More Like this

1. Arctos: Community-driven innovations for managing natural and cultural history collections

   https://doi.org/10.1371/journal.pone.0296478  

   Cicero, Carla; Koo, Michelle S; Braker, Emily; Abbott, John; Bloom, David; Campbell, Mariel; Cook, Joseph A; Demboski, John R; Doll, Andrew C; Frederick, Lindsey M; et al (May 2024, PLOS ONE)

   Meloro, Carlo (Ed.)

   More than tools for managing physical and digital objects, museum collection management systems (CMS) serve as platforms for structuring, integrating, and making accessible the rich data embodied by natural history collections. Here we describe Arctos, a scalable community solution for managing and publishing global biological, geological, and cultural collections data for research and education. Specific goals are to: (1) Describe the core features and implementation of Arctos for a broad audience with respect to the biodiversity informatics principles that enable high quality research; (2) Highlight the unique aspects of Arctos; (3) Illustrate Arctos as a model for supporting and enhancing the Digital Extended Specimen concept; and (4) Emphasize the role of the Arctos community for improving data discovery and enabling cross-disciplinary, integrative studies within a sustainable governance model. In addition to detailing Arctos as both a community of museum professionals and a collection database platform, we discuss how Arctos achieves its richly annotated data by creating a web of knowledge with deep connections between catalog records and derived or associated data. We also highlight the value of Arctos as an educational resource. Finally, we present the financial model of fiscal sponsorship by a nonprofit organization, implemented in 2022, to ensure the long-term success and sustainability of Arctos. 

   more » « less
2. Making Parasite-Host Associations Visible using Global Biotic Interactions

   https://doi.org/10.3897/biss.4.58985  

   Seltmann, Katja; Poelen, Jorrit; Sullivan, Kathryn; Zaspel, Jennifer (October 2020, Biodiversity Information Science and Standards)

   null (Ed.)

   A wealth of information about how parasites interact with their hosts already exists in collections, scientific publications, specialized databases, and grey literature. The US National Science Foundation-funded Terrestrial Parasite Tracker Thematic Collection Network (TPT) project began in 2019 to help build a comprehensive picture of arthropod ectoparasites including the evolution of these parasite-host biotic associations, distributions, and the ecological interactions of disease vectors. TPT is a network of biodiversity collections whose data can assist scientists, educators, land managers, and policymakers to better understand the complex relationship between hosts and parasites including emergent properties that may explain the causes and frequency of human and wildlife pathogens. TPT member collections make their association information easier to access via Global Biotic Interactions (GloBI, Poelen et al. 2014), which is periodically archived through Zenodo to track progress in the TPT project. TPT leverages GloBI's ability to index biotic associations from specimen occurrence records that come from existing management systems (e.g., Arctos, Symbiota, EMu, Excel, MS Access) to avoid having to completely rework existing, or build new, cyber-infrastructures before collections can share data. TPT-affiliated collection managers use collection-specific translation tables to connect their verbatim (or original) terms used to describe associations (e.g., "ex", "found on", "host") to their interpreted, machine-readable terms in the OBO Relations Ontology (RO). These interpreted terms enable searches across previously siloed association record sets, while the original verbatim values remain accessible to help retain provenance and allow for interpretation improvements. TPT is an ambitious project, with the goal to database label data from over 1.2 million specimens of arthropod parasites of vertebrates coming from 22 collections across North America. In the first year of the project, the TPT collections created over 73,700 new records and 41,984 images. In addition, 17 TPT data providers and three other collaborators shared datasets that are now indexed by GloBI, visible on the TPT GloBI project page. These datasets came from collection specimen occurrence records and literature sources. Two TPT data archives that capture and preserve the changes in the data coming from TPT to GloBI were published through Zenodo (Poelen et al. 2020a, Poelen et al. 2020b). The archives document the changes in how data are shared by collections including the biotic association data format and quantity of data captured. The Poelen et al. 2020b report included all TPT collections and biotic interactions from Arctos collections in VertNet and the Symbiota Collection of Arthropods Network (SCAN). The total number of interactions included in this report was 376,671 records (500,000 interactions is the overall goal for TPT). In addition, close coordination with TPT collection data managers including many one-on-one conversations, a workshop, and a webinar (Sullivan et al. 2020) was conducted to help guide the data capture of biotic associations. GloBI is an effective tool to help integrate biotic association data coming from occurrence records into an openly accessible, global, linked view of existing species interaction records. The results gleaned from the TPT workshop and Zenodo data archives demonstrate that minimizing changes to existing workflows allow for custom interpretation of collection-specific interaction terms. In addition, including collection data managers in the development of the interaction term vocabularies is an important part of the process that may improve data sharing and the overall downstream data quality. 

   more » « less
3. From spectators to stewards: Transforming public involvement in natural history collections

   https://doi.org/10.3897/nhcm.1.138247  

   von_Konrat, Matt; Rodriguez, Yarency; Bailey, Colleen; Gwilliam_III, Gilbert F; Christian, Christine; Aguero, Blanka; Ahn, June; Albion, Zoe; Allen, James R; Bailey, Colin; et al (December 2024, Natural History Collections and Museomics)

   A comprehensive overview of volunteer-driven public programs focused on activities to enhance natural history collections (NHCs) is provided. The initiative revolves around the WeDigBio events and the Collections Club at the Field Museum, aiming to deepen the public’s connection with scientific collections, enhance participatory science, and improve data associated with natural history specimens. The implementation and journey of these programs are outlined, including surveys conducted from 2015 through 2021 to gauge participant motivation, satisfaction, and the impact of these events on public engagement with NHCs. Results show trends in on-site and virtual volunteer participation over the years, especially during the peak period of the COVID-19 pandemic. The majority of participants expressed high satisfaction, indicating a willingness to continue participating in similar activities. The surveys revealed a shift towards more altruistic motivations for participation over time, with increased emphasis on supporting the Field Museum and contributing to the scientific community. The success of participatory science events demonstrates the potential of volunteer-driven programs to contribute meaningfully to the preservation, digitisation, and understanding of biodiversity collections, ultimately transforming spectators into stewards of natural history. From 2015 to present participants celebrate a significant milestone, with over a thousand community scientists contributing to the inventorying, collection care, curation, databasing, or transcription of 286,071 specimens, objects or records. We also discuss accuracy and quality control as well as a checklist and recommendations for similar activities. 

   more » « less
4. An Information Ecosystem Map of Resources Supporting the Mobilization and Discovery of Paleontological Specimen Data

   https://doi.org/10.3897/biss.8.139040  

   Little, Holly; Karim, Talia; Krimmel, Erica; Walker, Lindsay (October 2024, Biodiversity Information Science and Standards)

   Over the last decade, the United States paleontological collections community has invested heavily in the digitization of specimen-based data, including over 10 million USD funded through the National Science Foundation’s Advancing Digitization of Biodiversity Collections program. Fossil specimen data—9.0 million records and counting (Global Biodiversity Information Facility 2024)—are now accessible on open science platforms such as the Global Biodiversity Information Facility (GBIF). However, the full potential of this data is far from realized due to fundamental challenges associated with mobilization, discoverability, and interoperability of paleontological information within the existing cyberinfrastructure landscape and data pipelines. Additionally, it can be difficult for individuals with varying expertise to develop a comprehensive understanding of the existing landscape due to its breadth and complexity. Here, we present preliminary results from a project aiming to explore how we might address these problems. Funding from the US National Science Foundation (NSF) to the University of Colorado Museum of Natural History, Smithsonian National Museum of Natural History, and Arizona State University will result in, among other products, an “ecosystem map” for the paleontological collections community. This map will be an information-rich visualization of entities (e.g. concepts, systems, platforms, mechanisms, drivers, tools, documentation, data, standards, people, organizations) operating in, intersecting with, or existing in parallel to our domain. We are inspired and informed by similar efforts to map the biodiversity informatics landscape (Bingham et al. 2017) and the research infrastructure landscape (Distributed System of Scientific Collections 2024), as well as by many ongoing metadata cataloging projects, e.g. re3data and the Global Registry of Scientific Collections (GRSciColl). Our strategy for developing this ecosystem map is to model the existing information and systems landscape by characterizing entities, e.g. potentially in a graph database as nodes with relationships to other nodes. The ecosystem map will enable us to provide guidance for communities workingacrossdifferent sectors of the landscape, promoting a shared understanding of the ecosystem that everyone works in together. We can also use the map to identify points of entry and engagement at various stages of the paleontological data process, and to engage diverse memberswithinthe paleontological community. We see three primary user types for this map: people new(er) to the community, people with expertise in a subset of the community, and people working to integrate initiatives and systems across communities. Each of these user types needs tailored access to the ecosystem map and its community knowledge. By promoting shared knowledge with the map, users will be able to identify their own space within the ecosystem and the connections or partnerships that they can utilize to expand their knowledge or resources, relieving the burden on any single individual to hold a comprehensive understanding. For example, the flow of taxonomic information between publications, collections, digital resources, and biodiversity aggregators is not straightforward or easy to understand. A person with expertise in collections care may want to use the ecosystem map to understand why taxonomic identifications associated with their specimen occurrence records are showing up incorrectly when published to GBIF. We envision that our final ecosystem map will visualize the flow of taxonomic information and how it is used to interpret specimen occurrence data, thereby highlighting to this user where problems may be happening and whom to ask for help in addressing them (Fig. 1). Ultimately, development of this map will allow us to identify mobilization pathways for paleontological data, highlight core cyberinfrastructure resources, define cyberinfrastructure gaps, strategize future partnerships, promote shared knowledge, and engage a broader array of expertise in the process. Contributing domain-based evidence FAIRly*2 requires expertise that bridges the content (e.g. paleontology) and the mechanics (e.g. informatics). By centering the role of humans in open science cyberinfrastructure throughout our process, we hope to develop systems that create and sustain such expertise. 

   more » « less
5. Challenges and opportunities for using natural history collections to estimate insect population trends

   https://doi.org/10.1111/1365-2656.13763  

   Davis, Courtney L.; Guralnick, Robert P.; Zipkin, Elise F. (June 2022, Journal of Animal Ecology)

   Abstract Natural history collections (NHC) provide a wealth of information that can be used to understand the impacts of global change on biodiversity. As such, there is growing interest in using NHC data to estimate changes in species' distributions and abundance trends over historic time horizons when contemporary survey data are limited or unavailable.However, museum specimens were not collected with the purpose of estimating population trends and thus can exhibit spatiotemporal and collector‐specific biases that can impose severe limitations to using NHC data for evaluating population trajectories.Here we review the challenges associated with using museum records to track long‐term insect population trends, including spatiotemporal biases in sampling effort and sparse temporal coverage within and across years. We highlight recent methodological advancements that aim to overcome these challenges and discuss emerging research opportunities.Specifically, we examine the potential of integrating museum records and other contemporary data sources (e.g. collected via structured, designed surveys and opportunistic citizen science programs) in a unified analytical framework that accounts for the sampling biases associated with each data source. The emerging field of integrated modelling provides a promising framework for leveraging the wealth of collections data to accurately estimate long‐term trends of insect populations and identify cases where that is not possible using existing data sources. 

   more » « less