Digital Humanities Abstracts

“METS: The Metadata Encoding Transmission Standard”
Merrilee Proffitt RLG Birgit Stehno MetaE Project Alexander Egger MetaE Project Thornton Staples University of Virginia

METS is a generalized metadata framework, developed to encode the structural metadata for objects within a digital library and related descriptive and administrative metadata. Those currently involved with or planning digitization will want to hear about METS, which can help to structure data for presentation and/or archiving. Expressed using the XML schema language of the World Wide Web Consortium, METS provides for the responsible management and transfer of digital library objects by bundling and storing appropriate metadata along with the digital objects. The use of a single, flexible means of encoding can simplify both the exchange of objects between repositories and the development of software tools for search and display of those objects. Additionally, METS encoding will provide a coherent means for archiving digital objects and their metadata. The METS initiative has two major components. On the technical side, the initiative seeks to provide a single, standard mechanism for encoding all forms of metadata for digital library objects. On the organizational side, the group looks towards developing mechanisms for maintenance and further development of the format, including establishing a METS testbed and METS tools. The first paper will provide a basic introduction to METS and will outline the objectives and progress and of the METS initiative to date. The second two papers will be reports from the field. Each project will give organizational background and context to their work, and will explain how METS may help the projects meet their objectives.

Introduction to METS

Merrilee Proffitt
METS is a generalized metadata framework, developed to encode the structural metadata for objects within a digital library and related descriptive and administrative metadata. METS provides for the responsible management and transfer of digital library objects by bundling and storing appropriate metadata along with the digital objects. METS is expressed using XML, which means that METS data is stored according to platform and software independent encoding standards, such as UTF-8 (Unicode), ISO-8859-1, etc. One important application of METS may be as an implementation of the Open Archival Information System (OAIS) reference model and as such can function as a Submission Information Package (SIP) for use as a transfer syntax; a Dissemination Information Package (DIP) for display or other applications; and an Archival Information Package (AIP) for storing and managing information internally.
METS had its beginnings as a project that identified metadata and architecture problems as an area of critical need for digital libraries. As more and more institutions created digital images and other files, there was growing concern about sensible storage for the digital objects (defined as digital files plus associated metadata). It was the beginning of a serious discussion, tying together many important aspects of digital library research. The Making of America 2 (MOA2) project sponsored by the Digital Library Federation (DLF) in the early stages and funded by the National Endowment for the Humanities was the project that resulted from these discussions. New York Public Library and the libraries of Cornell, Penn State, and Stanford collaborated under the leadership of the University of California, Berkeley Library, contributing images and data towards an investigation of structural and administrative metadata for digital objects. The MOA2 Document Type Definition (DTD), which was the direct predecessor of METS, was developed for the MOA2 project to encapsulate what were then seen as the required metadata elements. The MOA2 project was completed in early 2000, the Council on Library and Information Resources (CLIR) published the group's findings, and the MOA2 DTD was circulated for assessment and discussion. While MOA2 aroused considerable interest within the library community, the MOA2 DTD was too restrictive in some respects and lacked some basic functionality, especially for time-based media such as audio and video. A meeting was held in February 2001 for the various parties interested in advancing the MOA2 DTD to the next stage. Following this meeting, METS was born.
The METS Initiative: Technical Underpinnings
The technical component of the METS initiative has completed a draft schema for the encoding format and made it publicly available for review. The METS schema tries to support the dual and sometimes competing requirements of ensuring interoperability and exchange of documents between different institutions while also allowing for significant flexibility in local practice with regards to descriptive and administrative metadata standards. METS has a very simple structure with just four major components: descriptive metadata, administrative metadata, file inventory, and structural map. Only the file inventory and structural map are required.
  • The descriptive metadata is optional. A METS object can contain a Metadata Reference or a Metadata Wrapper. A Metadata Reference is a link to external descriptive metadata. A Metadata Wrapper is for descriptive metadata that is internal to the METS object, as either Base64 encoded binary data or XML. METS does not require a particular scheme for description, so the implementer can choose the most appropriate descriptive scheme.
  • The administrative metadata, also optional, has four optional subcomponents for technical metadata, rights metadata, source metadata, and preservation metadata. Each of these subsections act like the descriptive section in that the metadata can be encoded ("wrapped") within the METS document or pointed to in an external location ("referenced").
  • The file inventory allows for listing all the files associated with a digital object. Files can be grouped; some groupings might include master files, thumbnails, etc. The files may be pointed to or can be contained internally as Base64 encoded binary data.
  • The structural map forms a simple or complex tree structure that describes the digital object. The structural map permits the definition of a digital object that has either parallel or sequential modes and also allows for the coding of particular regions or zones of a file as part of the document.
The METS Initiative: Organizational
The standard is currently maintained in the Network Development and MARC Standards Office of the Library of Congress. Having played a key role in moving this initiative forward and serving as the work coordinator, the DLF has helped to bring the METS work to the forefront. RLG has recently taken over as the new coordinator. This is a natural step for a number of reasons. The METS standard will be applicable to RLG's member community of libraries, museums, archives, and historical societies. METS fits in nicely with much of RLG's ongoing work in digital preservation. Finally, RLG has always advocated community standards such as EAD and Z39.50, and METS is viewed as such a standard. For the next six to eight months, in partnership with the METS editorial board, RLG will continue the process of education, information dissemination, and gathering of feedback on METS. The process of review and evaluation based on use will continue during this time.


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unknown. MOA2 homepage:. : ,
unknown. DLF homepage:. : ,
unknown. RLG homepage:. : ,
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B. Hurley J. Price-Wilkin M. Proffitt H. Besser. The Making of America II Testbed Project: A Digital Library Service Model. : CLIR, 1999.


Birgit Stehno Alexander Egger
METAe is a research and development project co-funded by the European commission (5th Framework, IST Programme, area "Digital Heritage and Cultural Content") and aims at the development of an application software for digital archives and libraries. This software package, the METAe-engine, will automate the structural encoding of digitized material by introducing layout and document analysis as basic features. In analogy to OCR engines, where pure text is generated from image files, the METAe engine will extract layout and logical elements such as page numbers, pictures, captions, titles, subtitles, footnotes and document structures such as prefaces, chapters, subchapters, issues, contributions, etc. by analyzing the digitized pages of printed documents. The output of the METAe engine will be an 'archival information package' (OAIS) - ready for further processing and integration into digital library applications. This approach should guarantee that a huge amount of work which up to now has to be done manually will be done automatically. A central issue related to automated document understanding is the choice of the mark-up language. As the METAe project aims to produce a highly flexible output, existing guidelines and standards have been analyzed with regard to the needs of automated metadata capturing and encoding. The team decided to follow the METS working group.
Structural mark-up with automated layout analysis and document understanding
In contrast to text encoding performed by humans, automated capturing of structural metadata, i.e. the automated recognition of the physical and logical structure, requires not only a representation model (DTD), but also a recognition model which supports the automated identification of logical elements such as titles, chapters, footnotes, etc. (Cfr. Brugger, 1998; Dori et al., 2000, p. 424f.) As up to now artificial intelligence is not able to identify logical units by understanding their textual contents, recognition models have to represent rules and principles which allow the extraction of logical units on the basis of their component elements, of their physical (layout) characteristics and their syntactic relations. Having this information encoded in a model, the physical structure (physical blocks and sets of blocks) of a scanned image can be mapped onto the logical one. The model used in the METAe project has been generated by hand on the basis of a detailed analysis of monographs and journals and is represented by 'Augmented Transition Networks' (Woods, 1970), a formal grammar used normally within the field of natural language parsing. (Stehno/Retti). Since TEI is conceived as a "common encoding scheme for complex textual structures" meeting "the varied encoding requirements of any discipline or application" (Sperberg-McQueen/Burnard, 1999) our plan was to integrate the TEI encoding scheme in our recognition model as well as in the presentation model. However, this approach turned out to be problematic, since TEI - though it represents an advanced mark-up language - is not designed for automated document understanding and encoding. TEI offers just a very inexplicit set of rules for the hierarchical structuring of the elements. The METAe engine creates an extensive set of descriptive and administrative metadata on the document and its parts. A lot of different metadata standards (e.g. MARC, Dublin Core, or DIG35) will be used depending on the type of metadata and on the kind of element the metadata is linked to. TEI provides the possibility of adding metadata, mostly bibliographic metadata, in the TEI header as well as in the attributes of some of its elements. For the purpose of METAe the set of elements and attributes of TEI is not extensive enough. The METAe engine requires the possibility to add a set of descriptive and administrative metadata in any metadata format to any of the elements created by the engine. Moreover TEI never was designed to encode layout characteristics and physical structure of printed objects in a detailed and exhaustive way. By the help of the 'rend'-attributes, typographical information like <head rend='italics'> can be encoded in some cases, but the detailed description of pages, page spaces, text blocks and lines or strings is not possible. Within automated document analysis and understanding, all this physical information is available because it is needed for the identification of logical units. E.g., titles of different levels nearly always are expressed by different font styles and sizes, margin notes appear on the outer margin of pages, the font size of epigraphs is smaller than the default one, etc. Once disposing of this information, it should be encoded and thus conserved, in order to allow the recoverability of the original respectively an electronic representation which presents the source text with high fidelity. Considering these arguments, we decided to use the METS schema within the METAe project. The METS schema allows to encode the bibliographical, administrative and structural metadata separately providing the possibility to encode the physical as well as the logical structure within the 'structural maps'. By this way it is possible to describe the hierarchical layout of each page, i.e. the decomposition of a page into page spaces (print space and outer/inner/top/bottom margin), and physical blocks (text/image/composed blocks). In the METAe project this information is assembled in an XML file named "ALTO" ('Analysed layout and text object'). The physical and logical structures are encoded by linking and grouping layout elements out of the ALO file using 'div' tags of the structural maps. The physical structure is linked also to the image files of the pages. Each physical and logical element can be assigned an arbitrary set of metadata.
METAe: Organizational
The METAe project comprises 14 partners from Europe and the US among them universities, libraries, and software companies. The METAe engine will be a collaborative product with input from all partners. The software development is carried out by the German software company CCS and the University of Florence. The University of Innsbruck is responsible for the recognition model and the structural mark-up. A first prototype of the METAe engine will be available for demonstration purposes in spring 2002.


R. Brugger. “Eine statistische Methode zur Erkennung von Dokumentstrukturen.” University of Fribourg, 1998.
D. Dori D. Doermann C. Shin R. Haralick I. Phillips M. Buchman R. David. “The Representation of Document Structure: A Generic Object- Process Analysis.” Handbook of Character Recognition and Document Analysis. Ed. H. Bunke P. S. P. Wang. Singapore: World Scientific Publishing Company, 2000. 421-456.
Library of Congress, Network Development and MARC Standards Office. MARC21 Concise Format for Bibliographic Data. : , 2001.
unknown. METAe Project, University of Innsbruck:. : ,
unknown. METS. Official homepage at the Library of Congress:. : ,
The Association for Literary and Linguistic Computing (ALLC) Guidelines for Electronic Text Encoding and Interchange. TEI P3. Ed. C. M. Sperberg-McQueen Lou Burnard. Chicago, Oxford: Text Encoding Initiative, 1999.
B. Stehno G. Retti. “Modelling the logical structure of books and journals using augmented transition network grammars.” . : .
W. A. Woods. “Transition Network Grammars for Natural Language Analysis.” Communications of the ACM. 1970. 13: 591-606.


Thornton Staples
The University of Virginia Library has been building digital collections since 1992. We have amassed a large collection that includes a variety of SGML encoded etexts, digital still images, video and audio files, and social science and geographic data sets that are being served to the public from a collection of independent web sites that have very little cross-integration. We began searching in 1998 for a digital library management system that could effectively meet both our current and future digital content needs. Like many other libraries, we initially sought a vertical vendor solution that provided a complete, self-contained package for delivering and managing all digital content needs. Finding nothing available that would meet our needs, we decided to embark on an in-house development effort. Modularity and use of open-system standards is fundamental to our design strategy. Such modularity is essential for future evolution through component replacement. We are convinced that an object-oriented design is most appropriate, allowing us maximum flexibility, scalability and, eventually, interoperability with other repositories. We are also convinced that the Library should be providing tools to our users to give them sophisticated access to our collections and to help them manage their own collections. In the summer of 1999, early in our design process, we discovered a paper about the Flexible Extensible Digital Object Repository Architecture (FEDORA) written by Carl Lagoze and Sandra Payette at Cornell's Digital Library Research Group, describing the architecture that they had designed. FEDORA is a modular architecture built on the principle that interoperability and extensibility is best achieved by the clean separation of data, interfaces, and mechanisms (i.e., executable programs). A FEDORA Repository provides a general-purpose management layer for digital objects. In their simplest form, digital objects are containers that aggregate mime-typed streams of data (e.g., digital images, XML files, metadata), known as datastreams. It should be noted that datastreams can be references to external data - either disseminations of other FEDORA digital objects, or service requests to remote data sources. This capability allows FEDORA digital objects to serve as aggregators and value-added surrogates for existing on-line digital content. In addition to behaving in a generic manner, digital objects must be able to mirror real-world entities by providing access methods that make an object behave in a content-specific manner. For example, a natural behavior for a book would be "Get Table of Contents." FEDORA allows the association of rich and extensible behaviors with digital objects by "plugging in" generic components known as disseminators. Each disseminator aggregates references to: (1) a formally defined behavior interface that defines a set of methods for a particular kind of digital library resource (e.g. a Book interface), (2) an executable mechanism that runs these methods, and (3) the datastreams that the execution mechanism should use to fulfill specific method requests. These interfaces and mechanisms can, themselves, be stored as digital objects, laying the foundation for unlimited extensibility of the architecture. The Digital Library Research and Development group implemented the FEDORA architecture, using an SQL database and a single Java servlet. We implemented a variety of different testbeds, ultimately scale-testing a repository with 10,000,000 objects in it, simulating a very heavy user load, with excellent results. In September of 2001 we received a grant from the Andrew W. Mellon Foundation that will enable the University of Virginia Library, in collaboration with Cornell University, to build a sophisticated digital object repository system based on FEDORA that can be the basis for a variety of information management schemes. We will form two teams to carry out this project. First, a development team composed of people from Virginia and Cornell that will pursue a three-phase project with the goal of producing an open-source reference implementation, which will be available to other libraries and practitioners as they construct digital library systems. The first phase involves taking a strong proof of concept (already done) and producing a package that can be distributed and used in a variety of settings. The later phases will extend system by adding important functions that a sophisticated digital library system needs. The second team will deploy the software package at each of their own sites, using it to deliver testbeds of their own digital resources. That group includes: the Digital Library group at Indiana University; the Humanities Computing group at New York University; the Digital Collections and Archives Department at Tufts University; the Humanities Computing group at Kings College, London; the Refugee Studies Center at Oxford University; and the Motion Picture Broadcasting and Recorded Sound Division at the Library of Congress; and a library/academic computing team from Northwestern University. As the development team started to review the Virginia implementation, we discussed the possibility of building the objects as XML files, then using these files to build the necessary indexes in SQL databases. By doing this we are able to build the management interface against the XML, simplifying that effort, while separating the backend of the repository to make it easy to experiment with other indexing schemes. Ultimately, that should make it easy for us to experiment with a full-XML based repository, which we suspect will allow us to scale up to required levels. As we started to redesign the implementation, we looked at the Metadata Encoding and Transmission Standard (METS) schema to see if it would work for describing the objects. It turned out that most of what we needed to describe a FEDORA object was readily available in METS. The only thing really missing was a way to handle the disseminators that FEDORA uses to give the object behaviors. We made a proposal to the METS working group that resulted in a new top-level section being added for behavioral metadata that will be optional. That section can be used to associate an object with a behavior definition object and a corresponding behavior mechanism object. This presentation will discuss the use of METS to build a variety of different types of FEDORA objects, including the two types of behavior objects.