Databasing References: Difference between revisions

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== Natural History Specimen Digitization : Challenges and Concerns, by A. Vollmar, J. A. Macklin, L. S. Ford., Biodiversity Informatics, 7, pp. 93-112. ==

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https://journals.ku.edu/index.php/jbi/article/viewFile/3992/3806#

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!scope="col" | Description ||

A survey on the challenges and concerns involved with digitizing natural history specimens was circulated to curators, collections managers, and administrators in the natural history community in the Spring of 2009, with over 200 responses received. The overwhelming barrier to digitizing collections was a lack of funding or issues directly related to funding, leaving institutions mostly responsible for providing the necessary support. The uneven digitization landscape leads to a patchy accumulation of records at varying qualities, and based on different priorities, ultimately influencing the data's fitness for use. The survey results also indicated that although the kind of specimens found in collections and their storage can be quite variable, there are many similar challenges across disciplines when digitizing including imaging, automated text scanning and parsing, geo-referencing, etc. Thus, better communication between domains could foster knowledge on digitization leading to efficiencies that could be disseminated through documentation of best practices and training.

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== New York Botanical Garden Virtual Herbarium Best Practices Guide. ==

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http://sciweb.nybg.org/Science2/hcol/mtsc/NYBG_Best_Practices.doc

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!scope="col"; style="vertical-align:top";  | Description ||  

The purpose of this guide is to lay out the governing principles and procedures that have evolved over the ten years of experience with the NYBG Virtual Herbarium. Hopefully this document will be useful in future years in explaining the rationale behind the approach taken and decisions made along the way, and may be useful to other institutions who are just now embarking on a Virtual Herbarium project, or searching for comparative or benchmark data.

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== Not another frickin' database!, by Michael Wall. ==

!scope="col" width="15%" | Pub Date || 2010

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http://www.ecnweb.org/dev/files/13_Wall_2010.pdf#

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!scope="col"; style="vertical-align:top";  | Description ||  

This document reports on the Entomology Collection Health Online database at San Diego Natural History Museum. ECHO is not a specimen database. Rather, ECHO allows users to search the collection of taxa, assess the collection health of those taxa, and examine large images of drawers containing taxa. All drawers and schmidt boxes in the collection are catalogued to the lowest determined taxonomic level. SDNHM contains 219 databased drawers. Data on curatorial health is available for approximately 42,100 specimens.

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== Principals of Data Quality, A. Chapman. ==

!scope="col" width="15%" | Pub Date || 2005, GBIF

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!scope="col" | URL ||   

http://imsgbif.gbif.org/CMS_ORC/?doc_id=1229&download=1#

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!scope="col" | Description ||

There are many data quality principles that apply when dealing with species data and especially with the spatial aspects of those data. These principles are involved at all stages of the data management process. A loss of data quality at any one of these stages reduces the applicability and uses to which the data can be adequately put. These include: Data capture and recording at the time of gathering, Data manipulation prior to digitisation (label preparation, copying of data to a ledger, etc.), Identification of the collection (specimen, observation) and its recording, Digitisation of the data, Documentation of the data (capturing and recording the metadata), Data storage and archiving, Data presentation and dissemination (paper and electronic publications, web-enabled databases, etc.), Using the data (analysis and manipulation). All these have an input into the final quality or “fitness for use” of the data and all apply to all aspects of the data – the taxonomic or nomenclatural portion of the data – the “what”, the spatial portion – the “where” and other data such as the “who” and the “when” (Berendsohn 1997). Before a detailed discussion on data quality and its application to species-occurrence data can take place, there are a number of concepts that need to be defined and described. These include the term data quality itself, the terms accuracy and precision that are often misapplied, and what we mean by primary species data and species-occurrence data.

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== Reference Model for an Open Archival Information System (OAIS), by the Space Data Systems, Consultative Committee. ==

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This document is a technical recommendation for use in developing a broader consensus on what is required for an archive to provide permanent or indefinite long-term preservation of digital information. The recommendation establishes a common framework of terms and concepts which comprise an Open Archival Information System (OAIS). It allows existing and future archives to be more meaningfully compared and contrasted. It provides a basis for further standardization within an archival context and it should promote greater vendor awareness of, and support of, archival requirements. Through the process of normal evolution, it is expected that expansion, deletion, or modification of this document may occur. This Recommendation is therefore subject to CCSDS document management and change control procedures which are defined in Procedures Manual for the Consultative Committee for Space Data Systems.

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== Relational database design and implementation for biodiversity informatics, by P. J. Morris, PhyloInformatics 7: 1-66 - 2005. ==

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http://www.athro.com/general/Phyloinformatics_7_85x11.pdf#

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!scope="col" | Description ||

The complexity of natural history collection information and similar information within the scope of biodiversity informatics poses significant challenges for effective long term stewardship of that information in electronic form. This paper discusses the principles of good relational database design, how to apply those principles in the practical implementation of databases, and examines how good database design is essential for long term stewardship of biodiversity information. Good design and implementation principles are illustrated with examples from the realm of biodiversity information, including an examination of the costs and benefits of different ways of storing hierarchical information in relational databases. This paper also discusses typical problems present in legacy data, how they are characteristic of efforts to handle complex information in simple databases, and methods for handling those data during data migration.

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== Report on trial of SatScan tray scanner system by SmartDrive Ltd., by V. Blagoderov, I. Kitching, T. Simonsen, V. Smith; Natural History Museum, London. ==

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!scope="col" | Description ||

Smartdrive Ltd. has developed a prototype imaging system, SatScan, that captures digitised images of large areas while keeping smaller objects in focus at very high resolution. The system was set up in the Sackler Biodiversity Imaging laboratory of Natural History Museum on March 8, 2010 for a one-month trial. A series of projects imaging parts of the entomological, botanical, and palaeoentomological collections were conducted to assess the system's utility for museum collection management and biodiversity research. The technical and practical limitations of the system were investigated as part of this process.The SatScan system facilitates the capturing of a very large number of good quality images in a very short time. Large parts of the NHM collection could be digitised in dorsal view extremely quickly. These images have a wide range of uses across research, collection management, and public engagement. Scalability of the system is limited by our desire to assign unique identifiers (a number and/or a barcode) to specimens, and the cropping of these images. Without these identifiers digitised images will have limited long term value. The assignment of specimen level identifiers is potentially labour intensive. Options for assigning identifiers were not investigated as part of this trail but include the use of physical labels on each specimen (with significant resource implications and a significant volunteer workforce) and the use of virtual identifiers (as a virtual layer over the image, perhaps automatically assigned, and possible coupled with physical labels attached to specimens as dictated by recuration activities). Intuitive software (with a web interface) needs to be developed to facilitate this process, including support for cropping of an image and the automatic assignment and printing of an identifier label. On-demand assignment of identifiers would allow us to prioritize the digitisation but it will represent a significant change to the way we curate our collections and would require sustained and ongoing support from Collection Management. Additional concerns relate to the amount of storage space required to manage images, connection with existing digital systems and the utility of dorsal images for certain parts of the collection. These problems need to be addressed as part of a larger scale study.

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== Scientific Collections: Mission-Critical Infrastructure for Federal Science Agencies, A Report of the Interagency Working Group on Scientific Collections. ==

!scope="col" width="15%" | Pub Date || 2009

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!scope="col" | URL ||  http://www.whitehouse.gov/sites/default/files/sci-collections-report-2009-rev2.pdf#

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!scope="col"; style="vertical-align:top";  | Description ||  

This report represents the first step in an ongoing process of identifying and characterizing scientific collections and determining their long-term stewardship needs. Robust interagency collaboration will remain vital as we develop a systematic approach to safeguarding these scientific treasures for generations of scientists. Also see: https://www.ida.org/upload/stpi/pdfs/ida-d-3694-final.pdf

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== Semi-automated workflows for acquiring specimen data from label images in herbarium collections, Taxon, Volume 59, Number 6, pp. 1830-1842.==

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December 2010

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http://www.ingentaconnect.com/content/iapt/tax/2010/00000059/00000006/art00014#

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!scope="col"; style="vertical-align:top";  | Description ||  

Computational workflow environments are an active area of computer science and informatics research; they promise to be effective for automating biological information processing for increasing research efficiency and impact. In this project, semi-automated data processing workflows were developed to test the efficiency of computerizing information contained in herbarium plant specimen labels. Our test sample consisted of Mexican and Central American plant specimens held in the University of michigan Herbarium (MICH). The initial data acquisition process consisted of two parts: (1) the capture of digital images of specimen labels and of full-specimen herbarium sheets, and (2) creation of a minimal field database, or "pre-catalog", of records that contain only information necessary to uniquely identify specimens. For entering "pre-catalog" data, two methods were tested: key-stroking the information (a) from the specimen labels directly, or (b) from digital images of specimen labels. In a second step, locality and latitude/longitude data fields were filled in if the values were present on the labels or images. If values were not available, geo-coordinates were assigned based on further analysis of the descriptive locality information on the label. Time and effort for the various steps were measured and recorded. Our analysis demonstrates a clear efficiency benefit of articulating a biological specimen data acquisition workflow into discrete steps, which in turn could be individually optimized. First, we separated the step of capturing data from the specimen from most keystroke data entry tasks. We did this by capturing a digital image of the specimen for the first step, and also by limiting initial key-stroking of data to create only a minimal "pre-catalog" database for the latter tasks. By doing this, specimen handling logistics were streamlined to minimize staff time and cost. Second, by then obtaining most of the specimen data from the label images, the more intellectually challenging task of label data interpretation could be moved electronically out of the herbarium to the location of more highly trained specialists for greater efficiency and accuracy. This project used experts in the plants' country of origin, Mexico, to verify localities, geography, and to derive geo-coordinates. Third, with careful choice of data fields for the "pre-catalog" database, specimen image files linked to the minimal tracking records could be sorted by collector and date of collection to minimize key-stroking of redundant data in a continuous series of labels, resulting in improved data entry efficiency and data quality.

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== Specimen Imaging Documentation: Consortium of Pacific Northwest Herbaria, Version 4.0. ==

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!scope="col" | URL ||   

http://www.pnwherbaria.org/documentation/imaging-documentation-v4.pdf#

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!scope="col" | Description ||

Detailed, step-by-step documentation for herbarium imaging/label capture from the Consortium of Pacific Northwest Herbaria.

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== The AIC Guide to Digital Photography and Conservation Documentation ==

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!scope="col" | URL ||   

http://www.conservation-us.org/index.cfm?fuseaction=Page.ViewPage&PageID=1531

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!scope="col" | Description ||

AIC has published the long-awaited second edition of the AIC Guide to Digital Photography and Conservation Documentation. This book is a comprehensive guide to digital photographic equipment, software, and processing tailored to the needs of conservation professionals. Authors Franziska Frey, Dawn Heller, Dan Kushel, Timothy Vitale, Jeffrey Warda (editor), and Gawain Weaver have more than doubled the size of the first edition, which includes major extensions and updates to the text and is fully illustrated with over 120 color figures. This second edition also has a wraparound internal spiral binding, allowing the book to lay flat.

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== The use of specimen label images for efficient data acquisition in research collections cataloguing: Workflow, Ingio Granzow-de la Cerda, Juan Carols Gomez-Martinez, Jose Luis Garcia-Castillo.  ==

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http://tdwg2006.tdwg.org/fileadmin/2006meeting/slides/GranzowCerda_ImagesM%C3%A9xMichCatalog_abs0098.pdf#

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!scope="col" | Description ||

A presentation about an NSF-BRC project to digitize specimen of Mexican plants at the University of Michigan Herbarium, including consideration of equipment, work flow, and databasing.

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==  Uses of Primary Species-Occurence Data, by A. Chapman. ==

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2005, GBIF

!scope="col"; style="vertical-align:top";  | Description ||  

This paper examines uses for primary species occurrence data in research, education, and in other areas of human endeavour, and provides examples from the literature of many of these uses. The paper examines not only data from labels, or from observational notes, but the data inherent in museum and herbarium collections themselves, which are long-term storage receptacles of information and data that are still largely untouched. Projects include the study of the species and their distributions through both time and space, their use for education, both formal and public, for conservation and scientific research, use in medicine and forensic studies, in natural resource management and climate change, in art, history and recreation, and for social and political use. Uses are many and varied and may well form the basis of much of what we do as people every day.

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== Utility (and Shortcomings) of High Resolution Drawer Imaging for Remote Curation and Outreach, by M. Bertone, A. Deans, North Carolina State University.  ==

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http://www.ecnweb.org/dev/files/17_Bertone_2010.pdf#

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!scope="col"; style="vertical-align:top";  | Description ||  

A very good presentation to Entomology 2010 about NCSU's drawer imaging system using Gigapan technology.

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==  VertNet: A New Model for Biodiversity Data Sharing, by Heather Constable, Robert Guralnick, John Wieczorek, Carol Spencer, A. Townsend Peterson, The VertNet Steering Committee, PLoS Biology, Volume 8, Issue 2, e1000309. ==

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http://www.plosbiology.org/article/fetchObjectAttachment.action?uri=info%3Adoi%2F10.1371%2Fjournal.pbio.1000309&representation=PDF#

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!scope="col"; style="vertical-align:top";  | Description ||  

A paper on the vertebrate biodiversity networks. The fundamental concept underlying the vertebrate biodiversity networks is that data contributors are the primary and authoritative source for information about the occurrence data over which they have custody. The networks merely facilitate access and sharing of these distributed primary resources. A fully decentralized architecture, with all requests distributed directly to the primary sources, highlighted the primacy of the contributing institutions and was an essential phase in promoting participation, instilling confidence and a sense of control within the community.

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