Executive Summary 1
Part I: Project Background 3
Those who are interested in reading about the MOA2 Project and its goals should read the Executive Summary, and Part I: Project Background.
Those who are interested in the technical details of the Model for Digital Library Objects should read Part II: The MoA II Digital Library Service Model. Those who wish just an overview of the concept of the Model should read An Overview of the Model and the Summary from Part II. Those who are interested in a discussion of the use of Tools within the Digital Library should read Part III: Implementing the Service Model for MoA II. For a brief overview of this subject, see The MoA II Testbed -- Services and Tools within Part III.
Discussions of metadata and recommendations for collection of such are primarily discussed in Part III. Readers who wish to learn about structual metadata (i.e. metadata that are relevant to presentation of the digital object in terms of navigation an d use) can consult the Structural Metadata section of Part III. Those who wish to follow the discussion of Administrative metadata (which we have defined as information used in the management of digital objects and collections) should see the Ad ministrative Metadata section of Part III. This paper does not contain a detailed discussion of descriptive metadata.
Imaging best practices are discussed in Part IV--Best Practices for Image Capture. An overview of this topic along with specific recommendations can be found at the end of Part IV in Summary of General Recommendations and Specific Min imum Recommendations for this Project.
The library community has a distinguished history of developing standards to enhance the discovery and sharing of print materials (e.g., MARC, Z39.50, ISO ILL protocols, etc.). This leadership role continues today through library participation in crea ting new best practices and standards that address digital collections and content issues (e.g., EAD, TEI, preservation imaging, etc.). In addition, libraries have worked actively within the broader Internet community to adopt other standards that are use d to store and access digital library materials (e.g., TIFF, HTTP, URNs, etc.). Perhaps the most important goal of this paper is to open a new dialogue in the ongoing conversation about digital library standards, specifically, to discuss the need for any new best practices and standards that are required if the digital library is to meet traditional collection, preservation, and access objectives.
The discussion this paper hopes to stimulate builds on work completed to date and asks the question, "How can we create digital library services that interoperate in an integrated manner across multiple, distributed repositories?" Clearly, t he standards and best practices mentioned above play an important role in answering this question. However, this paper and the MoA II Testbed Project in general focus on a new area of discussion that goes beyond the discovery of a digital object, and focu ses on how it is handled once it is found. That is, the paper and testbed focus on the need to develop standards for creating and encoding digital representations of archival objects (e.g., a digitized photograph, a digital representation of a book or dia ry, etc.). If tools are to be developed that can work with digitized archival objects across distributed repositories, these objects will require some form of standardization.
This paper aims to begin the discussion of digital object definitions by developing and examining metadata standards for digital representations of a variety of archival objects, whether they be in the form of text, digitized page images, photographs, etc. For our purposes there are three types of metadata: Descriptive, Structural, and Administrative. Descriptive metadata is used to discover the object. The project testbed proposes to use existing descriptive metadata standards (such as MARC records and the Dublin Core), as well as existing descriptive/structural metadata (like the EAD) to help the user locate a particular digital object. The paper proposes defining new standards for the Structural and Administrative metada ta that will be needed to view and manage digital objects. Structural metadata defines the object's internal organization and is needed for display and navigation of that object. Administrative metadata contains the management information ne eded to keep the object over time and identify artifacts that might have been introduced during its production and management (e.g., when was the object digitized, at what resolution, who can access it, etc.).
At a higher level, this paper proposes a Digital Library Service Model in which services are based on tools that work with the digital objects from distributed repositories. This borrows from the popular object oriented design model. It defines a digi tal object as encapsulating content, metadata and methods. Methods are program code segments that allow the object to perform services for tools, such as "get the next page of this digital diary." Unlike other models, methods are included as part of the object. This paper proceeds by identifying several archival digital object classes that will be examined as part of the MoA II project, including photographs, photo-albums, diaries, journals, letterpress books, ledgers and correspon dence. One of the first development efforts for the testbed will be to create the tools that display and navigate these MoA II objects, some of which have complex internal organization. Therefore, another goal of this paper is to identify the structural m etadata elements that are needed to support display and navigation, to ensure they are included as part of the digital objects. In addition, this paper begins to examine the methods (program code) that could be included with each class of object.
Because each partner library in the MoA II project will digitize images, the paper also investigates issues around best practices for digitization, in particular the capture of administrative metadata as part of this process.
After this paper has been reviewed by the wider community, the MoA II participants plan to incorporate reader feedback into the development of digital object definitions for the classes of materials to be examined in the MoA II Testbed. These definiti ons will specify how to encode the content, metadata and methods as part of the object. An important goal of the project is to use the testbed to investigate the advantages and limitations of these definitions and help stimulate a broader discussion of st andards for digital library objects and best practices for digitizing archival materials. This discussion must include the project participants, the DLF membership and the wider community. In addition, the project will contribute to the existing discussio n in the DLF Architecture Committee on distributed system architectures for digital libraries. The MoA II testbed will give the library and archival community a tool that can be used to test, evaluate and refine digital library object definitions and digi tization practices. It is expected that these discussions will move the archival community and the library community in general, closer to consensus on standards and best practices in these areas.
Specifically, the MoA II Testbed will provide a vehicle that will allow the DLF to investigate, refine and recommend metadata elements and encodings used to discover, display and navigate these digital archival objects. In addition, this pro ject will provide a guide to best practices for the digitization of archival materials. Overall, the DLF expects that the MoA II testbed will provide a working system in which metadata and digitization problems can be investigated, and where different sol utions can be discussed, tested, and refined. The project will provide the DLF membership with information that could be used to create standards or best practice recommendations for each research area, all of which are required for the creation of a nati onal digital library. In addition, the project will be of great value to the larger library community, in that it will advance the discussion of the nature of the digital library and move the community toward consensus as part of our ongoing discussion.
This project is broken down into three phases. The project planning phase has been funded by the DLF and is now underway. The NEH-funded production phase will commence in July. This is where we will be able to test the theories developed in the planni ng phase. Finally, at the completion of the production phase, the project will disseminate its tested ideas and practices to the broader community.
The MoA II Testbed Project Planning Phase The MoA II Testbed proposal, submitted to the NEH for funding in May 1998, included a planning phase to be funded by the DLF that covers the time directly proceeding NEH funding. UC Berkeley has now received funds from the DLF that will allo w the planning phase activities to proceed. The MoA II planning year proposal to the DLF can be found at http://sunsite.Berkeley.EDU/moa2/moaplan.html.
It is crucial that the methodology employed by the MoA II Testbed Project engage the wider community of scholars, archivists and librarians interested in access to the digital materials represented in this project. In addition, this process must also include metadata and technical experts at the proper time to ensure their contributions are utilized to maximum effect. Therefore, the following methodology is recommended. These activities include:
1) UC Berkeley, working directly with the other four NEH participants, consultants and selected archivists, will review the collections that have been proposed for conversion and identify the classes of digital archival objects to be represented in th e testbed. The classes could include formats such as correspondence, photographs, diaries, ledgers, etc. Note: The MoA II Steering Committee has recommended that books and serial articles be considered out of scope for this project.
2) UC Berkeley, working directly with the other four NEH participants, consultants and selected archivists, will draft a white-paper that identifies the behaviors each class of digital objects should be able to exhibit, as well as the structura l and administrative metadata to support these behaviors. In addition, the white paper will suggest initial best practices for digitizing the classes of archival objects to be included in this project. The white paper will include a compilation of existin g work in all the above areas, as well as any original contributions the group can provide.
3) The participants of the MoA II Testbed project and the DLF Architecture Committee will review the white paper. Upon revision from comments received, the paper will then be available for distribution as a basis for discussion in the wider community.
4) Technical experts on the Berkeley staff will analyze the white paper and design a means of encoding the behaviors, metadata, and objects for implementation during the Research and Production Phase of the project.
The MoA II Testbed Project Production Phase The MoA II testbed will be created in the NEH-funded year and will be used to investigate, refine and enhance the working definitions of administrative and structural metadata, the key behaviors of archival objects and best practice guidelin es for digitization. The goals of the testbed are to:
The MoA II Testbed Project Dissemination Phase Following completion of the Research and Production Phase, the MoA II project will seek funding for an invitational seminar to review project results. Participants will include representatives of a broad spectrum of fields and interest group s, including, for example, digital library experts, archivists and special collections librarians, scholars, computer scientists, museum technologists, and others who have participated in other phases of development of the EAD protocols, are engaged in si milar work, or who have appropriate expertise. The results of this phase will include widespread dissemination of the results of the project, refinement as necessary of the practices established, and formulation of an agenda for further community review a nd acceptance.
This paper also proposes a Digital Object Model that fits within the overall Service Model. The Object Model defines digital objects, which are the foundation of the Service Model, as an encapsulation of content, metadata and methods.
1) The Service Layer
This top layer describes the services that are to be provided for a specific audience of users. Given the MoA II project is focused on the use of archival materials by scholars, these services could include the discovery, display, n avigation and manipulation of digital surrogates made from these collections. The specific service model used in this project follows the standard archival model. That is, materials can be discovered via USMARC collection level records in a catalog; the c atalog records can link the user to the related finding aid that describes the collection in more detail and; the finding aids can link to individual digitized archival materials.
The service layer is actually comprised of a suite of tools that is created to support the needs of a particular audience. For example, scholars would be comfortable using sophisticated electronic finding aids to locate and view digital archival materials such as photographs or diaries. However, fifth-graders, with less rigorous information needs, may require simpler tools to discover and view these items.
2) The Tools Layer
This layer contains the tools that act at the request of the user. For example, a tool may be created to display and navigate a diary. The MoA II tools will consist of:
3) The Digital Object Layer
This layer contains the actual digital objects that populate distributed network repositories. Objects of the same class share encoding standards that encapsulate (i.e., includes) their content, metadata and methods - a full explanation of t his concept follows in the next section. Separate digital object classes could be defined for books, continuous tone photographs, diaries, etc.
A Model for Digital Library Objects Digital library objects form the foundation layer of the Digital Library Service Model, as described in the previous section. We can now create a Digital Object Model for these objects that will fit within the overall Service Model.
Adding Classes and Content to the MoA II Object Model The MoA II object model defines classes of digital archival objects (e.g., diaries, journals, photographs, correspondence, etc.). As expected, each object in a given class has content that is a digital representation of a parti cular item. The format of the content can be digitized page images, ASCII text, numeric datasets, etc. The following examples describe three classes of archival objects, along with their content format.
1) Descriptive Metadata is used in the discovery and identification of an object. Examples include MARC and Dublin Core records.
2) Structural Metadata is used to display and navigate a particular object for a user and includes the information on the internal organization of that object [
3) Administrative Metadata represents the management information for this object: the date it was created, its content file format (JPEG, JTIP, etc.), rights information, etc.
Adding Methods to the MoA II Object Model Methods are a concept defined within the object oriented analysis and design paradigm. Therefore, it would be useful to begin by reviewing concepts to be used in this paper that originate from object oriented design.
Object Oriented Design (OOD) as Part of the Object Model
Object oriented design has become very popular, as can be seen by the widespread use of related programming languages like C++ and Java. Some of the reasons for this popularity also make OOD an attractive addition to the Digital Library Service Model. In particular, object oriented design actually models users' behaviors, making it easier to more accurately translate their needs into system applications. This advantage will be discussed in more detail in the following section.
There is another important advantage for considering OOD. In object oriented design, a digital object conceptually encapsulates both content and methods. An object has content, as expected, but it also contains segments of program code c alled methods. These methods are part of the object and can be used by developers to interact with the content. For example, a developer can ask a digital book object named Book1 for page 25 by executing that object's get_page() metho d and specifying page 25. This method call may look something like Book1.get_page(25).
There are a number of advantages in making methods part of the object, but probably the most important is that these basic program segments do not have to be re-invented by every developer creating a new tool. [
Defining the Difference between Behaviors and Methods
One great advantage of the object oriented design approach is that it models users' behavior with methods. Therefore, this paper will now introduce a clear distinction between user level behaviors and methods. Simply put, behavior s are how users describe what tools can do for them. For example, zoom in on this area of a photograph, show me this diary, display the next page of this book, or translate this page to French. Methods are how system designers describe what tools can do f or a user.
One important purpose for distinguishing differences between user level behaviors and methods is to put in place a process where the library community can engage their users in a dialogue on what services and tools they require, down to the behaviors they need in each tool. Software engineers can then map the user behaviors into sets of methods that are required to perform the necessary functions. The line between behaviors and methods represents the transition from user requirements to system design.
The following are example user level behaviors that might be relevant to a digital library object class of type diary.
Methods as part of the MoA II Digital Object Model
We can now add methods to the Object Model. At this point, it is important to note the close relationship between methods and metadata. In most cases, the methods require that appropriate metadata to be present if they are to perform their func
Summary This paper proposed a Digital Library Service Model for the MoA II project in which services are based on tools that work with the digital objects from distributed repositories. This model recommends that l ibraries first define the services they need to provide for each audience they support, then define the tools that are needed to implement these services. This process should include the identification of the tools' user level behaviors (i.e., what the tools do as required by the users).
This paper also proposes a Digital Object Model that fits within the overall Service Model. The Object Model describes digital objects, the foundation of the Service Model, as an encapsulation of content, metadata and me thods. Different classes of objects exist (e.g., diary, photograph, etc.) and the content of each object can be text, digitized page images, photographs, etc. The object also contains metadata that is divided into three types: Descriptive metadata used to discover the object; Structural metadata that defines the object's internal organization and is needed for display and navigation of that object; and Administrative metadata that contains management information (e.g., the date th e object digitized, at what resolution, who can access it, etc.). Finally the digital object definition borrows from the popular object oriented design model and includes methods as part of the object. Methods are program code segments that allow t he object to perform services for tools, such as "get the next page of this digital diary."
Continuous tone photographs: Single archival object. May have caption or other textual information recorded on its face or on verso. Continuous tone photographs are interesting for this project for a number of reasons: they exist in quant ity in many of our collections; and they will give us an opportunity to look closely as the collection of administrative metadata for use in object behaviors. The most basic of objects, the continuous tone photograph will help us to build a solid platform upon which we can base the rest of our work.
Photo albums: Bound manuscript object, containing a collection of continuous tone photographs. The photo album may contain captions, which are separate from the photographs or other items, such as newspaper clippings, etc. Photo albums ar e in a way a logical extension of continuous tone photographs, since they contain photos ordered in a structured manner, allowing us to look at structural metadata issues, in addition to administrative metadata.
Diaries, journals, and letterpress books: Bound manuscript objects, usually arranged chronologically and with date notations. May have additional structure, such as an accounts section noted in the back. Again, these are structured docume nts, with the further possibility of additional metadata in the form of partial text (dates and other markers) included for additional navigation. With the inclusion of full texts, such as the William Henry Jackson diaries at NYPL, full searching and navi gation is possible.
Ledgers: Bound manuscript objects that contain accounting records, usually arranged by account, although sometimes they are also in simple chronological order. Clearly, documents of this sort have a different structure than diaries and jo urnals, but (from the structural/navigation standpoint) are they really a different object type, or a variation on a theme? Again, inclusion of more text, while more costly, allows for more sophisticated searching and navigation.
Correspondence: Objects of this class may be simple (a single page letter) or complex (a letter with an envelope and enclosures and/or attachments). Investigating correspondence will allow the project to examine these sometimes complicate d documents and the structural metadata relationships between the sub-documents (letter to envelope, for example).
The classes of material listed above have been selected for the testbed either because large quantities are held by participating institutions, and/or because they offer the MoA II Project important challenges in terms of the behaviors needed to view, navigate, or manipulate them. The complex structure of photo albums challenges us to offer the viewer the ability to see individual photographs, to see a photograph with its caption, and to see photos and captions within the context of pages and pages wi thin the context of an entire album.
The complex structure of diaries and journals allows us to explore presentation to the user of individual entries and let them jump from one entry to another (or from an index to an entry). It also lets us explore issues raised when individual page sc ans have no correspondence whatsoever with the logical structure of the document (i.e. journal and diary entries frequently end in the middle of a physical page and a new entry begins on that same page). In addition, these materials allow for display and navigation experiments when different levels of metadata are available. For example, a "minimal" digital diary might be comprised of a series of page images, in which case, only a base set of behaviors that can be implemented (e.g., turn to the next page, previous page). However, a richer diary may have encoded text transcribed for each page image that allowed for tool behaviors that can; display a table of contents for the diary; jump to a particular page or dated entry; search for text strings or "more entries like this one;" etc.
The structure of letterpress books and ledgers lets us examine the interaction between indices that exist within a document and the various individual entries/parts in that document. The project will also explore how the structure of these items diffe rs from those of diaries and journals. While ledgers, letterpress books, journals and diaries clearly are different classes of items from an archivist's point of view, they may be more similar than not from a structural metadata perspective.
In addition, the MoA II testbed will give the participants and the wider community a chance to evaluate different practices for encoding the relationships between objects. In particular, it will help the community understand the advantages and drawbac ks of using these practices based on how tools are able to implement different behaviors for each practice. For example, a series of correspondence could be scanned and:
a) placed into a single "base object";
b) created as separate objects, one for each letter, and then all linked together through the creation of a new "aggregate collection (folder?) object";
c) created as separate objects inside a "embedded collection (folder?) object." A collection object has metadata for the collection, followed by the embedded objects, each with their own metadata and content. This differs from b) in that th e objects are embedded, as opposed to linked;
d) organized through a finding aid in which the container list points to any of the above.
Each base object, whether it stands by itself or is part of an aggregation or embedded collections object, can have "divisions." That is, it can be divided into sections through the use of text encoding. For example, a diary can have dated entries that are identified by the text encoding which can then be used for display and navigation. In the same manner, any type of object can also be a "compound object" by linking to other objects, or embedding them inside itself. While the co ncepts of compound, linked or embedded objects is not new, the MoA II testbed will give the archival and library community a tool to better evaluate all the above options for digital archival objects, particularly in the context of distributed repositorie s.
The MoA II testbed will give the DLF and the wider community an opportunity to create objects using all the practices listed above. As important, it will allow for the evaluation of each practice, as they can be better understood based on how tools ca n use each practice to meet the needs of their intended audience.
The MoA II Testbed -- Services and Tools The Digital Library Service Model described earlier in this paper proposed a three-tier model, with services, tools and digital objects comprising the layers from top to bottom. The MoA II testbed will implement the standard archival model w ithin the Digital Library Service Model. That is, USMARC collection level records in a catalog will link to their related finding aids, which in turn will link to the digital archival objects in that collection.
The top tier in the model represents a service layer that is comprised of suites of tools that focus on supporting particular audiences. (e.g., scholars, university undergraduates, K-12 students, etc.). For example, archivists may require diffe rent tools for the discovery, display, navigation and manipulation of digital archival objects than would K-12 students. The MoA II Testbed project will initially focus on general services for scholars in using the classes of digital objects selected for this project. Future research projects that could be considered may include developing service models for more novice users (e.g., K-12) or more customized services for specialized scholarship (e.g., service for medieval manuscript scholars, as envisioned by the Digital Scriptorium Project).
The suite of tools to be developed in the MoA II testbed will initially include:
The goals of the testbed are to: create tools that help the community understand how digital archival objects are discovered, displayed and navigated; understand how metadata is used by these tools and to come to a better understanding of what value t he metadata provides, and at what cost; and to provide the DLF a set of metadata practices that can be reviewed and recommended to the wider community.
Behaviors and Methods--"What Tools Do" Definition The Digital Library Service Model presented earlier defines behaviors as the way that "users describe what tools do for them." Engaging users in a dialog about behaviors is a methodology that can be used to understand user n eeds as defined by the functionality of the tools. These user-level behaviors are then mapped by system designers into methods--discrete segments of program code that execute operations for tools. The translation from behaviors to methods represent s the transition from defining user needs to system design. In many cases, high level methods in a tool will have the same name as a user level behavior. Creating methods that model a user's desired behaviors is, in fact, one of the strengths of object-or iented design.
When we speak about "methods," we speak about the operations that tools let us perform on digital objects. We will use this notion of methods to specify the range of activities that should be supported through the metadata described elsewher e in this white paper. In an object-oriented model, the methods are embedded in the digital objects; digital objects reveal methods to tools interacting with them. We acknowledge that many repositories in the MoA II environment will not deploy object-orie nted models. Instead, the methods will be made available to tools that interact with repositories rather than the individual digital objects themselves. Nevertheless, we believe that this model is helpful both in conceptualizing the nature of the t asks supported and in preparing for a type of digital library that may scale more effectively than current architectures.
Methods supported in the digital library should be both those common and exceptional operations users expect to perform with the digital objects. For an image collection, a method might be facilitating a "pan" or "zoom" on a portio n of an image, or providing an enlargement of an image. For an encoded diary, the digital object's method might involve providing the tool information about levels and types of organization (e.g., one volume, including 128 dated entries, an itinerary, and a list of contacts with addresses). The encoded diary's methods might also yield both simple ("next entry," "previous entry") and more complex navigation (e.g., locate the first dated entry in November 1884; find entries where dates a re separated by more than ten days). While no object or repository would be required to support the full range of methods--a practical impossibility--the model proposed here will facilitate the development of increasingly sophisticated tools that c an scale for use on a growing body of complex archival objects.
Contexts and Constraints The methods of the digital library reside in tools that are sometimes client-based and sometimes server-based, depending on the state of our technology and that of our users. The location of that method (i.e., on client or server) may shift with changes in those circumstances. For example, widespread adoption of an image client that supports progressive transmission of image data might shift image processing from server to client, expediting image processing and reducing load on the s erver. However, an interim measure might rely on a server-based compression/decompression process where the server can generate "pan" or "zoom" views at the user's request in real time, thus relieving the client of processing responsib ility and shifting the work to the server.
Just as the methods we discuss may move from client to server and back again, so too will they separate into specialized functions or merge into high level, multi-faceted functions. For example, we might postulate that "print" and "disp lay" are different methods, with one object optimized for screen display, and another object optimized for a printer. While being careful to make clear that the authors of this document are not endorsing Acrobat as a tool or, especially, PDF a s a storage format, we can see that Acrobat demonstrates a model where "display" and "print" are merged in the same tool. If we argue that Acrobat handles "display" poorly, we might push for a clearer separation of these two methods. By separating the methods conceptually, we are able to assess the applicability of the tool in the service of the method.
High level methods are frequently comprised of a series of calls to lower level methods. For example, because "print" is a behavior most users require in a tool, most tools will have a high level method expressed something like "print(a 1,a2 aN)." In the example, the information inside the parentheses represents arguments that tell the method what object to print, which printer to use, etc. The "print" method would actually execute a series of lower level methods. It may, for example, first ask an object to deliver its content in a format suitable for printing by executing the proper method. Next, it may execute an operating system specific method that sends (i.e., spools) the formatted content to that particular printer.
Finally, some methods are applicable to all or most objects, while others may need to be finely tailored to the type of object--so finely tailored, in fact, that they rely on entirely different functions or primitives. An obvious example is the differ
ence between navigation of pages and navigation of portions of an image. A system that navigates a bound book might use operations such as "display next page" or "show page list"; a system that navigates a continuous tone image might u
se operations such as "display 200x200 pixels centered on coordinates X by Y". The following sections attempt to define methods that we believe are central to creating the digital library. Wherever possible, we will attempt to describe methods i
n ways that are sufficiently generic to be applicable to a wide variety of objects; in some cases, we will describe methods specific to some data types. [
Navigation General Navigation
We can think of navigation as a process stream consisting of a request, a receive, and a display action, where each action interacts with a reference to objects or metadata for objects rather than to the objec ts themselves. A significant portion of the user's activity is what we would think of as navigation. For example, the user who finds a digital scrapbook in a repository will request what we would call a "table of contents." Depending on the exte nt to which the book was processed, that table of contents may consist only of a stream of page references, or it may consist of a nested list of chapter and section headings. In navigating through the scrapbook, the user's navigation tool will:
1) request references (to pages listed by page number or to sections listed by section headings);
2) receive the references in a discernable format; and
3) display that information in a meaningful way for me as the user of the tool.
Importantly, the user expects a series of references, and not actual delivery of the objects (i.e., the actual pages or sections will not be sent until requested).
Navigation also depends on an understanding of relationship primitives. These relationship primitives, parent, child, and sibling, are the generic references a tool uses to facilitate navigation. The navigation method is af fected by the tool requesting, receiving, and displaying the parents, children, or siblings of an object that the user has located. For example, to navigate a fully encoded and logically organized scrapbook, a navigation tool might request references to t he first level children in the scrapbook. A user would be presented with a list that looked like the following:
In contrast to the more generic form of navigation discussed above, image navigation uses image-specific information to accomplish its ends. Systems that display image information need information analogous to geographic references--X an d Y coordinates along with dimensions of the portion of the image to be displayed. Increasingly, tools for image management and manipulation use notions of segmentation to optimize the relatively confined space of a video display, as well as other resourc es in short supply (e.g., network capacity, memory, and CPU capacity). As mentioned earlier, some of these technologies are primarily server-based, while others shift responsibility to the client. Wavelet compression, for example, allows a repository to s tore a form of the image rich in information (e.g., extremely high resolution), and to generate lower resolution versions and subsets in real time, at the request of the user or an intermediary. Another approach implicit in the tool/format called JTIP seg ments the image into overlapping tiles in a pyramidal structure, allowing the user to pan and zoom on a full resolution image by requesting the next tile, or a corresponding tile at a higher resolution. In both of these cases, the image navigation tool receives information about resolutions, resolution ratios, and window sizes to make the navigation possible; the image display tool (discussed below) uses that information to pan, zoom, crop, and otherwise use images.
Display and Print The display method uses a reference to a known object to effect delivery of an item to a screen-oriented tool (e.g., a graphical web browser). By contrast to navigation where the user tool requests object references, the display tool will work from an object identifier it has received from an intermediary or that it can infer from a query where only one object exists. From this relatively simple operation, we quickly encounter more complex issues.
One of the most complex issues for display is the variety of known item references that an intermediary must handle. At its simplest, a display tool will encounter references to page images in a format clearly identified by structural metadata. Similarly, the tool may receive a reference to an encoded text section (e.g., a chapter), again in a format identified by structural metadata. Slightly more complex references include requests such as that to display the next or previous siblin g of a digital object (e.g., next page or previous chapter), or the parent of a digital object (e.g., the chapter that includes this page). For images, an intermediary may request the display of a known item at a specific resolution. More chall enging will be the standard articulation of a reference to display a portion (e.g., 250x250 pixels, centered on pixel X.Y) of an image at a specific resolution. Panning, zooming, and cropping of an image are variations on this type of request.
Printing is, we believe, a method similar to the display method, differing only in its use of output devices (i.e., printers, plotters, disks, etc.) Indeed, the option to print may use the same format as the option to display, as is the case with systems relying primarily on encapsulating images in PDF for delivery. The display and print methods are closely intertwined, and differ based on the formats available from the repository and user preferences. For example, i magine a repository of bitonal, 600dpi page images offers GIF images with interpolated gray-scale, Postscript, and PDF. A user without Acrobat may choose to display the GIF images but print using the Postscript files containing encapsulated images, while another user with Acrobat may choose to rely entirely on the PDF image files so that she might print and display from the same source.
Combination or Comparison As the body of materials in the digital library grows, the ability to create combinations of data or perform comparisons becomes increasingly important. "Combining" and "comparing" methods are applicable to both images an d text. Most common with art and architectural images (cf. the common use of two slide projectors in art historical instruction), we also frequently see the need to be able to support the comparison of two passages of text, or the display of a text alongs ide an image. Common applications of this method we might expect to see include:
More than most other methods, those for repository search currently tend to be methods exhibited by server-side programs rather than client-side tools. We can easily imagine at least portions of these methods migrating to the user's desktop, inherent in tools for managing and interpreting results, but considerable standardization will first need to take place. In repository search, an intermediary will collect information about the user's query, the characteristics of the available collections, and wi ll begin to process results (e.g., in a sorted list by object or by collection). This intermediary has clearly distinct discovery and retrieval functions, so these will be treated separately below.
In order to support discovery within or among repositories, each collection must participate in a conversation with the client or intermediary; this conversation constitutes the method we associate with discovery. Among the charac teristics of a repository's discovery method will necessarily be a means to understand the search parameters of the repository, including gathering information on searchable fields, the sorts of operators that can be applied, and other constraints. Of course these mechanisms have been specified in protocols such as Z39.50, but it is important to explore "lighter weight" and more flexible mechanisms such as the SIL specified by Nigel Kerr's "Personal Collections and Cros s-Collection Technical White Paper" (http://dns.hti.umich.edu/~nigelk/work/pccc.html).
In order to support the retrieval of results within and among repositories, the conversation identified above must also include a well-specified retrieval method. Results must come from the repository or repositories in a well-articulated and e asily parsed syntax. The tool will use this syntax, for example, to build result lists, to bring together results from multiple repositories, and to compile results from multiple repositories. An example of a proposed specification for such a retrieval me thod can also be found in Nigel Kerr's "Personal Collections and Cross-Collection Technical White Paper" (http://dns.hti.umich.edu/~nigelk/work/pccc.html).
Color Analysis An admittedly challenging set of methods will come with richer and more reliable color metadata. The availability of a Color Look Up Table (CLUT), providing color, shape, and texture distribution that can be processed through automatic means , will aid in a variety of tasks. For example, a color-matching behavior might take CLUT information from manuscript fragments, locating fragments by color or texture that are more likely to be from the same paper stock. CLUT information can also b e used to measure subtle variations in information such as shape and patterns, and thus hidden features such as characters obscured by palimpsest erasures. Methods using the CLUT will support these types of analysis.
Bookmarks, Annotation, and Links
As the digital library grows in maturity and capability, the array of interactions with objects will grow more complex. Intra-object bookmarks, annotations, and more sophisticated linking methods are all parts of methods that our users desir
e; none of these methods is outside the capabilities of readily available desktop technology today. Nevertheless, our ability to support these methods is hampered by unreliable or incomplete metadata, by the absence of generalized notions of user authenti
cation and authorization, and by a lack of support by repositories. Importantly, though, we lack tools to exploit methods in these areas. Many of these methods are explored in great detail in the research applications developed by Robert Wilensky a
nd his team as they pursue notions of "multivalent documents." [
MoA II Metadata Metadata can be in a header, a MARC record, a database, an SGML file, or distributed amongst a variety of locations. An object or repository only needs to be able to reconstitute the metadata and present it to a user or application when requ ested (discovery, navigation, and administrative functions).
1) Descriptive Metadata The library community has a long history of developing standards and best practices for descriptive metadata (e.g., MARC, Dublin Core, etc.). Given existing standards and ongoing work within the community to investigate descriptive metadata issues, the MoA II proposal did not focus on this area. Instead, the proposal to the NEH recommended a MoA II testbed that used a union catalog, with MARC records contributed by the participants. The participants will also contribute finding aids encoded to the EAD community standard.
Therefore, the discovery process will consist of users searching the MoA II union catalog of MARC collection level records that will be linked to their corresponding finding aids, and the finding aids will then be linked to the appropriate archival di gital library object (e.g., photograph, diary, etc.). Of course, it will also be possible to search the finding aids directly to discover archival library objects.
2) Structural Metadata The authors of this white paper offer the following definition of our use of the term "structural metadata":
Structural metadata are those metadata that are relevant to presentation of the digital object to the user, describing them in terms of:
1) Navigation, e.g., navigating internal organization and exploring the relationship of a sub-object to other sub-objects (see Tables of structural metadata features for a definition of sub-objects); and
2) Use, e.g., the format or formats of the objects available for use, rather than those formats stored.
The terminology of the digital library is evolving rapidly. In fact, as can be seen in Appendix Iquite readily, even avoiding domains where the term is used much differently (e.g., georeferenced data), quotes on the subject show considerable variation in the way that our community uses the term structural metadata. Current thinking divides digital library metadata into either three categories (descriptive, administrative, and structural metadata) or into two categories (descriptive and structur al metadata, with structural metadata subsuming both administrative and structural metadata). The approach taken here is to separate administrative and structural metadata, which in turn influences the way we refer to structural metadata. A technical term , like any word, is ultimately defined by the way we use the term. Nevertheless, of most importance here is not that we see structural metadata as separate from administrative metadata, but rather that we propose the following categories for inclus ion in the MoA II architecture.
It is important to note that even though the categories defined here are presented in SGML, the data in a repository will not necessarily be stored in an encoded form (such as SGML) or in a table. This document does not advocate particul ar methods for storing data; the authors believe that various approaches will be necessary at the different institutions, and that different approaches may even exist within the same institution. For example, a single institution may store descriptive met adata in USMARC, portions of structural and administrative data in relational tables, and other portions in SGML. The examples provided here are intended only to illustrate the type of data presented in interactions between repositories and intermediaries . We assume that the metadata documented here will be extracted from a metadata management system (or systems) in interactions with intermediaries such as tools. Further, default and inherited values will be expressed explicitly at the level of the sub-object, even if implicitly associated with the sub-object through the metadata management system.
Structural Metadata Elements and Features Tables
These tables attempt to be comprehensive and are recommendations for the full set of possible structural metadata elements that we think an individual collection may possibly find useful. Some repositories will only use the minimum set of requi red elements. Other repositories will also use elements that can be derived in an automated fashion. Still others will choose to use elements that are easy to derive. The table: includes both minimal and maximal values; identifies required and repeatable fields; and identifies which field values may be inherited or supplied manually. Some elements can fulfill both administrative and structural functions.
Some elements are more relevant to "raw" data (such as page scans) that has not required much intellectual examination of the data structure. Other elements are more relevant to "seared" data (such as chapter divisions and headings
) that involves only minimal examination of data structure to generate appropriate metadata. Still other elements are primarily relevant to "cooked" data (such as SGML marked-up text) that has a very involved intellectual examination of its stru
The table presented here is divided into two primary categories: structural metadata defining the "object," and structural metadata defining the digital sub-objects themselves (e.g., the individual digital pages). In making this distinction, we divide the structural information for a digital object into that which refers to the constituent objects that cohere into a whole (e.g., a description of the extent of a digital book), and that which is specific to the individual parts (e.g., page or image references). The model presented here owes a great deal to the "Structural Metadata Dictionary for LC Repository Digital Objects," both for its organization and for many of the elements themselves.
In making the distinction between object and sub-object metadata, we acknowledge that the distinction is in some ways artificial. For example, a tool might assemble information relating to the constituent parts of a photo album by querying each of the constituent sub-objects rather than querying a specially designed digital object. We believe, however, that certain economies prevail when storing information such as ownership (i.e., of the digital object) only once in the object rather than with each s ub-object, and this model strives to balance the specification of elements accordingly.
|Unique identifier reference||A unique identifier must be presented with each digital resource. In order to ensure the effective coordination of metadata, structural metadata must contain a unique identifier reference (referring to the object's unique identifier). This unique identifi er is intended to be a precursor (and functional equivalent) to an URN.||
Describes the types of content available (i.e., not necessarily formats captured) for this digital object. It consists of paired attributes containing (1) a generic and controlled descriptor of the type of material (e.g., text, page image, continuous tone
image, audio, etc.), and (2) the format available for each. Objects will be available in a number of formats. For example:
Page: TIFF, GIF, JPEG, PDF
Image: JFIF, JTIP, etc.
Text: HTML, XML
Computationally, a tool or service should be able to do something like say "there are 324 images available in four different formats, thus we can build a table of views that's four wide and 324 high." It may not appear as a table< /I>, per se, but as options available for selection by a user.
Extent is in many ways analogous to the extent statement in a MARC record, and for structural data provides information specific to the number and levels of component types. In the simplest terms, this element facilitates the sort of dialogue between obje
ct and intermediary that runs as follows:
|Data file size||The file size of an object sent to an intermediary such as a client or tool. It is distinct from the file size of the object stored or captured, which is administrative data.||No||No||
|Structural Division(s) (DIVn)||
A digital object may be logically divided into parts (e.g., letters in a diary). If resources are made available to support some level of encoding, structural divisions are encoded with the TEI element DIVn (e.g., <DIV1>). Should an ob
ject be encoded for logical features, encoders may wish to exploit other TEI elements (not documented here). The fully encoded document may be offered as a version of the digital object. Many of the attributes of the Digital Object, described below, will
be applicable to the Structural Division(s).
|Yes||Manually supplied in encoding|
|Relationships provide information on sub-object relationships. A diary entry in a diary section (e.g., a year) would have as its parent the section, and would have as siblings the previous and next diary entries. If, for example, it was an unusually long diary entry with sections of its own, its "children" would be the sections within the entry.||No||Yes||Automatically generated|
|Sub-object Type||This category constitutes use information and is intended primarily for pages and includes values such as "TOC1" (i.e., first table of contents page).||No||No||Manually supplied in data capture|
|Sub-object value||This value carries the page number for objects that are pages. Unnumbered pages may not have an N value, or the N value may be supplied through inference.||No||No||Manually supplied in data capture|
|Sub-object sequence||Pages require a sequence indicator (e.g., this is the third page in the sequence of pages contained in this book). Carries a numeric value only and must be specified.||Yes||No||Manually supplied in data capture|
|Sub-object Format||Images of all types (e.g., page images and continuous tone images) require format information. The contents of the Sub-object Format element are coordinated with the Content Type element (see above). While Content Type declares the available formats for a particular "type" of information (e.g., encoded text), the Sub-object Format element refers to these declarations to inform the intermediary of the available formats for the object at hand. For example, a page image may be said to be available as a GIF image, a PDF file, and a TIFF G4 image.||Yes||No||Inherited from Object header|
|Sub-object dimensions||Dimension information such as the resolution offered by the object (i.e., not the captured resolution) may be provided. This element documents the forms of the image object that can be requested from the repository (i.e., in order to assist an intermediar y in navigation, manipulation, etc.). For images of all types (i.e., bitonal and continuous tone), this is resolution and pixel dimensions. The element is not applicable for text. To imagine the relationship between administrative and structural metadata in this regard, we can imagine a repository declaring to a tool: "This image is stored in 1200dpi 24bit color, which is administrative data; it is available to you as 72dpi with a 256 color adaptive palette, which is structural metadata."||No||No||Inherited from Object header|
|Sub-object size||This element offers two values, "Reference" and "Full", and is used to describe generic instances of an image. It is important to note that we favor a perspective that sees all available versions of an image on a continuum going from t he lowest usable resolution to a full resolution. However, we acknowledge (1) the "lowest usable resolution" is a moving target and that (2) an arbitrarily specified "reference" version is a useful concept. We would like to prop ose that the "Reference" version is 500 pixels high (or less, if the original captured was fewer than 500 pixels high). The only other option here is "Full", which is a 1:1 display of resolution captured.||No||No||Inherited from Object header|
|Sub-object reference||This attribute carries information needed to locate the sub-object. Where possible, it should be an URN. Alternatively, it must be based on the URN for the object of which the sub-object is a part.||Yes||No||Manually supplied in data capture or automatically generated|
3) Administrative Metadata Administrative metadata consists of the information that allows the repository to manage its digital collection. This includes:
Administrative metadata is critical for long-term file management. Without well-designed administrative metadata, image file contents may be as unrecognizable and unreadable a decade from now as Wordstar or VisiCalc files are today. Administrative met adata should help future administrators determine the type of file it is, when it was created, what particular original it was created from, what methods or personnel might have introduced artifacts into the image, and where the different parts of this (o r related) digital object reside. Eventually, we hope that administrative metadata may help objects care for their own long-term management.
In the past, certain administrative metadata (such as file formats) resided in file headers, while others resided in accompanying databases. At some point in the future, all administrative metadata may reside within the file header, but that would be ineffective until community standards develop on where they would go within the header, how to express them, etc. In this paper we define the administrative metadata fields necessary irrespective of a particular syntax of where these fields will actually reside. And for the purposes of the MOA2 Project, we will deliver all the administrative metadata external to the image file header.
In this section we primarily discuss administrative metadata for "master" files. But in the future, repositories are likely to see "master" files which are themselves derivatives of previous files. In order to make the administrati ve metadata we identify as compatible as possible with future developments, we have included a minimal amount of information that deals with derivative files (or other instantiations of a work). This will hopefully lay the groundwork for future research p rojects to be able to identify and trace the provenance of a particular digital work.
Administrative Metadata Elements and Features Tables
As with the structural metadata tables presented above, these tables attempt to be comprehensive and are recommendations for the full set of possible administrative metadata elements that we think an individual collection may possibly find usef ul. Some repositories will only use the minimum set of required elements. Other repositories will also use elements that can be derived in an automated fashion. Still others will choose to use elements that are easy to derive. The table includes both mini mal and maximal values, which are allowed to repeat, etc. Some elements can fulfill both administrative and structural functions.
Though the number of metadata fields may at first seem daunting, a high proportion of the fields is likely to be the same for all the images scanned during a particular scanning session. For example, metadata about the scanning device, light source, d ate, etc. is likely to be the same for an entire session. And some metadata about the different parts of a single object (such as the scan of each page of a book) will be the same for that entire object. This kind of repeating metadata will not require ke yboarding each individual metadata field for each digital image; instead, these can be handled either through inheritance or by batch-loading of various metadata fields. In any case, this is an attempt to identify best practices for metadata development, and we expect that individual repositories will follow this to the extent that they can afford.
The rest of this section is divided into 4 convenient parts: elements for the creation of a digital master image; identifying the digital image and what is needed to view or use it; linking the parts of a digital object or its instantiations, providin g context; and ownership, rights, and reproduction information. The first two parts, both recorded at the point of capture, uniquely identify a particular representation of a work. For future derivative images, these could be iteratively nested to represe nt the provenance of a work.
|source type||Photographic print, slide, manuscript, printed page(s), another digital image||to identify the material from which the digital file was created - the item on hand, even if it itself is a reformatted version, e.g. the scan of a 35mm slide of a painting would be entered here as a 35mm slide||Yes||No||
|source physical dimensions||10.2cm x 18.4cm||Actual physical dimension scanned if cropped. Needed for appropriate facsimile output||Yes||No||
|source characteristics||film type/ASA/manu-facturer, print type; tightly bound volume||Relevant if an intermediary stage is actually removed from 'original'; or may add descriptive details of source which may impact on scanning quality||No||No||
|source ID||a local catalog unique ID for a book; an accession number for a special collections item||the source of the source image (recursively)||Yes||No||
|scanning date||any usual time stamp: yyyy/mm/dd or yyyy/mm||Need date to year/month specificity to assist in later evaluation of technology at the time of digital master creation.||Yes||No||Automatically generated|
|ICC scanner profile||
||Describes the color artifacts introduced by the scanning device. Necessary to map the images into standard color space and to adjust for display and printing devices.||No||No||Generated once per session|
|Light source||Example: 3400K Tungsten, infrared, Osram Delux L fluorescent||Should be specific to settings for this scan (f-stop, electronic shutter speed, filtering, illumination level); may be necessary in later evaluation of color capture. Again, may be specific to each image or by inheritance to collections of images a via a separate descriptive file (with anomalies indicated per image as needed).||No||No||Batch generated|
|Resolution||600 dpi; 400 dpi interpolated to 600 dpi; 1536 x 1024||the settings on the input scanning device (cameras usually measure these in dimensions, other devices in dpi). Note where device does its own interpolation.||No||No||Automatically generated|
Identifying the digital image (master or derivative) and what is needed to view or use it (recorded at point of capture).
This metadata is needed by applications programs in order to recognize how to initially display the digital object, including notes as to file format, compression schemes, and color space. Today there are common conventions for carrying much of this information in a file's header, but it is not certain that future software will be able to interpret all of these. (For example, today's operating systems can look at the beginning of file headers and determine whether the file is Microsoft Word, Ad obe Acrobat, or a JFIF/JPEG file. But those same operating systems may not recognize less common file formats, or even earlier versions of a format as prevalent as Microsoft Word.) It is important that this information be expressed in a consistent way in fields within the file header that are clearly readable (such as uncompressed ASCII). There are common conventions for a number of these fields, as well as for expression of field contents. In addition, applications software automatically saves most of th is information within the header when files are created, so for most of these fields there is no issue of expense or difficulty in finding and noting the proper metadata.
|Type of Image||MIME TYPES, bit-mapped||To determine what class of image, and hence what general viewer type will be needed.||Yes||No||Automatically generated|
|File format||TIFF,GIF, JFIF, SPIFF, FlashPix, JTIP, PICT, PCD, PhotoShop, EPS,||File format needed for viewer to display image.||Yes||No||Automatically generated|
|(Lossless) compression format||LZW||Type of algorithm needed to decompress the image, with note of software package used to apply the format, and degree/percentage of compression used where options exist.||Yes||No||Automatically generated|
|Dimensions||310 x 437||Dimensions in pixels, often needed by viewer, and acts as an indication of quality to user.||Yes||No||Automatically generated|
|Bit-depth||1, 8, 24, color, grey scale||Color depth, often needed by viewer and acts as an indication of quality to user.||Yes||No||Automatically generated|
|Color Lookup Table (CLUT)||(usually a binary table of RGB values)||Color values actually used in the image, often needed by some file formats, especially GIF.||Yes||No||Automatically generated|
|Color space||CMYK, RGB, Lab||Color space used, often needed by viewer and indicates whether image was initially created for onscreen display or for pre-press output. (Some color space parameters such as white point may require individual tags).||Yes||No||Automatically generated|
Linking the parts of a digital object or its instantiations, providing context (overlaps with Structural)
|Overall View Image||the image file representing the overall view (used to find the location of a detail within the overall image); may not apply if details are not used||If this image file represents a detail or part of a another image, the parent file should be indicated here.||No||No||
|Sequence Number||Example: 4 of 5; 2B of [Primary Image ID](?)||Relative position of a particular image in an image file chain that begins with the file named in the PRIMARY IMAGE tag. There is no one clear-cut labeling system for this concept: should an arbitrary sequence number be provided for detail images that are linked to a primary image when there is no obvious sequence? Unlike the pages of a book, where sequencing is critical to textual integrity, detail images of a larger view image may be sequenced according to many different criteria, i.e. wide view to narr ow view, left to right, top to bottom, or no particular order at all.||No||No||
|Sequence Total||250 (equal to the number of related image files in the chain; i.e. the book has 250 pages, each page represented by one image file)||The total number of image files in a given sequence; this number may not be known at the time of capture but should be calculated' prior to use of master or beginning of derivative production.||No||No||
|Version (from MESL Data Dictionary - NR)||10 /13/95; from the second edition of the permanent catalog||This field contains the full text of any information that the content provider considers necessary to uniquely identify the version of this information represented. This field may contain an arbitrary number or the date of creation of the electronic data set, or may point to any internal version control information needed by the content provider.||No||No||
|Version Date||DEFINITION: mm/dd/yy.||date the version referred to in VERSION was created; could be somewhat redundant if this data is used in the VERSION field||No||No||
|Owner||EXAMPLE: Saskia||Owner(s) of the copyright on the digital image file, which MAY be the creator of the digital image file, or the person(s) from whom the digital image file was purchased or licensed. It should contain the name(s) of the person(s) from whom copy/distributio n and display/transmission rights may be secured. Note: this refers to the copyright on the digital image only, not the work(s) represented in the digital image.||No||Yes||Likely to be inherited for an entire collection|
|Owner Number NR)||Example: [widely varies]||Any number or alphanumeric string that uniquely identifies the image as belonging to the owner. It can take the form of numbers, text strings, barcodes, electronic ID number, or file name.||No||No||Likely to be inherited for an entire collection|
|Copyright Date||EXAMPLE: 1997||Date of copyright expressed as yyyy; in current approaches to interpretation of copyright law, the year is sufficient information.||No||No||Likely to be inherited for an entire collection|
|Credit Line (from MESL data Dictionary - NR)||DEFINITION: The text required to be displayed whenever the image/data appears. EXAMPLE: Copyright Berkeley Art Museum, 1978. All rights reserved.||
||No||No||Likely to be inherited for an entire collection|
|Copy / Distribution Restrictions||DEFINITION: text that spells out any copyright restrictions pertaining to the copy and distribution of this image file. EXAMPLE: Copy and distribution of this file is prohibited without the express written consent of...||
||No||No||Likely to be inherited for an entire collection|
|Display/Transmission Restrictions||DEFINITION: text that spells out any copyright restrictions regarding the transmission and display of this image file. EXAMPLE: This file may be displayed or transmitted across a network only by person(s) who have signed a license agreement with ...||
||No||No||Likely to be inherited for an entire collection|
|License Term||DEFINITION: specifies the duration of any licensing arrangement covering this image||
||No||No||Likely to be inherited for an entire collection|
|License Begin Date||DEFINITION: start date of any licensing agreement covering this image expressed as mm/dd/yy||
||No||No||Likely to be inherited for an entire collection|
|License End Date||DEFINITION: end date of any licensing agreement covering this image expressed as mm/dd/yy||
||No||No||Likely to be inherited for an entire collection|
Encoding - Best Practices Encoding Archival Object Content and Finding Aids Many of the MoA II materials will involve text encoding. This may be the case whether the documents are carefully transcribed and edited versions of the original documents, whether they simply organize (conceptually) a mass of automatically generated OCR, or whether only the framework of a document is encoded, with pointers to images. Moreover, finding aids for many resources will be encoded to support fine-grained access to a collection. The DLF is fortunate to be able to rely on substantia l work and large community efforts in both of these areas. Moreover, work is underway in the DLF to organize discussions around our use of the available guidelines.
For the encoding of finding aids, the Encoded Archival Description (EAD) should be used by project participants. Information about the EAD, including guidelines for the application of the EAD as well as DTDs, is available at http://lcweb.loc.gov/ead/. While it is the case that the EAD guidelines allow considerable latitude for the application of markup to finding aids, work with the EAD must grow out of local assessment of the needs for finding aid support and t he way that these finding aids will be used. Discussions are underway in the DLF surrounding inter-institutional searching of EAD-encoded collections, and the ways that this will cause us to give scrutiny to local practice. Rather than those proposed effo rts, continuing to drive the application of EAD by locally defined needs will help clarify the range of needs for inter-institutional applications.
Text encoding efforts in MoA II will be well supported by the SGML articulated in the Text Encoding Initiative Guidelines (TEI). Information about the TEI can be found at: http://www-tei.uic.edu/orgs/tei/ . A searchable/browsable version of the TEI Guidelines can be found at: http://www.hti.umich.edu/docs/TEI/. The TEI offers support for a broad range of types of documents and methods, including the transcri ption of primary sources and damaged documents. More importantly, the TEI Guidelines and the associated DTDs offer support for encoding the wide range of structures that may be present in MoA II documents, regardless whether transcriptions are included. J ust as with the EAD, the TEI offers considerable flexibility in the ways documents can be encoded. Discussions are underway in the DLF surrounding a June/July meeting to discuss the use of the TEI by digital library projects.
A further note on the relevance of XML to these two central encoding schemas may be useful. XML promises to bring richly encoded documents to the user's desktop through widely available browsers. Moreover, a growing array of XML-capable tools should b e available through mainstream software development. It is the expectation of the authors of this white paper that we will soon see XML-compliant versions of both the TEI and the EAD DTDs. One editor of the TEI Guidelines has been centrally involved in th e writing of the XML specifications and the TEI editors have declared their intention to create XML-compliant versions of the widely used TEI DTDs. We are likely to see no less from the EAD.
Because image capture capabilities are changing so rapidly, we will divide the "best practices" discussion into two parts: general recommendations that should apply to many different types of objects, and specific minimum recommendations to be used during the course of the MoA II testbed project. Below you will find a discussion of the practices that we think are fairly universal, and we believe that this portion of the document will be usable for many years to come. This includes the notion of masters and derivatives, when images should be corrected to "look better", etc. This also contains some discussion of how to go about selecting image quality for a particular collection, and issues in choosing file formats. The section, Summ ary of General Recommendations, found at the end of Part IV provides a list of these suggested best practices.
But the issues of image quality and file formats are both complex (and vary from collection to collection) and in flux (due to rapid technological developments and emerging standards). Therefore, at the end of Part IV, we have also summarized the more specific recommendations to be employed right now in MoA II, and provide a list of minimally acceptable levels rather than a precise set of guidelines (see: Specific Minimum Recommendations for this Project).
Recommendations for the full set of structural and administrative metadata are listed in Part III (above). Standards and procedures for the image capture process are described below.
Scanning Appropriate scanning procedures are dictated by the nature of the material and the product one wishes to create. There is no single set of image quality parameters that should be applied to all documents that will be scanned. Decisions as to image quality typically take into consideration the research needs of users (and potential users), the types of uses that might be made of that material, as well as the artifactual nature of the material itself. The best situation is one where the source materials and project goals dictate the image quality settings and the hardware and software one employs. Excellent sources of information are available, including the experience of past and current library and archival projects (see Appendix Bibliograph y section entitled "Scanning and Image Capture"). The pure mechanics of scanning are discussed in Besser (Procedures and Practices for Scanning), Besser and Trant (Introduction to Imaging) and Kenney's Cornell manual (Digital Imaging for Librari es and Archives). It is recommended that imaging projects consult these sources to determine appropriate options for image capture. Decisions of quality appropriate for any particular project should be based on best anticipation of use of the digital reso urce.
Digital Masters And Their Derivatives Digital master files are created as the direct result of image capture. The digital master should represent as accurately as possible the visual information in the original object. (Note: this is similarity in terms of technical fidelity usi ng objective technological measurements; this is not accuracy as determined by comparing the object scanned to an image on a display device. This type of accuracy is obtained by the manipulation of settings before scanning rather than by image processing after scanning). The primary functions of digital master files are to serve as an archival image and as a source for derivative files. In the archival sense, a digital master file may serve as a surrogate for the original, may completely replace originals or be used as security against possible loss of originals due to disaster, theft and/or deterioration. Derivative files are created from digital master images for editing or enhancement, conversion of the master to different formats, and presentation and transmission over networks. Typically, one would capture the master file at a very high level of image quality, then would use image processing techniques (such as compression and resolution reduction) to create the derivative images which would be deliv ered to users.
Long term preservation of digital master files requires a strategy of identification, storage, and migration to new media and policies about their use and access to them. The specifications for derivative files used for image presentation may change o ver time; digital masters with an archival purpose can be processed by different presentation methods to create necessary derivative files without the expense of digitizing the original object again.
Image Quality Image quality for digital capture from library originals is a measure of the completeness and the accuracy of the capture of the visual information in the original. There is some subjectivity involved in determining completeness and accuracy (should the digital representation of faded or stained handwriting show legibility or reflect the illegibility of the source material?). Image quality should be judged in terms of the goals of the project.
Image quality depends on the project's planning choices and implementation. Project designers need to consider what standard practices they will follow for input resolution and bit depth, layout and cropping, image capture metric (including color mana gement), and the particular features of the capture device and its software. Benchmarking quality (see Kenney's Cornell Manual) for any given type of source material can help one select appropriate image quality parameters that capture just the amount of information needed from the source material for eventual use and display. By maximizing the image quality of the digital master files, managers can ensure the on-going value of their efforts, and ease the process of derivative file production.
Quality is necessarily limited by the size of the digital image file, which places an upper limit on the amount of information that can be stored. The size of a digital image file depends on the size of the original and the resolution of capture (numb er of pixels in both height and width that are sampled from the original to create the digital image), the number of channels (typically 3: Red, Green, and Blue: "RGB"), and the bit depth (the number of data bits used to store the image data for one pixel).
Measuring the accuracy of visual information in digital form implies the existence of a capture metric, i.e., the rules that give meaning to the numerical data in the digital image file. For example, the visual meaning of the pixel data Red=246, Green =238, Blue=80 will be a shade of yellow, which can be defined in terms of visual measurements. Most capture devices capture in RGB using software based on the video standards defined international agreements. A useful introduction to these topics can be f ound in Poynton's Color FAQ: <http://www.inforamp.net/~poynton/ColorFAQ.html>. We strongly urge that imaging projects adopt standard target values for color metrics as Poynton discusses, s o that the project image files are captured uniformly.
A reasonably well-calibrated grayscale is all but required for measuring and adjusting the capture metric of a scanner or digital camera. We recommend that a standard target consisting of grayscale, centimeter scale, and standard color patches be incl uded along one edge of every image captured, to provide an internal reference within the image for linear scale and capture metric information. Kodak makes a set consisting of grayscale (with approximate densities), color patches, and linear scale which i s available in two sizes: 8 inches long (Q-13, CAT 152 7654) and 14 inches long (Q-14, CAT 152 7662)
Bit depth is an indication of an image's tonal qualities. Bit depth is the number of bits of color data which are stored for each pixel; the greater the bit depth, the greater the number of gray scale or color tones that can be represented and the lar ger the file size. The most common bit depths are:
Lossy compression is unwise, as we do not yet know how today's lossy compression schemes (optimized for human eyes viewing a CRT screen) may affect future uses of digital images (such as computer-based analysis systems or display on future display dev ices). Unlike lossy compression, lossless compression will not eliminate data we may later find useful. But lossless compression adds a level of complexity to decoding the file many years hence. And many vendor products that claim to be lossless (primaril y those that claim "lossless JPEG") are actually lossy. Those who choose lossless compression should make sure they take into consideration digital longevity issues.
The objective of color management is to control the capture and reproduction of color in such a way that an original print can be scanned, displayed on a computer monitor, and printed, with the least possible change of appearance from the original to the monitor to the printed version. This objective is made difficult by the limits of color reproduction: input devices such as scanners cannot "see" all the colors of human vision, and output devices such as computer monitors and printers have even more limited ranges of colors they can reproduce. Most commercial color management systems are based on the ICC (International Color Consortium) data interchange standard, and are often integrated with image processing software used in the publishing industry. They work by systematically measuring the color properties of digital input devices and of digital output devices, and then applying compensating corrections to the digital file to optimize the output appearance. Although color management syste ms are widely used in the publishing industry, there is no consensus yet on standards for how (or whether) color management techniques should be applied to digital master files. Until a clear standard emerges, it is not recommended that digital master fil es be routinely processed by color management software.
Useful image quality guidelines for different types of source materials are listed in Puglia & Rosinkski's NARA Guidelines and in Kenney's Cornell Manual (see bibliography).
Formats Digital masters should capture information using color rather than grayscale approaches where there is any color information in the original documents. Digital masters should use lossless compression schemes and be stored in internationally recognized formats. TIFF is a widely used format, but there are many types of TIFF files, and consistency in use of the files by a variety of applications (viewers, printers etc.) is a necessary consideration. In the future, we hope that international sta ndardization efforts (such as ISO attempts to define TIFF-IT and SPIFF) will lead vendors to support standards-compliant forms of image storage formats. Proprietary file formats (such as Kodak's Photo CD) should be avoided.
Image Metadata Metadata or data describing digital images must be associated with each image created, and most of this should be noted at the point of image capture. Image metadata is needed to record information about the scanning process itself, about th e storage files that are created, and about the various pieces that might compose a single object.
As mentioned earlier in this paper, the number of metadata fields may at first seem daunting. However, high proportions of these fields are likely to be the same for all the images scanned during a particular scanning session. For example, metadata ab out the scanning device, light source, date, etc. is likely to be the same for an entire session. And some metadata, about the different parts of a single object (such as the scan of each page of a book), will be the same for that entire object. This kind of repeating metadata will not require keyboarding each individual metadata field for each digital image; instead, these can be handled either through inheritance or by batch-loading of various metadata fields.
Administrative metadata includes a set of fields noting the creation of a digital master image, identifying the digital image and what is needed to view or use it, linking its parts or instantiations to one another, and ownership and reproduction info rmation. Structural metadata includes fields that help one reassemble the parts of an object and navigate through it. Details about administrative and structural metadata tags are noted in Part III.
Summary of General Recommendations
Bibliography Organization of Information for Digital Objects The article "An Architecture for Information in Digital Libraries" by William Arms, Christophe Blanchi and Edward Overly of the Corporation for National Research Initiatives and published in D-Lib Magazine, February 1997 iss ue.http://www.dlib.org/dlib/february97/cnri/02arms1.html
Repository Access Protocol - Design Draft - Version 0.0 by Christophe Blanchi of CNRI is found at http://titan.cnri.reston.va.us:8080/pilot/locdesign.html and begins " This document describes the repository prototype for the Library of Congress. This design is based on version 1.2 of the Repository Access Protocol (RAP) and the Structural Metadata Version 1.1 from the Library of Congress."
"The Warwick Framework: A Container Architecture for Aggregating Sets of Metadata" by Carl Lagoze, Digital Library Research Group, Computer Science Department, Cornell University; Clifford A. Lynch, Office of the President, University of Cal ifornia, and Ron Daniel Jr., Advanced Computing Lab, Los Alamos National Laboratory (July, 1996)
Metadata [Cornell University Library] METADATA WORKING GROUP REPORT to Senior [Library] Management, JULY 1996 http://www.library.cornell.edu/DLWG/MWGReporA.htm
and the related work "Distillation of [Cornell UL] Working Group Recommendations" November, 1996 http://www.library.cornell.edu/DLWG/DLMtg.html
"Information Warehousing: A Strategic Approach to Data Warehouse
Development" by Alan Perkins, Managing Principal of Visible Systems Corporation (White Paper Series)
SGML as Metadata: Theory and Practice in the Digital Library. Session organized by Richard Gartner (Bodleian Library, Oxford)
"A Framework for Extensible Metadata Registries" by Matthew Morgenstern of Xerox, a visiting fellow of the Design Research Institute at Cornell http://dri.cornell.edu
Using the Library of Congress Repository model, developed and used in the National Digital Library Program:
Using the Library of Congress Repository model, developed and used in the National Digital Library Program:
Using the Library of Congress Repository model, developed and used in the National Digital Library Program:
The Structural Metadata Dictionary for LC Repository Digital Objects http://lcweb.loc.gov:8081/ndlint/repository/structmeta.html
which then leads to further documentation of their Data Attributes
with a list of the attributes
and their definitions
The same site then gives examples of using this model for a photo collection
a collection of scanned page images
and a collection of scanned page images and SGML encoded, machine-readable text
Scanning And Image Capture Howard Besser and Jennifer Trant. Introduction to Imaging. Getty Art History Information Project.
Image Quality Working Group of ArchivesCom, a joint Libraries/AcIS Committee. Technical Recommendation for Digital Imaging Projects,
Howard Besser. Procedures & Practices for Scanning, Procedures and Processes for Scanning. Canadian Heritage Information Network (CHIN), http://sunsite.Berkeley.edu/Imaging/Databases/Scanning Electronic Text Center at Alderman Library, University of Virginia. "Image Scanning: A Basic Helpsheet,
Electronic Text Center at Alderman Library, University of Virginia. "Text Scanning: A Basic Helpsheet"
Michael Ester. Digital Image Collections: Issues and Practice. Washington, D.C. , Commission on Preservation and Access (December, 1996).
Carl Fleischhauer. Digital Historical Collections: Types, Elements, and Construction. National Digital Library Program, Library of Congress, http://lcweb2.loc.gov/ammem/elements.html.
Carl Fleischhauer. Digital Formats for Content Reproductions. National Digital Library Program, Library of Congress.
Picture Elements, Inc. Guidelines for Electronic Preservation of Visual Materials (revisiosn 1.1, 2 March 1995). Report submitted to the Library of Congress, Preservation Directorate.
Reilly, James M and Franziska S. Frey, "Recommendations for the Evaluation of Digital Images Produced from Photographic, Microphotographic, and Various Paper Formats" Report to the Library of Congress, National Digital Library Project by Ima
ge Permanence Institute. May, 1996
Anne R. Kenney. Digital Imaging for Libraries and Archives. Cornell University Library, June 1996.
International Color Consortium:
Steven Puglia and Barry Roginski. NARA Guidelines for Digitizing
Archival Materials for Electronic Access, College Park: National Archives
and Records Administration, January 1998.
International Organization for Standardization, Technical Committee 130 (n.d.). ISO/FDIS 12639: Graphic technology - Prepress digital data exchange - Tag image file format for image technology (TIFF/IT). Geneva: International Organization fo r Standardization (ISO).
Poynton's Color FAQ: