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1. Tephra Fusion 2022 workshop focused on best practices in tephra data recommends innovative computer solutions to build databases

   Wallace, K.L. ( January 2022 , EarthCube Annual Meeting 2022)

   A series of international workshops held in 2014, 2017, 2019, and 2022 focused on improving tephra studies from field collection through publication and encouraging FAIR (findable, accessible, interoperable, reusable) data practices for tephra data and metadata. Two consensus needs for tephra studies emerged from the 2014 and 2017 workshops: (a) standardization of tephra field data collection, geochemical analysis, correlation, and data reporting, and (b) development of next generation computer tools and databases to facilitate information access across multidisciplinary communities. To achieve (a), we developed a series of recommendations for best practices in tephra studies, from sample collection through analysis and data reporting (https://zenodo.org/record/3866266). A 4-part virtual workshop series (https://tephrochronology.org/cot/Tephra2022/) was held in February and March, 2022, to update the tephra community on these developments, to get community feedback, to learn of unmet needs, and to plan a future roadmap for open and FAIR tephra data. More than 230 people from 25 nations registered for the workshop series. The community strongly emphasized the need for better computer systems, including physical infrastructure (repositories and servers), digital infrastructure (software and tools) and human infrastructure (people, training, and professional assistance), to store, manage and serve global tephra datasets. Some desired attributes of improved computer systems include: 1) user friendliness 2) ability to easily ingest multiparameter tephra data (using best practice recommended data fields); 3) interoperability with existing data repositories; 4) development of tool add-ons (plotting and statistics); 5) improved searchability 6) development of a tephra portal with access to distributed data systems, and 7) commitments to long-term support from funding agencies, publishers and the cyberinfrastructure community. 

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2. Workforce Capacity Development and the Digital Extended Specimen

   https://doi.org/10.3897/biss.5.73927  

   Monfils, Anna ; Ellwood, Elizabeth R. ( September 2021 , Biodiversity Information Science and Standards)

   As we look to the future of natural history collections and a global integration of biodiversity data, we are reliant on a diverse workforce with the skills necessary to build, grow, and support the data, tools, and resources of the Digital Extended Specimen (DES; Webster 2019, Lendemer et al. 2020, Hardisty 2020). Future “DES Data Curators” – those who will be charged with maintaining resources created through the DES – will require skills and resources beyond what is currently available to most natural history collections staff. In training the workforce to support the DES we have an opportunity to broaden our community and ensure that, through the expansion of biodiversity data, the workforce landscape itself is diverse, equitable, inclusive, and accessible. A fully-implemented DES will provide training that encapsulates capacity building, skills development, unifying protocols and best practices guidance, and cutting-edge technology that also creates inclusive, equitable, and accessible systems, workflows, and communities. As members of the biodiversity community and the current workforce, we can leverage our knowledge and skills to develop innovative training models that: include a range of educational settings and modalities; address the needs of new communities not currently engaged with digital data; from their onset, provide attribution for past and future work and do not perpetuate the legacy of colonial practices and historic inequalities found in many physical natural history collections. Recent reports from the Biodiversity Collections Network (BCoN 2019) and the National Academies of Science, Engineering and Medicine (National Academies of Sciences, Engineering, and Medicine 2020) specifically address workforce needs in support of the DES. To address workforce training and inclusivity within the context of global data integration, the Alliance for Biodiversity Knowledge included a topic on Workforce capacity development and inclusivity in Phase 2 of the consultation on Converging Digital Specimens and Extended Specimens - Towards a global specification for data integration. Across these efforts, several common themes have emerged relative to workforce training and the DES. A call for a community needs assessment: As a community, we have several unknowns related to the current collections workforce and training needs. We would benefit from a baseline assessment of collections professionals to define current job responsibilities, demographics, education and training, incentives, compensation, and benefits. This includes an evaluation of current employment prospects and opportunities. Defined skills and training for the 21st century collections professional: We need to be proactive and define the 21st century workforce skills necessary to support the development and implementation of the DES. When we define the skills and content needs we can create appropriate training opportunities that include scalable materials for capacity building, educational materials that develop relevant skills, unifying protocols across the DES network, and best practices guidance for professionals. Training for data end-users: We need to train data end-users in biodiversity and data science at all levels of formal and informal education from primary and secondary education through the existing workforce. This includes developing training and educational materials, creating data portals, and building analyses that are inclusive, accessible, and engage the appropriate community of science educators, data scientists, and biodiversity researchers. Foster a diverse, equitable, inclusive, and accessible and professional workforce: As the DES develops and new tools and resources emerge, we need to be intentional in our commitment to building tools that are accessible and in assuring that access is equitable. This includes establishing best practices to ensure the community providing and accessing data is inclusive and representative of the diverse global community of potential data providers and users. Upfront, we must acknowledge and address issues of historic inequalities and colonial practices and provide appropriate attribution for past and future work while ensuring legal and regulatory compliance. Efforts must include creating transparent linkages among data and the humans that create the data that drives the DES. In this presentation, we will highlight recommendations for building workforce capacity within the DES that are diverse, inclusive, equitable and accessible, take into account the requirements of the biodiversity science community, and that are flexible to meet the needs of an evolving field. 

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3. Remote sensing in support of endangered species management and animal movement research – the Env-DATA tool pack

   Bohrer, G ; Kays, R ; Davidson, SC ; Wienzierl, R ; Dodge, S ; Mcclain, KM ; Wikelski, M. ( October 2015 , Proceedings of the 66th International Astronautical Congress, International Astronautical Federation)

   The movement of animals is strongly influenced by external factors in their surrounding environment such as weather, habitat types, and human land use. With advances in positioning and sensor technologies, it is now possible to capture animal locations at high spatial and temporal granularities. Likewise, modern space-based remote sensing technology provides us with an increasing access to large volumes of environmental data, some of which changes on an hourly basis. Environmental data are heterogeneous in source and format, and are usually obtained at different scales and granularities than movement data. Indeed, there remain scientific and technical challenges in developing linkages between the growing collections of animal movement data and the large repositories of heterogeneous remote sensing observations, as well as in the developments of new statistical and computational methods for the analysis of movement in its environmental context. These challenges include retrieval, indexing, efficient storage, data integration, and analytic techniques. We have developed a new system - the Environmental-Data Automated Track Annotation (Env-DATA) - that automates annotation of movement trajectories with remote-sensing environmental information, including high resolution topography, weather from global and regional reanalysis datasets, climatology, human geography, ocean currents and productivity, land use, vegetation and land surface variables, precipitation, fire, and other global datasets. The system automates the acquisition of data from open web resources of remote sensing and weather data and provides several interpolation methods from the native grid resolution and structure to a global regular grid linked with the movement tracks in space and time. Env-DATA provides an easy-to-use platform for end users that eliminates technical difficulties of the annotation processes, including data acquisition, data transformation and integration, resampling, interpolation and interpretation. The new Env-DATA system enhances Movebank (www.movebank.org), an open portal of animal tracking data. The aim is to facilitate new understanding and predictive capabilities of spatiotemporal patterns of animal movement in response to dynamic and changing environments from local to global scales. The system is already in use by scientists worldwide, and by several conservation managers, such as the consortium of federal and private institution that manage the endangered Californian Condor populations. 

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4. Highlights and Outcomes of the 2021 Global Community Consultation

   https://doi.org/10.3897/biss.5.72716  

   Ellwood, Elizabeth R. ; Bentley, Andrew ; Buschbom, Jutta ; Hardisty, Alex ; Mast, Austin ; Miller, Joe ; Monfils, Anna ; Nelson, Gil ; Paul, Deborah L ( August 2021 , Biodiversity Information Science and Standards)

   International collaboration between collections, aggregators, and researchers within the biodiversity community and beyond is becoming increasingly important in our efforts to support biodiversity, conservation and the life of the planet. The social, technical, logistical and financial aspects of an equitable biodiversity data landscape – from workforce training and mobilization of linked specimen data, to data integration, use and publication – must be considered globally and within the context of a growing biodiversity crisis. In recent years, several initiatives have outlined paths forward that describe how digital versions of natural history specimens can be extended and linked with associated data. In the United States, Webster (2017) presented the “extended specimen”, which was expanded upon by Lendemer et al. (2019) through the work of the Biodiversity Collections Network (BCoN). At the same time, a “digital specimen” concept was developed by DiSSCo in Europe (Hardisty 2020). Both the extended and digital specimen concepts depict a digital proxy of an analog natural history specimen, whose digital nature provides greater capabilities such as being machine-processable, linkages with associated data, globally accessible information-rich biodiversity data, improved tracking, attribution and annotation, additional opportunities for data use and cross-disciplinary collaborations forming the basis for FAIR (Findable, Accessible, Interoperable, Reproducible) and equitable sharing of benefits worldwide, and innumerable other advantages, with slight variation in how an extended or digital specimen model would be executed. Recognizing the need to align the two closely-related concepts, and to provide a place for open discussion around various topics of the Digital Extended Specimen (DES; the current working name for the joined concepts), we initiated a virtual consultation on the discourse platform hosted by the Alliance for Biodiversity Knowledge through GBIF. This platform provided a forum for threaded discussions around topics related and relevant to the DES. The goals of the consultation align with the goals of the Alliance for Biodiversity Knowledge: expand participation in the process, build support for further collaboration, identify use cases, identify significant challenges and obstacles, and develop a comprehensive roadmap towards achieving the vision for a global specification for data integration. In early 2021, Phase 1 launched with five topics: Making FAIR data for specimens accessible; Extending, enriching and integrating data; Annotating specimens and other data; Data attribution; and Analyzing/mining specimen data for novel applications. This round of full discussion was productive and engaged dozens of contributors, with hundreds of posts and thousands of views. During Phase 1, several deeper, more technical, or additional topics of relevance were identified and formed the foundation for Phase 2 which began in May 2021 with the following topics: Robust access points and data infrastructure alignment; Persistent identifier (PID) scheme(s); Meeting legal/regulatory, ethical and sensitive data obligations; Workforce capacity development and inclusivity; Transactional mechanisms and provenance; and Partnerships to collaborate more effectively. In Phase 2 fruitful progress was made towards solutions to some of these complex functional and technical long-term goals. Simultaneously, our commitment to open participation was reinforced, through increased efforts to involve new voices from allied and complementary fields. Among a wealth of ideas expressed, the community highlighted the need for unambiguous persistent identifiers and a dedicated agent to assign them, support for a fully linked system that includes robust publishing mechanisms, strong support for social structures that build trustworthiness of the system, appropriate attribution of legacy and new work, a system that is inclusive, removed from colonial practices, and supportive of creative use of biodiversity data, building a truly global data infrastructure, balancing open access with legal obligations and ethical responsibilities, and the partnerships necessary for success. These two consultation periods, and the myriad activities surrounding the online discussion, produced a wide variety of perspectives, strategies, and approaches to converging the digital and extended specimen concepts, and progressing plans for the DES -- steps necessary to improve access to research-ready data to advance our understanding of the diversity and distribution of life. Discussions continue and we hope to include your contributions to the DES in future implementation plans. 

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5. Recent Advances in the Temple University Digital Pathology Corpus

   https://doi.org/10.1109/SPMB47826.2019.9037859  

   Hunt, I. ; Husain, S. ; Simon, J. ; Obeid, I. ; Picone, J. ( December 2019 , IEEE Signal Processing in Medicine and Biology Symposium (SPMB))

   Obeid, Iyad ; Picone, Joseph ; Selesnick, Ivan (Ed.)

   The Neural Engineering Data Consortium (NEDC) is developing a large open source database of high-resolution digital pathology images known as the Temple University Digital Pathology Corpus (TUDP) [1]. Our long-term goal is to release one million images. We expect to release the first 100,000 image corpus by December 2020. The data is being acquired at the Department of Pathology at Temple University Hospital (TUH) using a Leica Biosystems Aperio AT2 scanner [2] and consists entirely of clinical pathology images. More information about the data and the project can be found in Shawki et al. [3]. We currently have a National Science Foundation (NSF) planning grant [4] to explore how best the community can leverage this resource. One goal of this poster presentation is to stimulate community-wide discussions about this project and determine how this valuable resource can best meet the needs of the public. The computing infrastructure required to support this database is extensive [5] and includes two HIPAA-secure computer networks, dual petabyte file servers, and Aperio’s eSlide Manager (eSM) software [6]. We currently have digitized over 50,000 slides from 2,846 patients and 2,942 clinical cases. There is an average of 12.4 slides per patient and 10.5 slides per case with one report per case. The data is organized by tissue type as shown below: Filenames: tudp/v1.0.0/svs/gastro/000001/00123456/2015_03_05/0s15_12345/0s15_12345_0a001_00123456_lvl0001_s000.svs tudp/v1.0.0/svs/gastro/000001/00123456/2015_03_05/0s15_12345/0s15_12345_00123456.docx Explanation: tudp: root directory of the corpus v1.0.0: version number of the release svs: the image data type gastro: the type of tissue 000001: six-digit sequence number used to control directory complexity 00123456: 8-digit patient MRN 2015_03_05: the date the specimen was captured 0s15_12345: the clinical case name 0s15_12345_0a001_00123456_lvl0001_s000.svs: the actual image filename consisting of a repeat of the case name, a site code (e.g., 0a001), the type and depth of the cut (e.g., lvl0001) and a token number (e.g., s000) 0s15_12345_00123456.docx: the filename for the corresponding case report We currently recognize fifteen tissue types in the first installment of the corpus. The raw image data is stored in Aperio’s “.svs” format, which is a multi-layered compressed JPEG format [3,7]. Pathology reports containing a summary of how a pathologist interpreted the slide are also provided in a flat text file format. A more complete summary of the demographics of this pilot corpus will be presented at the conference. Another goal of this poster presentation is to share our experiences with the larger community since many of these details have not been adequately documented in scientific publications. There are quite a few obstacles in collecting this data that have slowed down the process and need to be discussed publicly. Our backlog of slides dates back to 1997, meaning there are a lot that need to be sifted through and discarded for peeling or cracking. Additionally, during scanning a slide can get stuck, stalling a scan session for hours, resulting in a significant loss of productivity. Over the past two years, we have accumulated significant experience with how to scan a diverse inventory of slides using the Aperio AT2 high-volume scanner. We have been working closely with the vendor to resolve many problems associated with the use of this scanner for research purposes. This scanning project began in January of 2018 when the scanner was first installed. The scanning process was slow at first since there was a learning curve with how the scanner worked and how to obtain samples from the hospital. From its start date until May of 2019 ~20,000 slides we scanned. In the past 6 months from May to November we have tripled that number and how hold ~60,000 slides in our database. This dramatic increase in productivity was due to additional undergraduate staff members and an emphasis on efficient workflow. The Aperio AT2 scans 400 slides a day, requiring at least eight hours of scan time. The efficiency of these scans can vary greatly. When our team first started, approximately 5% of slides failed the scanning process due to focal point errors. We have been able to reduce that to 1% through a variety of means: (1) best practices regarding daily and monthly recalibrations, (2) tweaking the software such as the tissue finder parameter settings, and (3) experience with how to clean and prep slides so they scan properly. Nevertheless, this is not a completely automated process, making it very difficult to reach our production targets. With a staff of three undergraduate workers spending a total of 30 hours per week, we find it difficult to scan more than 2,000 slides per week using a single scanner (400 slides per night x 5 nights per week). The main limitation in achieving this level of production is the lack of a completely automated scanning process, it takes a couple of hours to sort, clean and load slides. We have streamlined all other aspects of the workflow required to database the scanned slides so that there are no additional bottlenecks. To bridge the gap between hospital operations and research, we are using Aperio’s eSM software. Our goal is to provide pathologists access to high quality digital images of their patients’ slides. eSM is a secure website that holds the images with their metadata labels, patient report, and path to where the image is located on our file server. Although eSM includes significant infrastructure to import slides into the database using barcodes, TUH does not currently support barcode use. Therefore, we manage the data using a mixture of Python scripts and manual import functions available in eSM. The database and associated tools are based on proprietary formats developed by Aperio, making this another important point of community-wide discussion on how best to disseminate such information. Our near-term goal for the TUDP Corpus is to release 100,000 slides by December 2020. We hope to continue data collection over the next decade until we reach one million slides. We are creating two pilot corpora using the first 50,000 slides we have collected. The first corpus consists of 500 slides with a marker stain and another 500 without it. This set was designed to let people debug their basic deep learning processing flow on these high-resolution images. We discuss our preliminary experiments on this corpus and the challenges in processing these high-resolution images using deep learning in [3]. We are able to achieve a mean sensitivity of 99.0% for slides with pen marks, and 98.9% for slides without marks, using a multistage deep learning algorithm. While this dataset was very useful in initial debugging, we are in the midst of creating a new, more challenging pilot corpus using actual tissue samples annotated by experts. The task will be to detect ductal carcinoma (DCIS) or invasive breast cancer tissue. There will be approximately 1,000 images per class in this corpus. Based on the number of features annotated, we can train on a two class problem of DCIS or benign, or increase the difficulty by increasing the classes to include DCIS, benign, stroma, pink tissue, non-neoplastic etc. Those interested in the corpus or in participating in community-wide discussions should join our listserv, nedc_tuh_dpath@googlegroups.com, to be kept informed of the latest developments in this project. You can learn more from our project website: https://www.isip.piconepress.com/projects/nsf_dpath. 

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