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1. Internet of Samples

   https://doi.org/10.1002/pra2.572  

   Richard, Stephen M; Vieglais, David; Cui, Hong; Davies, Neil; Deck, John; Gan, Quan; Kansa, Eric C; Kansa, Sarah Whitcher; Kunze, John; Mandel, Danny; et al (October 2021, Proceedings of the Association for Information Science and Technology)

   Material samples are indispensable data sources in many natural science, social science, and humanity disciplines. More and more researchers recognize that samples collected in one discipline can be of great value for another. This has motivated organizations that manage a large number of samples to make their holdings accessible to the world. Currently, multiple projects are working to connect natural history and other samples managed by individual institutions or individuals into a universe of samples that follow FAIR principles. This poster reports the progress of the US NSF‐funded iSamples project, in the context of other efforts initiated by US DOE, DiSCCo, BCoN, and GBIF. By October 2021, we will also be able to present an iSamples prototype. We encourage individual organizations that hold material samples to get to know these projects and help shape these projects to realize the goal of a global linked sample cloud that connects all material samples and is accessible to all. 

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2. Opening Doors to Physical Sample Data Discovery, Integration, and Credit

   https://doi.org/10.31223/X5ST2K  

   Damerow, Joan; Raia, Natalie; Stanley, Val; Choe, Saebyul; Borton, Mikayla; Byers, Neil; Cassidy, Ellen; Cholia, Shreyas; Edmunds, Rorie; Forbes, Brieanne; et al (June 2024, Nature Scientific Data)

   Physical samples and their associated (meta)data underpin scientific discoveries across disciplines, and can enable new science when appropriately archived. However, there are significant gaps in community practices and infrastructure that currently prevent accurate provenance tracking, reproducibility, and attribution. For the vast majority of samples, descriptive metadata is often sparse, inaccessible, or absent. Samples and associated (meta)data may also be scattered across numerous physical collections, data repositories, laboratories, data files, and papers with no clear linkages or provenance tracking as new information is generated over time. The Physical Samples Curation Cluster has therefore developed ‘A Scientific Author Guide for Publishing Open Research Using Physical Samples.’ This involved synthesizing existing practices, community feedback, and assessing real-world examples to identify community and infrastructure needs. We identified areas of work needed to enable authors to efficiently reference samples and related data, link related samples and data, and track their use. Our goal is to help improve the discoverability, interoperability, use of physical samples and associated (meta)data into the future. 

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3. Fostering better coding practices for data scientists

   https://doi.org/10.1162/99608f92.97c9f60f  

   Pruim, Randall; Gîrjau, Maria-Cristiana; Horton, Nicholas J. (July 2023, Harvard Data Science Review)

   Meng, X-L (Ed.)

   Many data science students and practitioners are reluctant to adopt good coding practices as long as the code ‘works.’ However, code standards are an important part of modern data science practice, and they play an essential role in the development of data acumen. Good coding practices lead to more reliable code and save more time than they cost, making them important even for beginners. We believe that principled coding is vital for quality data science practice. To effectively instill these practices within academic programs, instructors and programs need to begin establishing these practices early, to reinforce them often, and to hold themselves to a higher standard while guiding students. We describe key aspects of good coding practices for data science, illustrating with examples in R and in Python, though similar standards are applicable to other software environments. Practical coding guidelines are organized into a top ten list. 

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4. Connecting chemistry concepts with environmental context using student-built pH sensors

   https://doi.org/10.1080/10899995.2019.1702868  

   Seroy, Sasha K.; Zulmuthi, Hanis; Grünbaum, Daniel (December 2019, Journal of Geoscience Education)

   Educational research supports incorporating active engagement into K-12 education using authentic STEM experiences. While there are discipline-specific resources to provide students with such experiences, there are limited transdisciplinary opportunities that integrate engineering education and technological skill-building to contextualize core scientific concepts. Here, we present an adaptable module that integrates hands-on technology education and place-based learning to improve student understanding of key chemistry concepts as they relate to local environmental science. The module also supports disciplinary core ideas, practices, and cross-cutting concepts in accordance with the Next Generation Science Standards. We field-tested our module in three different high school courses: Chemistry, Oceanography and Advanced Placement Environmental Science at schools in Washington, USA. Students built spectrophotometric pH sensors using readily available electronic components and calibrated them with known pH reference standards. Students then used their sensors to measure the pH of local environmental water samples. Assessments showed significant improvement in content knowledge in all three courses relating to environmental relevance of pH, and to the design, use and environmental application of sensors. Students also reported increased self-confidence in the material, even when their content knowledge remained the same. These findings suggest that classroom sensor building and collection of environmental data increases student understanding and self-confidence by connecting chemistry concepts to local environmental settings. 

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5. Persistent, Global, Unique: The three key requirements for a trusted identifier system for physical samples

   https://doi.org/10.3897/biss.3.37334  

   Lehnert, Kerstin; Klump, Jens; Wyborn, Lesley; Ramdeen, Sarah (June 2019, Biodiversity Information Science and Standards)

   There is growing recognition that unambiguous citation and tracking of physical samples allows previously impossible linking of samples to data and publications, linking and integration of sample-based observations across data systems, and paves the road towards advanced data mining of sample-based data. And in recent years, there has been an uptake in the use of Persistent Identifiers (PIDs) for physical samples to support such citation and tracking. The IGSN (International Geo Sample Number) is a PID for physical samples. It was originally developed for the solid earth sciences, and has evolved into an international PID system with members in five continents and a network of active allocating agents. It has been adopted by a growing number and range of stakeholders worldwide, including national geological surveys, research infrastructure providers, collection curators, researchers, and data managers, and by other disciplines that need to refer to physical samples. Nearly 6.9 million samples have been registered with IGSNs so far. The IGSN system uses the Handle System (Kahn and Wilensky 1995; see also Handle.Net ® ) and has an international organization, IGSN e.V., to manage its governance structure and the technical architecture. The recent expansion of the IGSN beyond the geosciences into other domains such as biodiversity, archeology, and material sciences confirms the power of its concept and implementation, but imposes substantial pressures on the existing capacity and capabilities of the IGSN architecture and its governing organization. Modifications to the IGSN organizational and technical architecture are necessary at this point to keep pace with the growing demand and expectations. These changes are also necessary to ensure trustworthy and sustainable services for PID registration and resolution in a maturing research data ecosystem. The essential criteria for a trustworthy system include an organizational foundation that ensures longevity, sustainability, proper governance, and regular quality assessment of registration services. It also includes a reliable and secure technical platform, based on open standards, which is sufficiently scalable and flexible to accommodate the growing diversity of specimen types, use cases, and stakeholder requirements. In 2018, a major planning project for the IGSN was funded by the Alfred P. Sloan Foundation. An international group of experts participates in re-designing and improving the existing organization and technical architecture of the IGSN system, revising the current business model of the IGSN e.V. and professionalizing its operations. The goal is for the IGSN system to be able to respond to, and support in a sustainable manner, the rapidly growing demands of a global and increasingly multi-disciplinary user community, and to ensure that the IGSN will be a trustworthy, stable, and adaptable persistent identifier system for material samples, both technically and organizationally. The end result should also satisfy and facilitate participation across research domains, and will be a reliable component of the evolving research data ecosystem. Finally, it will ensure that the IGSN is recognized as a trusted partner by data infrastructure providers and the science community alike. 

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