Natural History Collections (NHC) Biodiversity Data Informatics 101 Note: In our greater scientific community, the scope for each of the terms: biological informatics, bioinformatics, and more recently, biodiversity informatics, is still evolving. So this brief description is a guide only and not meant to be prescriptive.     Biological Informatics, as in Advances in Biological Informatics (ABI) in the NSF’s Division of Biological Infrastructure, is the broader term. It encompasses the human skills and knowledge needed to effectively collect and use all kinds of biological data for research. In order for humans to do this well, they need robust hardware, intuitive software, and data standards, to succeed and sustain these efforts.     Bioinformatics traditionally refers to and deals with data, skills, knowledge, and standards needed to work with molecular and genomic data and the hardware and software to support this work. Scientists interested in bioinformatics are usually working with genomic data sets of some sort, and many (for example) want to learn Python in order to work effectively with this type of data.     Biodiversity Informatics usually encompasses the world of data at the organismal and ecosystem level and again the data, skills, knowledge, and standards needed to work with organismal and ecosystem level data and the hardware and software to support this work. Scientists interested in biodiversity informatics are usually working with organismal (idigbio), and or observation (ecosystem) data sets of some sort, and many (for example) want to learn R in order to work effectively with this type of data.     Of course, as we connect these worlds through projects like genotype-to-phenotype, or projects that try to connect organism-level morphometric data with genomic data, the lines are less and less clear. What is clear, is that the across these worlds, the computational and data literacy skills and knowledge needs are often the same. And, of course, the hardware, software, and data standards needs also overlap. Jennifer Strotman, Holly Little, Deborah Paul @SPNHC2017 Denver, Colorado 18 June 2017 tw @idbdeb

Welcome to Biodiversity Informatics 101 Your organizers Jennifer Strotman Smithsonian Holly Little Smithsonian Deborah Paul iDigBio

SPNHC Biodiversity Informatics 101 Logistics Wifi Name tags – first time at SPNHC? Wiki http://tinyurl.com/spnhcbi101 Group folder [see wiki for link] Google shared notes http://tinyurl.com/spnhcbi101notes Your resources and expertise Participant list Minute cards 2-minute stand-ups

NHC Biodiversity Informatics 101 Agenda

NHC Biodiversity Informatics 101 Origins and expectations Offer a pre-SPNHC opportunity for networking, mentoring, to enhance the SPNHC 2017 experience Our goals increase familiarity of current projects, working groups, and timely topics awareness of the larger picture 411 - where to find resources enhancing communication and collaboration with your informatician counterparts knowing how to ask and whom Contribute your insights and needs to inform the broader community Skills Data literacy Mentoring

Building and Caring for Digital Collections

dATA and Specimens With gratitude to Dorothy Allard! New tools, new software, making data management, data transformations more efficient… More ways for more people to participate, like crowd-sourcing of digitization, and it’s influencing specimen curation too. Everyone in this data pipe-line/path has skills needs. And the landscape is constantly changing. How do you keep up? With gratitude to Dorothy Allard!

Biological Informatics Bioinformatics Biodiversity Informatics molecular to gene organism to ecosystem For Biodiversity Informatics: What human skills and software tools are needed to collect, manage, and do research with this specimen and related data? What infrastructure is needed (hardware and software)? What data standards are needed? What data and computational literacy skills and knowledge are required through the data pipeline from data collection to digitization to data use / re-use? From NIBA 3.1. Implement new training opportunities in biodiversity informatics. * Develop new opportunities and expand existing training programs for collections professionals so that they can more fully engage in biodiversity informatics activities. These efforts should include exposure to informatics tools, their application both in biodiversity science and in informatics more broadly, and proper curation protocols for electronic data. * Promote new undergraduate curricula and graduate programs in biodiversity informatics, particularly those that are cross-disciplinary (e.g., engineering, computer science, geography, library science). Develop opportunities for US students to gain international experience through biodiversity informatics training experiences using specimens and data that originated in other countries. * Expand museum studies programs or biology degrees to include biodiversity informatics as applied to biocollections and exposure to topics such as informatics programming museum, visualization engineering, education and outreach visuals, natural language processing, and Web ontologies. 3.2. Establish career paths and professional retention incentives for data and specimen management and curation. * Develop evaluation mechanisms that recognize and reward the products of successful careers in biodiversity informatics. * Develop a standardized nomenclature and hierarchy for careers in biodiversity informatics that can inform position descriptions, hiring, and criteria for promotion. 3.3. Provide opportunities that encourage more people to become biodiversity software developers and that encourage the development of more biodiversity informatics software. * Develop workshop training and software developer courses in biodiversity informatics. * Develop schema that are accessible and establish service standards. * Train experts and students in the various aspects of tool development and programming (e.g., MySQL). * Collaborate with commercial firms to provide employment opportunities for biodiversity software developers who graduate from academic tracks. Your project?

Biological Informatics Bioinformatics Biodiversity Informatics molecular to gene organism to ecosystem where does one get these data and computational literacy skills and knowledge? For Biodiversity Informatics: What human skills and software tools are needed to collect, manage, and do research with this specimen and related data? What infrastructure is needed (hardware and software)? What data standards are needed? What data and computational literacy skills and knowledge are required through the data pipeline from data collection to digitization to data use / re-use? From NIBA 3.1. Implement new training opportunities in biodiversity informatics. * Develop new opportunities and expand existing training programs for collections professionals so that they can more fully engage in biodiversity informatics activities. These efforts should include exposure to informatics tools, their application both in biodiversity science and in informatics more broadly, and proper curation protocols for electronic data. * Promote new undergraduate curricula and graduate programs in biodiversity informatics, particularly those that are cross-disciplinary (e.g., engineering, computer science, geography, library science). Develop opportunities for US students to gain international experience through biodiversity informatics training experiences using specimens and data that originated in other countries. * Expand museum studies programs or biology degrees to include biodiversity informatics as applied to biocollections and exposure to topics such as informatics programming museum, visualization engineering, education and outreach visuals, natural language processing, and Web ontologies. 3.2. Establish career paths and professional retention incentives for data and specimen management and curation. * Develop evaluation mechanisms that recognize and reward the products of successful careers in biodiversity informatics. * Develop a standardized nomenclature and hierarchy for careers in biodiversity informatics that can inform position descriptions, hiring, and criteria for promotion. 3.3. Provide opportunities that encourage more people to become biodiversity software developers and that encourage the development of more biodiversity informatics software. * Develop workshop training and software developer courses in biodiversity informatics. * Develop schema that are accessible and establish service standards. * Train experts and students in the various aspects of tool development and programming (e.g., MySQL). * Collaborate with commercial firms to provide employment opportunities for biodiversity software developers who graduate from academic tracks. Your project?

NIBA Implementation Plan - Goal 3 Goal 3: Enhance the training of existing collections staff and create the next generation of biodiversity information managers 3.1. Implement new training opportunities in biodiversity informatics. 3.2. Establish career paths and professional retention incentives for data and specimen management and curation. 3.3 Provide opportunities that encourage more people to become biodiversity software developers and that encourage the development of more biodiversity informatics software. 3.1. Implement new training opportunities in biodiversity informatics. * Develop new opportunities and expand existing training programs for collections professionals so that they can more fully engage in biodiversity informatics activities. These efforts should include exposure to informatics tools, their application both in biodiversity science and in informatics more broadly, and proper curation protocols for electronic data. * Promote new undergraduate curricula and graduate programs in biodiversity informatics, particularly those that are cross-disciplinary (e.g., engineering, computer science, geography, library science). Develop opportunities for US students to gain international experience through biodiversity informatics training experiences using specimens and data that originated in other countries. * Expand museum studies programs or biology degrees to include biodiversity informatics as applied to biocollections and exposure to topics such as informatics programming museum, visualization engineering, education and outreach visuals, natural language processing, and Web ontologies. 3.2. Establish career paths and professional retention incentives for data and specimen management and curation. * Develop evaluation mechanisms that recognize and reward the products of successful careers in biodiversity informatics. * Develop a standardized nomenclature and hierarchy for careers in biodiversity informatics that can inform position descriptions, hiring, and criteria for promotion. 3.3. Provide opportunities that encourage more people to become biodiversity software developers and that encourage the development of more biodiversity informatics software. * Develop workshop training and software developer courses in biodiversity informatics. * Develop schema that are accessible and establish service standards. * Train experts and students in the various aspects of tool development and programming (e.g., MySQL). * Collaborate with commercial firms to provide employment opportunities for biodiversity software developers who graduate from academic tracks. Your project?

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