@article {1537,
	title = {Cleaning  Validating and Enhancing Data with Open Refine},
	year = {2013},
	keywords = {iDigBio Georeferencing Workshop Group (GWG), iDigBio GWG TTT 2},
	url = {https://www.idigbio.org/sites/default/files/workshop-presentations/ttt2/OpenRefineTTT22013.pptx},
	author = {Deborah L Paul}
}
@article {516,
	title = {Entomological Collections Network 2012: Update from the iDigBio HUB},
	year = {2012},
	abstract = {iDigBio{\textquoteright}s Second Summit is October 23 - 24, 2012 in Gainesville, FL. At this event, iDigBio - Integrated Digitized Biocollections - and the Thematic Collections Networks (TCNs) will meet to discuss progress during the first year and goals for upcoming years. At ECN \& ESA, I will present an update of activities at iDigBio and answer frequently asked questions about our structure, including "What is iDigBio? Where did we come from and what makes us unique? When is iDigBio going live with real data? Where is the data coming from? What does the data portal look like?" My talk will also provide information about the services/tools currently available through iDigBio and what is proposed for the future. Finally, I will summarize the efforts of our current working groups, which include Workflows, Authority Files, Standards, Augmenting Optical Character Recognition (OCR), Cyberinfrastructure and Public Participation in Science. Interested parties are encouraged to join an existing TCN with a PEN proposal, propose a new TCN, suggest a workshop or join an existing working group.},
	keywords = {ECN, Entomological Collections Network, entomology, ESA, HUB, iDigBio},
	url = {http://www.idigbio.org/sites/default/files/workshop-presentations/ecn-esa2012/HUBupdateESA_iDigBio.pptx},
	author = {Deborah L Paul and Gregory Riccardi and Gil Nelson}
}
@article {517,
	title = {Entomological Society of America (ESA) 2012: Update from the iDigBio HUB},
	year = {2012},
	abstract = {iDigBio{\textquoteright}s Second Summit is October 23 - 24, 2012 in Gainesville, FL. At this event, iDigBio - Integrated Digitized Biocollections - and the Thematic Collections Networks (TCNs) will meet to discuss progress during the first year and goals for upcoming years. At ESA/ECN, I will present an update of activities at iDigBio and answer frequently asked questions about our structure, including "What is iDigBio? Where did we come from and what makes us unique? When is iDigBio going live with real data? Where is the data coming from? What does the data portal look like?" My talk will also provide information about the services/tools currently available through iDigBio and what is proposed for the future. Finally, I will summarize the efforts of our current working groups, which include Workflows, Authority Files, Standards, Augmenting Optical Character Recognition (OCR), Cyberinfrastructure and Public Participation in Science. Interested parties are encouraged to join an existing TCN with a PEN proposal, propose a new TCN, suggest a workshop or join an existing working group. },
	keywords = {Entomological Society of America, ESA, HUB, iDigBio},
	url = {http://www.idigbio.org/sites/default/files/workshop-presentations/ecn-esa2012/HUBupdateESA_iDigBio.pptx},
	author = {Deborah L Paul and Gregory Riccardi and Gil Nelson}
}
@article {225,
	title = {Five task clusters that enable efficient and effective digitization of biological collections},
	journal = {ZooKeys},
	volume = {209},
	year = {2012},
	month = {07/2012},
	chapter = {19},
	abstract = {This paper describes and illustrates five major clusters of related tasks (herein referred to as task clusters) that are common to efficient and effective practices in the digitization of biological specimen data and media. Examples of these clusters come from the observation of diverse digitization processes. The staff of iDigBio (The U.S. National Science Foundation{\textquoteright}s National Resource for Advancing Digitization of Biodiversity Collections) visited active biological and paleontological collections digitization programs for the purpose of documenting and assessing current digitization practices and tools. These observations identified five task clusters that comprise the digitization process leading up to data publication: (1) predigitization curation and staging, (2) specimen image capture, (3) specimen image processing, (4) electronic data capture, and (5) georeferencing locality descriptions. While not all institutions are completing each of these task clusters for each specimen, these clusters describe a composite picture of digitization of
biological and paleontological specimens across the programs that were observed. We describe these clusters, three workflow patterns that dominate the implemention of these clusters, and offer a set of workflow recommendations for digitization programs.},
	keywords = {ADBC, biodiversity informatics, Biological specimen collections, curation, digitization, EF-1115210, iDigBio, Imaging, paleontological specimen collections, task cluster, workflow},
	doi = {doi: 10.3897/zookeys.209.3135},
	url = {http://www.pensoft.net/journals/zookeys/article/3135/five-task-clusters-that-enable-efficient-and-effective-digitization-of-biological-collections},
	author = {Gil Nelson and Deborah L Paul and Gregory Riccardi and Austin R. Mast}
}
@conference {547,
	title = {iConference2013: Augmenting optical character recognition (OCR) for improved digitization: Strategies to access scientific data in natural history collections},
	booktitle = {iConference 2013},
	year = {2013},
	month = {02/2013},
	publisher = {iSchools},
	organization = {iSchools},
	address = {Ft. Worth, Texas},
	abstract = {The Augmenting OCR Working Group (A-OCR WG) at Integrated Digitized Biocollections (iDigBio) seeks to improve community OCR strategies and algorithms for faster, better parsing of OCR output derived from valuable data on natural history collection specimen labels. This task is exceedingly difficult because museum labels are often annotated, and vary in content, form and font. Under the National Science Foundation{\textquoteright}s (NSF) Advancing Digitization of Biological Collections (ADBC) program, iDigBio is building a cyberinfrastructure to aggregate quality data from museum specimens housed in collections across the United States for use by researchers, educators, environmentalists and the public. Since March of 2012, the A-OCR WG formed from community consensus to begin its role in this endeavor, defining reachable goals including setting up a hackathon concurrent with iConference 2013. This paper reports on the definition of some key problems identified by the A-OCR WG since these science problems will drive research and cyberinfrastructure development.},
	keywords = {EF-1115210, iConference2013, iDigBio, information analysis, information organization, information retrieval, information services, machine language, Natural Language, OCR, qualitative data analysis, research methods},
	doi = {10.9776/13266},
	url = {https://www.ideals.illinois.edu/bitstream/handle/2142/39427/266.pdf?sequence=4},
	author = {Deborah L Paul and Heidorn, P. Bryan}
}
@conference {546,
	title = {iConference2013: Improving the Character of Optical Character Recognition (OCR): iDigBio Augmenting OCR Working Group Seeks Collaborators and Strategies to Improve OCR Output and Parsing of OCR Output},
	booktitle = {iConference 2013},
	year = {2013},
	month = {02/2013},
	publisher = {iSchools},
	organization = {iSchools},
	address = {Ft. Worth, Texas},
	abstract = {There are an estimated 2 {\textendash} 3 billion museum specimens world {\textendash} wide (OECD 1999, Ari{\~n}o 2010). In an effort to increase the research value of their collections, institutions across the U. S. have been seeking new ways to cost effectively transcribe the label information associated with these specimen collections. Current digitization methods are still relatively slow, labor-intensive, and therefore expensive. New methods, such as optical character recognition (OCR), natural language processing, and human-in-the-loop assisted parsing are being explored to reduce these costs. The National Science Foundation (NSF), through the Advancing Digitization of Biodiversity Collections (ADBC) program, funded Integrated Digitized Biocollections (iDigBio) in 2011 to create a Home Uniting Biodiversity Collections (HUB) cyberinfrastructure to aggregate and collectively integrate specimen data and find ways to digitize specimen data faithfully and faster and disseminate the knowledge of how to achieve this. The iDigBio Augmenting OCR Working Group is part of this national effort. - speed up the overall digitization process, - lower the cost, - improve overall efficiency, - assure digitized data is fit-for-use (NIBA 2010, Chapman 2005), and - provide the resulting digitized data records to researchers more quickly. The iDigBio Augmenting OCR (A-OCR) working group is actively engaged in identifying opportunities for collaboration to leverage OCR tools and technologies that are successful (both within and outside of the biology digitization domain) and disseminate these tools to the public or seek funding for development.},
	keywords = {EF-1115210, iConference2013, iDigBio, information analysis, information organization, information retrieval, information services, machine language, Natural Language, OCR, qualitative data analysis, research methods},
	doi = {10.9776/13493},
	url = {https://www.ideals.illinois.edu/bitstream/handle/2142/42089/493.pdf?sequence=2},
	author = {Robert Anglin and Jason Best and Figueiredo, Renato and Gilbert, Edward and Gnanasambandam, Nathan and Gottschalk, Stephen and Haston, Elspeth and Heidorn, P. Bryan and Lafferty, Daryl and Lang, Peter and Nelson, Gil and Deborah L Paul and Ulate, William and Kimberly Watson and Zhang, Qianjin}
}
@article {559,
	title = {iConference2013: Introducing iDigBio and the Augmenting OCR Working Group},
	year = {2013},
	abstract = {Highlights of this introduction include: "What is iDigBio? Who is the AOCR wg?" Why we are here at iConference2013? Where did we come from and what makes us unique? Where is our data coming from? and How can the iSchools community get involved?{\textquotedblright} The AOCR wg is working to find ways to speed up and improve access to digitization of natural history museum specimen data and we think the Information Science community can help. Five talks follow, explaining unique key parts of our story. Note the iDigBio* Augmenting Optical Character Recognition Working Group (AOCR wg) put together 4 submissions for iSchools iConference2013: this workshop, a paper, a poster, and an alternative event. All of these are concurrent with a Hackathon at the Botanical Research Institute of Texas (BRIT) as part of a strategic outreach effort. Interested parties are encouraged to participate in our Hackathon, join an existing iDigBio working group, propose and host a workshop, and contribute to our forums and online materials.

        Integrated Digitized Biocollections (iDigBio) is a National Science Foundation (NSF) project funded under the Advancing Digitization of Biological Collections (ADBC) program. Thematic Collection (Museum) Networks (TCNs) are NSF-funded to digitize specimen data needed to answer grand challenge questions and provide that data to iDigBio. iDigBio is building a cyberinfrastructure to integrate data from museums across the USA, making it accessible to everyone. 

},
	keywords = {Augmenting Optical Character Recognition, Darwin Core, iConference2013, iDigBio, Information Science, Natural Language Processing, Parsing, XML},
	url = {https://www.idigbio.org/sites/default/files/workshop-presentations/aocr-hackathon/LABELX.pdf/iConference2013WorkshopDP.pptx},
	author = {Deborah L Paul}
}
@article {274,
	title = {iDigBio Botany 2012 Workshop: Morphbank},
	year = {2012},
	abstract = {This presentation was given by Deborah Paul at the iDigBio Botany 2012 Workshop.},
	keywords = {iDigBio Botany 2012 Workshop},
	url = {https://www.idigbio.org/sites/default/files/workshop-presentations/botany2012/workshop/MorphbankQuickTourV2_Botany2012.pptx},
	author = {Deborah L Paul}
}
@article {308,
	title = {iDigBio Digitizing Plant Specimens Workshop: Pre \& Post Digitization Curation },
	year = {2012},
	abstract = {iDigBio "Digitizing Plant Specimens Workshop" Valdosta,Georgia September 2012},
	keywords = {Digitizing Plant Specimens Workshop 2012},
	url = {https://www.idigbio.org/sites/default/files/workshop-presentations/dpc2012/PrePostDigitizationCurationDP.pptx},
	author = {Deborah L Paul}
}
@article {307,
	title = {iDigBio Digitizing Plant Specimens Workshop: Sharing Data},
	year = {2012},
	abstract = {iDigBio "Digitizing Plant Specimens Workshop" Valdosta,Georgia September 2012},
	keywords = {Digitizing Plant Specimens Workshop 2012},
	url = {https://www.idigbio.org/sites/default/files/workshop-presentations/dpc2012/SharingDataDP.pptx},
	author = {Deborah L Paul}
}
@article {545,
	title = {iDigBio Hackathon: 1st iDigBio - BRIT Hackathon},
	year = {2013},
	abstract = {Overview of the Hackathon goals and introduction to iDigBio for those new to the project. Review this presentation before the other hackathon presentations to learn about the aOCR working group and the talks / presentations / work being done at this hackathon and after.},
	keywords = {Hackathon, Image Segmentation, Machine Learning, Natural Language, OCR, Parsing, Web Services, WorkFlows},
	url = {https://www.idigbio.org/sites/default/files/workshop-presentations/aocr-hackathon/1stiDigBio_BRITHackathon.pptx},
	author = {Deborah L Paul}
}
@article {438,
	title = {iDigBio Paleocollections Workshop 2012: Discovering Effective Workflows},
	year = {2012},
	keywords = {iDigBio Paleocollections Workshop 2012},
	url = {https://www.idigbio.org/sites/default/files/videos/slides/EffectiveWorkflowsPaleoWorkshop.pptx},
	author = {Deborah L Paul}
}
@article {437,
	title = {iDigBio Paleocollections Workshop 2012: Intro to Morphbank Image Repository Plus...},
	year = {2012},
	abstract = {This talk is designed as an overview, an introduction to Morphbank and specifically focuses on main features of Morphbank and using the custom workbook to allow paleontologists to share / store all pertinent metadata desired / required.},
	keywords = {2012, iDigBio Paleocollections Workshop April 26-29},
	url = {https://www.idigbio.org/sites/default/files/videos/slides/mbPaleoWorkshop.pptx},
	author = {Deborah L Paul}
}
@article {470,
	title = {IDigBio Summit II: Augmenting OCR (aOCR)},
	year = {2012},
	keywords = {IDigBio Summit II},
	url = {https://www.idigbio.org/sites/default/files/workshop-presentations/summit2/Paul_AocrSummit2012.pptx},
	author = {Edward Gilbert and Deborah L Paul}
}
@article {473,
	title = {IDigBio Summit II: Georeferencing (GWG)},
	year = {2012},
	keywords = {IDigBio Summit II},
	url = {https://www.idigbio.org/sites/default/files/workshop-presentations/summit2/wg_paul_GeotrainSummit2012_db_dp_shari.pptx},
	author = {Deborah L Paul and David Bloom and Shari Ellis}
}
@article {677,
	title = {Integrating Augmented OCR and Georeferencing in Natural History Collection (NHC)~Digitization},
	year = {2013},
	keywords = {SPNHC, SPNHC 2013},
	url = {https://www.idigbio.org/sites/default/files/workshop-presentations/spnhc2013/SPHNC2013_aOCR_GWGnew.pdf},
	author = {Deborah L Paul}
}
@article {1888,
	title = {Introduction to the Five Task Clusters of Digitization},
	year = {2014},
	keywords = {SiBBr 2014},
	url = {https://www.idigbio.org/wiki/images/0/06/IntroTo5TaskClusters_SiBBr.pdf},
	author = {Deborah L Paul}
}
@article {1328,
	title = {SPNHC 2014: Progress in Digitization: Using optical character recognition (OCR) output in digitization},
	year = {2014},
	abstract = {Before iDigBio, that{\textquoteright}s Integrated Digitized Biocollections, others began the work of figuring out how to use OCR output with machine learning (ML) and natural language processing (NLP) to improve the efficiency and speed with which data from museum specimen label images can be captured and validated. The Augmenting Optical Character Recognition (aOCR WG) Working Group at iDigBio is pleased to be building on that foundation. Improvements have been realized in parsing algorithms and visualization of data. Recently, researchers at The Royal Botanic Garden Edinburgh (RBGE) successfully used word clouds from OCR output to reveal useful data, otherwise dark, until a specimen label was digitized completely (Haston, et al TDWG 2013). Their work indicates this method results in greater transcriber job satisfaction. Inspired by this work, the OCR Integration Track Team at the iDigBio Citscribe Hackathon showed how indexing, scoring, and visualizing OCR output reveals otherwise hidden search terms, uncovers errors, and can improve the data transcriber and data validator experience. Using open-source software, we presented these ideas to those with transcription tools up-and-running including Notes From Nature, Biodiversity Heritage Library (BHL), ALA Biodiversity Volunteer Portal, Smithsonian Digital Volunteers, and the Lichen, Bryophytes and Climate Change Volunteer Portal using Symbiota software. The aOCR WG is working collaboratively with the Joint Research Activity (JRA) Synthesys3 Project to share expertise for automated data collection for digital images. Got text in your images? How might OCR output work for you? Come talk to our aOCR WG to find out and to share your expertise.},
	keywords = {confidence scores, data visualization, digitization, Machine Learning, Natural Language Processing, optical character recognition, SPNHC 2014, SPNHC 2014: Progress in Digitization},
	url = {https://www.idigbio.org/sites/default/files/workshop-presentations/spnhc2014/Paul_UsingOCRoutput.pptx},
	author = {Deborah L Paul and Andrea Matsunaga and Miao Chen and Jason Best and Sylvia Orli and Elspeth M Haston}
}
