The Experts below are selected from a list of 15486 Experts worldwide ranked by ideXlab platform
Joan Echtenkamp Klein - One of the best experts on this subject based on the ideXlab platform.
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The Philip S. Hench Walter Reed Yellow fever Collection Digitization Project: Two years and over 5,000 documents later
Journal of Archival Organization, 2002Co-Authors: Joan Echtenkamp KleinAbstract:Abstract The Philip S. Hench Walter Reed Yellow Fever Collection is the cornerstone collection in the Claude Moore Health Sciences Library's Historical Collections at the University of Virginia and, beyond the walls of the library, is of national significance. This article provides information on the collection and describes the Philip S. Hench Walter Reed Yellow Fever Collection Digitization Project, a digital Project supported by a two-year Institute of Museums and Library Services (IMLS) grant, that contains more than 5,000 documents selected from the collection. In addition to providing digital surrogates, the Project also supplied important metadata to enhance retrieval of those documents by utilizing the Text Encoded Initiative (TEI) and the Encoded Archival Description (EAD).
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The Philip S. Hench Walter Reed Yellow fever Collection Digitization Project: Two years and over 5,000 documents later
Journal of Archival Organization, 2002Co-Authors: Joan Echtenkamp KleinAbstract:Abstract The Philip S. Hench Walter Reed Yellow Fever Collection is the cornerstone collection in the Claude Moore Health Sciences Library's Historical Collections at the University of Virginia and, beyond the walls of the library, is of national significance. This article provides information on the collection and describes the Philip S. Hench Walter Reed Yellow Fever Collection Digitization Project, a digital Project supported by a two-year Institute of Museums and Library Services (IMLS) grant, that contains more than 5,000 documents selected from the collection. In addition to providing digital surrogates, the Project also supplied important metadata to enhance retrieval of those documents by utilizing the Text Encoded Initiative (TEI) and the Encoded Archival Description (EAD).
Pnina Shor - One of the best experts on this subject based on the ideXlab platform.
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The Leon Levy Dead Sea Scrolls Digital Library: The Digitization Project of the Dead Sea Scrolls
Digital Humanities in Biblical Early Jewish and Early Christian Studies, 2014Co-Authors: Pnina ShorAbstract:The Digitization Project of the Dead Sea Scrolls (DSS) was first conceived as yet another conservation effort to preserve the scrolls. The Israel Antiquities Authority (IAA) set out to develop a non-invasive monitoring methodology of their physical state, based on multi-spectral images. Once the IAA realized that they were going to create the best possible images to date and since all of the scrolls have been formally published, they decided to conduct a comprehensive Digitization Project in addition to developing a monitoring system. The IAA would image all of the DSS, including thousands of fragments, add their metadata, and put everything online, making it available to the public and the scholarly world alike in a way never before imagined.
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development of a technique based on multi spectral imaging for monitoring the conservation of cultural heritage objects
Analytica Chimica Acta, 2011Co-Authors: Emilio Marengo, Marcello Manfredi, Orfeo Zerbinati, Elisa Robotti, Eleonora Mazzucco, Fabio Gosetti, Greg Bearman, Pnina ShorAbstract:A new approach for monitoring the state of conservation of cultural heritage objects surfaces is being developed. The technique utilizes multi-spectral imaging, multivariate analysis and statistical process control theory for the automatic detection of a possible deterioration process, its localization and identification, and the wavelengths most sensitive to detecting this before the human eye can detect the damage or potential degradation changes occur. A series of virtual degradation analyses were performed on images of parchment in order to test the proposed algorithm in controlled conditions. The spectral image of a Dead Sea Scroll (DSS) parchment, IAA (Israel Antiquities Authority) inventory plate # 279, 4Q501 Apocryphal Lamentations B, taken during the 2008 Pilot of the DSS Digitization Project, was chosen for the simulation.
Brian Harrington - One of the best experts on this subject based on the ideXlab platform.
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optical music recognition system within a large scale Digitization Project
International Symposium Conference on Music Information Retrieval, 2000Co-Authors: Ichiro Fujinaga, Sayeed G Choudhury, Tim Dilauro, Michael Droettboom, Karl Macmillan, Brian HarringtonAbstract:An adaptive optical music recognition system is being developed as part of an experiment in creating a comprehensive framework of tools to manage the workflow of large-scale Digitization Projects. This framework will support the path from physical object and/or digitized material into a digital library repository, and offer effective tools for incorporating metadata and perusing the content of the resulting multimedia objects. The Project involves Digitization of the Lester S. Levy Collection of Sheet Music (Milton S. Eisenhower Library, Johns Hopkins University). In Phase One, images of the music and lyrics, and color images of the covers of the Levy Collection were digitized and a database of text index records was created. Phase Two consists of converting the digitized music to computer-readable music notation format along with full-text lyrics, generating sound renditions, and creating metadata to enhance search capabilities. During Phase One, the researchers at the Eisenhower Library created a database of text index records, images of the music and lyrics and color images of the cover sheets from the Levy Collection. This database is available to the general public at http://levysheetmusic.mse.jhu.edu. Currently, the Collection can be searched in three modes. First, users can search by subject, a keyword search on the text record. Each of the pieces has been indexed for the subject of the song and/or cover image. Users may also browse the Collection by the topical arrangement of the physical collection. In Phase Two, an adaptive optical music recognition (AOMR) software (Fujinaga 1997) is used to convert the TIFF image of scanned sheet music into computer readable-formats, which includes GUIDO and MIDI files along with full-text of the lyrics. These digital objects will be deposited into the data repository along with the scanned sheet music TIFF, JPEG and thumbnail, and associated metadata. The AOMR software offers five important advantages over similar commercial offerings. First, it can be run in batch processing mode, an essential feature for the Levy Collection given its large number of music sheets. It is important to note that most commercial software is intended for the casual user and does not scale for a large number of objects. Second, the software is written in C and therefore is portable across platforms. Third, the software can “learn” to recognize different music symbols—an issue considering the diversity of the Levy Collection and the universe of notated music, in general. Fourth, the software is open-sourced. Finally, this software can separate full-text lyrics that can be further processed using optical character recognition (OCR) technology. The AOMR process is divided into two major sections: symbol classification and musical semantic interpretation. The first step in the interpretation phase is to connect all inter-related symbols. In addition, many rhythmic errors can also be corrected by adjusting the metric placement of notes relative to their vertical alignment with notes in other parts. An interactive graphic editor suitable to be interfaced with the AOMR program is being developed jointly with the group working on the GUIDO editor (Renz 2000). The purpose of this editor is to correct any errors generated by the AOMR so that the corrected version then can be converted to GUIDO format. To enable powerful search and retrieval as well as user-friendly navigational mechanism, Phase Two of the Levy Project will include a strong metadata component. Commonly defined as “data about data,” metadata is structured representational information. The kinds of metadata important for Levy include descriptive (to enable searching, browsing and identification of items), structural (to enable the creation of an interface for optimum browsing and navigation), and administrative (to manage the digital components of the collection and aid users in identification of items). To further enhance the scholarly value of the Levy Collection, a web interface will be developed for a music research toolkit, for example, Humdrum (Huron 1997). These toolkits are software tools intended to assist in music research and are suitable for use in a wide variety of computer-based musical investigations, such as motivic, stylistic, and melodic analysis and concordance studies. We also propose to extend plans for developing automated means of mining authoritative name information and creating even richer name indexes. The entire Project is an experiment in developing a comprehensive framework of tools to manage the workflow of large-scale Digitization Projects. This framework will support the path from physical object and/or digitized material into a digital library repository, and offer effective tools for incorporating metadata and perusing the content of the resulting multimedia objects. The Levy Collection, with its large size and availability in digital format, is an ideal subject for development and evaluation of this proposed framework.
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ISMIR - Optical Music Recognition System within a Large-Scale Digitization Project
2000Co-Authors: Ichiro Fujinaga, Tim Dilauro, Michael Droettboom, Karl Macmillan, G. Sayeed Choudhury, Brian HarringtonAbstract:An adaptive optical music recognition system is being developed as part of an experiment in creating a comprehensive framework of tools to manage the workflow of large-scale Digitization Projects. This framework will support the path from physical object and/or digitized material into a digital library repository, and offer effective tools for incorporating metadata and perusing the content of the resulting multimedia objects. The Project involves Digitization of the Lester S. Levy Collection of Sheet Music (Milton S. Eisenhower Library, Johns Hopkins University). In Phase One, images of the music and lyrics, and color images of the covers of the Levy Collection were digitized and a database of text index records was created. Phase Two consists of converting the digitized music to computer-readable music notation format along with full-text lyrics, generating sound renditions, and creating metadata to enhance search capabilities. During Phase One, the researchers at the Eisenhower Library created a database of text index records, images of the music and lyrics and color images of the cover sheets from the Levy Collection. This database is available to the general public at http://levysheetmusic.mse.jhu.edu. Currently, the Collection can be searched in three modes. First, users can search by subject, a keyword search on the text record. Each of the pieces has been indexed for the subject of the song and/or cover image. Users may also browse the Collection by the topical arrangement of the physical collection. In Phase Two, an adaptive optical music recognition (AOMR) software (Fujinaga 1997) is used to convert the TIFF image of scanned sheet music into computer readable-formats, which includes GUIDO and MIDI files along with full-text of the lyrics. These digital objects will be deposited into the data repository along with the scanned sheet music TIFF, JPEG and thumbnail, and associated metadata. The AOMR software offers five important advantages over similar commercial offerings. First, it can be run in batch processing mode, an essential feature for the Levy Collection given its large number of music sheets. It is important to note that most commercial software is intended for the casual user and does not scale for a large number of objects. Second, the software is written in C and therefore is portable across platforms. Third, the software can “learn” to recognize different music symbols—an issue considering the diversity of the Levy Collection and the universe of notated music, in general. Fourth, the software is open-sourced. Finally, this software can separate full-text lyrics that can be further processed using optical character recognition (OCR) technology. The AOMR process is divided into two major sections: symbol classification and musical semantic interpretation. The first step in the interpretation phase is to connect all inter-related symbols. In addition, many rhythmic errors can also be corrected by adjusting the metric placement of notes relative to their vertical alignment with notes in other parts. An interactive graphic editor suitable to be interfaced with the AOMR program is being developed jointly with the group working on the GUIDO editor (Renz 2000). The purpose of this editor is to correct any errors generated by the AOMR so that the corrected version then can be converted to GUIDO format. To enable powerful search and retrieval as well as user-friendly navigational mechanism, Phase Two of the Levy Project will include a strong metadata component. Commonly defined as “data about data,” metadata is structured representational information. The kinds of metadata important for Levy include descriptive (to enable searching, browsing and identification of items), structural (to enable the creation of an interface for optimum browsing and navigation), and administrative (to manage the digital components of the collection and aid users in identification of items). To further enhance the scholarly value of the Levy Collection, a web interface will be developed for a music research toolkit, for example, Humdrum (Huron 1997). These toolkits are software tools intended to assist in music research and are suitable for use in a wide variety of computer-based musical investigations, such as motivic, stylistic, and melodic analysis and concordance studies. We also propose to extend plans for developing automated means of mining authoritative name information and creating even richer name indexes. The entire Project is an experiment in developing a comprehensive framework of tools to manage the workflow of large-scale Digitization Projects. This framework will support the path from physical object and/or digitized material into a digital library repository, and offer effective tools for incorporating metadata and perusing the content of the resulting multimedia objects. The Levy Collection, with its large size and availability in digital format, is an ideal subject for development and evaluation of this proposed framework.
Megan A Winget - One of the best experts on this subject based on the ideXlab platform.
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the liner notes Digitization Project providing users with cultural historical and critical music information
International Symposium Conference on Music Information Retrieval, 2008Co-Authors: Megan A WingetAbstract:Digitizing cultural information is a complex endeavor. Not only do users expect to have access to primary information like digital music files; it is also becoming more important for digital systems to provide contextual information for the primary artifacts contained within. The Liner Notes Markup Language (LNML) was developed to provide an XML vocabulary for encoding complex contextual documents that include an album’s packaging, informational notes and inserts, liners, and album labels. This paper describes the development of the LNML framework, its major structural elements and functions, and some of the more pressing problems related to usability and purpose. The current LNML model is based on the examination and encoding of fifty albums from the 80s Rock genre. We are currently encoding fifty additional Jazz albums, which will provide data to augment and strengthen the model. Development of the LNML is ongoing, with plans to examine Classical and World Music examples to further augment the model. 1. DIGITIZING CONTEXTUAL INFORMATION
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digitizing providing access to contextual cultural materials the liner notes Digitization Project
ACM IEEE Joint Conference on Digital Libraries, 2007Co-Authors: Megan A WingetAbstract:This paper describes a Digitization Project focused on developing a metadata modeling schema for album liner notes.
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JCDL - Digitizing & providing access to contextual cultural materials: the liner notes Digitization Project
Proceedings of the 2007 conference on Digital libraries - JCDL '07, 2007Co-Authors: Megan A WingetAbstract:This paper describes a Digitization Project focused on developing a metadata modeling schema for album liner notes.
Ichiro Fujinaga - One of the best experts on this subject based on the ideXlab platform.
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optical music recognition system within a large scale Digitization Project
International Symposium Conference on Music Information Retrieval, 2000Co-Authors: Ichiro Fujinaga, Sayeed G Choudhury, Tim Dilauro, Michael Droettboom, Karl Macmillan, Brian HarringtonAbstract:An adaptive optical music recognition system is being developed as part of an experiment in creating a comprehensive framework of tools to manage the workflow of large-scale Digitization Projects. This framework will support the path from physical object and/or digitized material into a digital library repository, and offer effective tools for incorporating metadata and perusing the content of the resulting multimedia objects. The Project involves Digitization of the Lester S. Levy Collection of Sheet Music (Milton S. Eisenhower Library, Johns Hopkins University). In Phase One, images of the music and lyrics, and color images of the covers of the Levy Collection were digitized and a database of text index records was created. Phase Two consists of converting the digitized music to computer-readable music notation format along with full-text lyrics, generating sound renditions, and creating metadata to enhance search capabilities. During Phase One, the researchers at the Eisenhower Library created a database of text index records, images of the music and lyrics and color images of the cover sheets from the Levy Collection. This database is available to the general public at http://levysheetmusic.mse.jhu.edu. Currently, the Collection can be searched in three modes. First, users can search by subject, a keyword search on the text record. Each of the pieces has been indexed for the subject of the song and/or cover image. Users may also browse the Collection by the topical arrangement of the physical collection. In Phase Two, an adaptive optical music recognition (AOMR) software (Fujinaga 1997) is used to convert the TIFF image of scanned sheet music into computer readable-formats, which includes GUIDO and MIDI files along with full-text of the lyrics. These digital objects will be deposited into the data repository along with the scanned sheet music TIFF, JPEG and thumbnail, and associated metadata. The AOMR software offers five important advantages over similar commercial offerings. First, it can be run in batch processing mode, an essential feature for the Levy Collection given its large number of music sheets. It is important to note that most commercial software is intended for the casual user and does not scale for a large number of objects. Second, the software is written in C and therefore is portable across platforms. Third, the software can “learn” to recognize different music symbols—an issue considering the diversity of the Levy Collection and the universe of notated music, in general. Fourth, the software is open-sourced. Finally, this software can separate full-text lyrics that can be further processed using optical character recognition (OCR) technology. The AOMR process is divided into two major sections: symbol classification and musical semantic interpretation. The first step in the interpretation phase is to connect all inter-related symbols. In addition, many rhythmic errors can also be corrected by adjusting the metric placement of notes relative to their vertical alignment with notes in other parts. An interactive graphic editor suitable to be interfaced with the AOMR program is being developed jointly with the group working on the GUIDO editor (Renz 2000). The purpose of this editor is to correct any errors generated by the AOMR so that the corrected version then can be converted to GUIDO format. To enable powerful search and retrieval as well as user-friendly navigational mechanism, Phase Two of the Levy Project will include a strong metadata component. Commonly defined as “data about data,” metadata is structured representational information. The kinds of metadata important for Levy include descriptive (to enable searching, browsing and identification of items), structural (to enable the creation of an interface for optimum browsing and navigation), and administrative (to manage the digital components of the collection and aid users in identification of items). To further enhance the scholarly value of the Levy Collection, a web interface will be developed for a music research toolkit, for example, Humdrum (Huron 1997). These toolkits are software tools intended to assist in music research and are suitable for use in a wide variety of computer-based musical investigations, such as motivic, stylistic, and melodic analysis and concordance studies. We also propose to extend plans for developing automated means of mining authoritative name information and creating even richer name indexes. The entire Project is an experiment in developing a comprehensive framework of tools to manage the workflow of large-scale Digitization Projects. This framework will support the path from physical object and/or digitized material into a digital library repository, and offer effective tools for incorporating metadata and perusing the content of the resulting multimedia objects. The Levy Collection, with its large size and availability in digital format, is an ideal subject for development and evaluation of this proposed framework.
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ISMIR - Optical Music Recognition System within a Large-Scale Digitization Project
2000Co-Authors: Ichiro Fujinaga, Tim Dilauro, Michael Droettboom, Karl Macmillan, G. Sayeed Choudhury, Brian HarringtonAbstract:An adaptive optical music recognition system is being developed as part of an experiment in creating a comprehensive framework of tools to manage the workflow of large-scale Digitization Projects. This framework will support the path from physical object and/or digitized material into a digital library repository, and offer effective tools for incorporating metadata and perusing the content of the resulting multimedia objects. The Project involves Digitization of the Lester S. Levy Collection of Sheet Music (Milton S. Eisenhower Library, Johns Hopkins University). In Phase One, images of the music and lyrics, and color images of the covers of the Levy Collection were digitized and a database of text index records was created. Phase Two consists of converting the digitized music to computer-readable music notation format along with full-text lyrics, generating sound renditions, and creating metadata to enhance search capabilities. During Phase One, the researchers at the Eisenhower Library created a database of text index records, images of the music and lyrics and color images of the cover sheets from the Levy Collection. This database is available to the general public at http://levysheetmusic.mse.jhu.edu. Currently, the Collection can be searched in three modes. First, users can search by subject, a keyword search on the text record. Each of the pieces has been indexed for the subject of the song and/or cover image. Users may also browse the Collection by the topical arrangement of the physical collection. In Phase Two, an adaptive optical music recognition (AOMR) software (Fujinaga 1997) is used to convert the TIFF image of scanned sheet music into computer readable-formats, which includes GUIDO and MIDI files along with full-text of the lyrics. These digital objects will be deposited into the data repository along with the scanned sheet music TIFF, JPEG and thumbnail, and associated metadata. The AOMR software offers five important advantages over similar commercial offerings. First, it can be run in batch processing mode, an essential feature for the Levy Collection given its large number of music sheets. It is important to note that most commercial software is intended for the casual user and does not scale for a large number of objects. Second, the software is written in C and therefore is portable across platforms. Third, the software can “learn” to recognize different music symbols—an issue considering the diversity of the Levy Collection and the universe of notated music, in general. Fourth, the software is open-sourced. Finally, this software can separate full-text lyrics that can be further processed using optical character recognition (OCR) technology. The AOMR process is divided into two major sections: symbol classification and musical semantic interpretation. The first step in the interpretation phase is to connect all inter-related symbols. In addition, many rhythmic errors can also be corrected by adjusting the metric placement of notes relative to their vertical alignment with notes in other parts. An interactive graphic editor suitable to be interfaced with the AOMR program is being developed jointly with the group working on the GUIDO editor (Renz 2000). The purpose of this editor is to correct any errors generated by the AOMR so that the corrected version then can be converted to GUIDO format. To enable powerful search and retrieval as well as user-friendly navigational mechanism, Phase Two of the Levy Project will include a strong metadata component. Commonly defined as “data about data,” metadata is structured representational information. The kinds of metadata important for Levy include descriptive (to enable searching, browsing and identification of items), structural (to enable the creation of an interface for optimum browsing and navigation), and administrative (to manage the digital components of the collection and aid users in identification of items). To further enhance the scholarly value of the Levy Collection, a web interface will be developed for a music research toolkit, for example, Humdrum (Huron 1997). These toolkits are software tools intended to assist in music research and are suitable for use in a wide variety of computer-based musical investigations, such as motivic, stylistic, and melodic analysis and concordance studies. We also propose to extend plans for developing automated means of mining authoritative name information and creating even richer name indexes. The entire Project is an experiment in developing a comprehensive framework of tools to manage the workflow of large-scale Digitization Projects. This framework will support the path from physical object and/or digitized material into a digital library repository, and offer effective tools for incorporating metadata and perusing the content of the resulting multimedia objects. The Levy Collection, with its large size and availability in digital format, is an ideal subject for development and evaluation of this proposed framework.