whitehead

   Jul 2021

2020

1. 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.

2. Collating soil quality and trace element State of Environment monitoring data

   Jo-Anne E. Cavanagh, Brandon Whitehead, Shirley Vickers, and Bryan Stevenson

   Jul 2020

2019

1. Earth Science is Ready for Preprints: The First Year of EarthArXiv

   Tom W Narock, Evan B. Goldstein, Christopher A-L. Jackson, Alodie A. Bubeck, Allison M. L. Enright, Jamie I Farquharson, Alfonso Fernandez, David Fernández-Blanco, Stéphanie Girardclos, Daniel E Ibarra, Sabine K. Lengger, Anson Mackay, Victor Venema, Brandon Whitehad, and Jean-Paul Ampuero

   EOS, Apr 2019

   Abs DOI

   Preprints — scholarly papers that precede publication in a peer-reviewed journal — speed the delivery and accessibility of academic work and lead to faster reuse by the scientific community, as evidenced by rapid citations and social media discussions. In the past year, EarthArXiv has emerged as a community-led initiative devoted to open scholarly communication. EarthArXiv became the first preprint server for the Earth Sciences on October 23rd, 2017, during the 10th International Open Access Week when it began accepting preprints and also postprints — the non-typeset version of a published article — from all subdomains of Earth science and related domains of planetary science. In our first year, EarthArXiv accepted ~500 submissions which had a total of ~60,000 downloads — we are taking these milestones as an opportunity to discuss the growth and next steps for EarthArXiv, as well as encourage others to join us in this movement toward openness.

2. Semantics for Data in Agriculture: A Community-Based Wish List

   Caterina Caracciolo, Sophie Aubin, Brandon Whitehead, and Panagiotis Zervas

   In Metadata and Semantic Research. MTSR 2018., Apr 2019

   Abs

   The paper reports on activities carried within the Agrisemantics Working Group of the Research Data Alliance (RDA). The group investigated on what are the current problems research and practitioners experience in their work with semantic resources for agricultural data and elaborated the list of requirements that are the object of this paper. The main findings include the need to broaden the usability of tools so as to make them useful and available to the variety of profiles usually involved in working with semantics resources; the need to online platform to lift users from the burden of local installation; and the need for services that can be integrated in workflows. We further analyze requirements concerning the tools and services and provide details about the process followed to gather evidence from the community.

3. 39 Hints to Facilitate the Use of Semantics for Data on Agriculture and Nutrition

   Sophie Aubin, Caterina Caracciolo, and Brandon Whitehead

   Apr 2019
4. 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.

5. Semantic Interoperability of Agricultural Data: the Output of the Agrisemantics WG [version 1; not peer reviewed]

   Sophie Aubin, Caterina Caracciolo, and Brandon Whitehead

   F1000Research, Apr 2019

   Abs DOI

   The Agrisemantics WG has reached its end and produced a set of recommendations to facilitate the use of semantics for Data on Agriculture and Nutrition and so improve their interoperability, discoverability and reusability. Based on an open dialog with the community of researchers and practitioners of semantic technologies, we have identified a few basic points to address in order to make their use more widespread and effective. Then, we have translated those points in specific recommendations roles and activities in data stewardship. Whether you are a data manager, a software developer, a semantics professional, or a policy maker, there is something you can do! Goal of the presentation is to present the final output of the group, together with the methodology followed, gather feedback and ideas for adoption.

6. Cultivating Semantics for Data in Agriculture and Nutrition. Recommendations from the RDA Agrisemantics Working Group.

   Sophie Aubin, Caterina Caracciolo, and Brandon Whitehead

   In IC 2019: 30es Journées francophones d’Ingénierie des Connaissances (Proceedings of the 30th French Knowledge Engineering Conference)., Jul 2019
7. The Agrisemantics recommendations to improve data interoperability in agriculture [version 1; not peer reviewed]

   Caterina Caracciolo, Sophie Aubin, and Brandon Whitehead

   F1000Research, Jul 2019

   Abs DOI

   The Agrisemantics working group focused on the use of semantics as a tool to achieve better data interoperability, especially in the area of agriculture. During our talk, we will introduce the recommendations produced by the group, and illustrate our plans for their maintenance and extension. We will also hint at a few examples of adoptions already ongoing and invite the audience to share ideas and suggestions for further refinement and adoption of the Agrisemantics recommendations.

8. eartharxiv/eartharxiv.github.io: EarthArXiv Resources Website

   Tom Narock, Vicky Steeves, Daniel Nüst, and Brandon Whitehead

   Jan 2019

   DOI

2018

1. Uses and Needs of Semantic Resources in the Area of Agriculture (version 1)

   Sophie Aubin, Caterina Caracciolo, and Brandon Whitehead

   Dec 2018

2016

1. An overview of semantic models in the geosciences: what do we have, and where are we going?

   Brandon Whitehead

   Feb 2016

   Abs

   Presentation for Earth science section of the Ontology Summit 2016.Overview and review of geoscience semantic models.A brief talk on the status of Earth science ontologies.

2013

1. Abstracting Transport to an Ontology Design Pattern for the Geosciences

   Brandon Whitehead, Benjamin Adams, Mark Schildhauer, Charles Vardeman, Werner Kuhn, Adam Shepard, and Krishna Sinha

   In 4th Workshop on Ontology and Semantic Web Patterns, Oct 2013

   Abs

   A core concept in geoscience/physical science research is the concept of transport. We present an ontology design pattern for the no- tion of transport in the geosciences using natural language coupled with a concept map. The top level concepts of the Transport Pattern are trans- port entity, transport mechanism, and transport event. These concepts are described in detail, and a brief example is provided to illustrate the usefulness of the pattern.