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1 PREMIS Contents: version 2.0 March 2008 Acknowledgments Introduction Background The PREMIS Data Model General Topics Implementation Considerations The PREMIS Data Dictionary Version 2.0 Special Topics Methodology Glossary

2 PREMIS Data Dictionary for Preservation Metadata version 2.0 PREMIS Editorial Committee March 2008

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4 CONTENTS Acknowledgments... ii PREMIS Web Sites and ... iv Introduction...1 Background...1 Development of the original PREMIS Data Dictionary...2 Implementable, core preservation metadata...3 The PREMIS Data Model...5 More on Objects...7 Intellectual Entities and Objects...9 More on Events...10 More on Agents...11 More on Rights...11 General Topics on the Structure and Use of the Data Dictionary...12 Identifiers...12 Relationships between Objects...13 Relationships between entities of different types...14 The 1:1 principle...14 Implementation Considerations...15 PREMIS conformance...15 Implementation of the data model...16 Storing metadata...17 Supplying metadata values...17 Extensibility...19 The PREMIS Data Dictionary Version Limits to the scope of the Data Dictionary...23 Object Entity...25 Event Entity Agent Entity Rights Entity Special Topics Format information Environment Object characteristics and composition level: the onion model Fixity, integrity, authenticity Digital signatures Non-core metadata Methodology Glossary Data Dictionary for Preservation Metadata: PREMIS version 2.0 i

5 ACKNOWLEDGMENTS PREMIS Editorial Committee members Rebecca Guenther, Library of Congress, Chair Steve Bordwell, General Register Office for Scotland Olaf Brandt, Koninklijke Bibliotheek, Netherlands Priscilla Caplan, Florida Center for Library Automation Gerard Clifton, National Library of Australia Angela Dappert, British Library Markus Enders, Staats- und Universitätsbibliothek Göttingen/British Library Brian Lavoie, OCLC Bill Leonard, Library and Archives Canada Zhiwu Xie, Los Alamos National Laboratory Special thanks These individuals contributed their expertise as former members of the PREMIS Editorial Committee: Rory McLeod, British Library Yaniv Levi, ExLibris These individuals were the original Preservation Metadata: Implementation Strategies (PREMIS) Working Group that developed version 1 of the Data Dictionary: Priscilla Caplan, Florida Center for Library Automation, co-chair Rebecca Guenther, Library of Congress, co-chair Robin Dale, RLG liaison Brian Lavoie, OCLC liaison George Barnum, U.S. Government Printing Office Charles Blair, University of Chicago Olaf Brandt, Göttingen State and University Library Mikki Carpenter, Museum of Modern Art Adam Farquhar, British Library David Gewirtz, Yale University Keith Glavash, MIT/DSpace Andrea Goethals, Florida Center for Library Automation Cathy Hartman, University of North Texas Helen Hodgart, British Library Nancy Hoebelheinrich, Stanford University Roger Howard, J. Paul Getty Museum ii Data Dictionary for Preservation Metadata: PREMIS version 2.0

6 Sally Hubbard, Getty Research Institute Mela Kircher, OCLC John Kunze, California Digital Library Vicky McCargar, Los Angeles Times Jerome McDonough, New York University/METS Evan Owens, Ithaka-Electronic Archiving Initiative Erin Rhodes, U.S. National Archives and Records Administration Madi Solomon, Walt Disney Corporation Angela Spinazze, ATSPIN Consulting Stefan Strathmann, Göttingen State and University Library Günter Waibel, RLG Lisa Weber, U.S. National Archives and Records Administration Robin Wendler, Harvard University Hilde van Wijngaarden, National Library of the Netherlands Andrew Wilson, National Archives of Australia and British Library Deborah Woodyard-Robinson, British Library and Woodyard-Robinson Holdings Ltd. Data Dictionary for Preservation Metadata: PREMIS version 2.0 iii

7 PREMIS WEB SITES AND PREMIS maintenance activity Web site: PREMIS Implementers' Group discussion list: To subscribe, send to with the message, "subscribe pig [your name]" Please send comments and questions to iv Data Dictionary for Preservation Metadata: PREMIS version 2.0

8 INTRODUCTION INTRODUCTION Background In June 2003, OCLC and RLG jointly sponsored the formation of the PREMIS (Preservation Metadata: Implementation Strategies) working group, comprised of international experts in the use of metadata to support digital preservation activities. The working group s membership included more than 30 participants, representing five different countries and a variety of domains, including libraries, museums, archives, government agencies, and the private sector. Part of the working group s charge was to develop a core set of implementable preservation metadata, broadly applicable across a wide range of digital preservation contexts and supported by guidelines and recommendations for creation, management, and use. This portion of the working group s charge was fulfilled in May 2005 with the release of Data Dictionary for Preservation Metadata: Final Report of the PREMIS Working Group. That 237-page Report provides a wealth of resources on preservation metadata. First and foremost is the Data Dictionary itself, a comprehensive, practical resource for implementing preservation metadata in digital archiving systems. The Data Dictionary defines preservation metadata that: Supports the viability, renderability, understandability, authenticity, and identity of digital objects in a preservation context; Represents the information most preservation repositories need to know to preserve digital materials over the long-term; Emphasizes implementable metadata : rigorously defined, supported by guidelines for creation, management, and use, and oriented toward automated workflows; and Embodies technical neutrality: no assumptions made about preservation technologies, strategies, metadata storage and management, etc. In addition to the Data Dictionary, the working group also published a set of XML schema to support implementation of the Data Dictionary in digital archiving systems. The PREMIS Data Dictionary was awarded the 2005 Digital Preservation Award, given under the auspices of the British Conservation Awards, as well as the 2006 Society of American Archivists Preservation Publication Award. Following the release of the Data Dictionary in 2005, the PREMIS working group retired and the PREMIS Maintenance Activity, sponsored by the Library of Congress, was initiated to maintain the Data Dictionary and coordinate other work to advance understanding of preservation metadata and related topics. In addition to providing a permanent Web home for the Data Dictionary, XML schema, and related materials, the Maintenance Activity also operates the PREMIS Implementers Group (PIG) discussion list and wiki, conducts tutorials on the Data Dictionary and its use, and commissions focused studies on preservation metadata topics. The Maintenance Activity also established an Editorial Committee responsible for further development of the Data Dictionary and the XML schema and promoting their use. Data Dictionary for Preservation Metadata: PREMIS version 2.0 1

9 INTRODUCTION The membership of the Editorial Committee reflects a variety of countries and institutional backgrounds. At the time of the Data Dictionary s release, the decision was made to freeze its content for at least 18 months, giving the digital preservation community time to read and digest it, experiment with its implementation, identify errors, and most importantly, provide feedback on ways that the Data Dictionary could be improved to increase its value and ease of application. Feedback was collected through a variety of mechanisms, and in 2007, the Editorial Committee determined that a sufficient level of commentary had accumulated to warrant undertaking the first revision of the Data Dictionary. The members of the Editorial Committee revised the Data Dictionary, making every effort to engage stakeholders in the process of revision. The Committee kept the preservation community informed of issues being discussed, solicited comment on proposed revisions, and consulted outside experts where appropriate. The result of this process is the PREMIS Data Dictionary for Preservation Metadata version 2.0. Development of the original PREMIS Data Dictionary The PREMIS working group was established to build on the earlier work of another initiative sponsored by OCLC and RLG: the Preservation Metadata Framework (PMF) working group. In the PMF working group outlined the types of information that should be associated with an archived digital object. Their report, A Metadata Framework to Support the Preservation of Digital Objects (the Framework), proposed a list of prototype metadata elements. 1 However, additional work was needed to make these prototype elements implementable. The PREMIS working group was asked to take the PMF group s work a step further and develop a data dictionary of core metadata for archived digital objects, as well as give guidance and suggest best practice for creating, managing, and using the metadata in preservation systems. Since the PREMIS working group had a practical rather than theoretical focus, members were sought from institutions known to be operating or developing preservation repository systems within the cultural heritage and information industry sectors. Diverse perspectives were also sought. The working group consisted of representatives from academic and national libraries, museums, archives, government, and commercial enterprises in five different countries. In addition, PREMIS called upon an international advisory committee of experts to review progress. To understand how preservation repositories were actually implementing preservation metadata, in November 2003 the working group undertook a survey of about 70 organizations thought to be active in or interested in digital preservation. The survey provided an opportunity to explore the state of the art in digital preservation generally, and questions were drafted to elicit information about policies, governance and funding, system architecture, and preservation strategies, as well as metadata practices. The subgroup contacted 16 of 48 respondents by telephone for more in-depth interviews. In December 2004 the PREMIS working group published its report based on the survey of digital repositories, Implementing Preservation Repositories for Digital Materials: Current Practice and Emerging Trends in the Cultural Heritage Community (the Implementation Survey Report). 2 The findings of this survey were extremely helpful in informing the working group s discussions as it developed the Data Dictionary. 2 Data Dictionary for Preservation Metadata: PREMIS version 2.0

10 INTRODUCTION Both the earlier Framework and the PREMIS Data Dictionary build on the Open Archival Information System (OAIS) reference model (ISO 14721). 3 The OAIS information model provides a conceptual foundation in the form of a taxonomy of information objects and packages for archived objects, and the structure of their associated metadata. The Framework can be viewed as an elaboration of the OAIS information model, explicated through the mapping of preservation metadata to that conceptual structure. The PREMIS Data Dictionary can be viewed as a translation of the Framework into a set of implementable semantic units. However, it should be noted that the Data Dictionary and OAIS occasionally differ in terminology usage; these differences are noted in the Glossary that accompanies this report. Differences usually reflect the fact that PREMIS semantic units require more specificity than the OAIS definitions provide, which is to be expected when moving from a conceptual framework to an implementation. Implementable, core preservation metadata The PREMIS Data Dictionary defines preservation metadata as the information a repository uses to support the digital preservation process. Specifically, the group looked at metadata supporting the functions of maintaining viability, renderability, understandability, authenticity, and identity in a preservation context. Preservation metadata thus spans a number of the categories typically used to differentiate types of metadata: administrative (including rights and permissions), technical, and structural. Particular attention was paid to the documentation of digital provenance (the history of an object) and to the documentation of relationships, especially relationships among different objects within the preservation repository. The group considered a number of definitions of core. In one view, core describes any metadata absolutely required under any circumstances. In another, core means that metadata is applicable to any type of repository implementing any type of preservation strategy. PREMIS uses this practical definition: things that most working preservation repositories are likely to need to know in order to support digital preservation. The words most and likely were chosen deliberately. Core does not necessarily mean mandatory, and some semantic units were designated as optional when exceptional cases were apparent. The concept of implementability also required definition. Most preservation repositories deal with large quantities of data. Therefore, a key factor in the implementability of preservation metadata is whether the values can be automatically supplied and automatically processed by the repository. Whenever possible the group defined semantic units that do not require human intervention to supply or analyze. For example, coded values from an authority list are preferred over textual descriptions. The working group decided that the Data Dictionary should be wholly implementation independent. That is, the core metadata define information that a repository needs to know, regardless of how, or even whether, that information is stored. For instance, for a given identifier to be usable, it is necessary to know the identifier scheme and the namespace in which it is unique. If a particular repository uses only one type of identifier, the repository would not need to record the scheme in association with each object. The repository would, however, need to know this information and to be able to supply it when exchanging metadata with other repositories. Because of the emphasis on the need to know rather than the need to record or Data Dictionary for Preservation Metadata: PREMIS version 2.0 3

11 INTRODUCTION represent in any particular way, the group preferred to use the term semantic unit rather than metadata element. The Data Dictionary names and describes semantic units. 4 Data Dictionary for Preservation Metadata: PREMIS version 2.0

12 INTRODUCTION The PREMIS Data Model The working group developed a simple data model to organize the semantic units defined in the Data Dictionary. The data model defines five entities the working group felt were particularly important in regard to digital preservation activities: Intellectual Entities, Objects, Events, Rights, and Agents. 4 Each semantic unit defined in the Data Dictionary is a property of one of the entities in the data model. Figure 1 provides a graphical illustration of the PREMIS Data Model. Figure 1: The PREMIS Data Model In Figure 1, entities are represented by boxes; relationships between entities are represented by arrows. The direction of the arrow indicates the direction of the relationship linkage as it is recorded in the preservation metadata. For example, the arrow pointing from the Rights entity to the Agents entity means that the metadata associated with the Rights entity includes a semantic unit recording information about the relationship with an Agent. The arrow pointing from the Objects entity back to itself indicates that the semantic units defined in the Data Dictionary support the recording of relationships between Objects. No other entity in the data model supports relationships of this type; in other words, while Objects can be related to other Objects, Events cannot be related to other Events, Agents cannot be related to other Agents, and so on. Data Dictionary for Preservation Metadata: PREMIS version 2.0 5

13 INTRODUCTION The entities in the PREMIS data model are defined as follows: Intellectual Entity: a set of content that is considered a single intellectual unit for purposes of management and description: for example, a particular book, map, photograph, or database. An Intellectual Entity can include other Intellectual Entities; for example, a Web site can include a Web page; a Web page can include an image. An Intellectual Entity may have one or more digital representations. Object (or Digital Object): a discrete unit of information in digital form. 5 Event: an action that involves or impacts at least one Object or Agent associated with or known by the preservation repository. Agent: person, organization, or software program/system associated with Events in the life of an Object, or with Rights attached to an Object. Rights: assertions of one or more rights or permissions pertaining to an Object and/or Agent. The PREMIS Data Dictionary defines semantic units. Each semantic unit defined in the Data Dictionary is mapped to one of the entities in the data model. In this sense, a semantic unit may be viewed as a property of an entity. For example, the semantic unit size is a property of an Object entity. units have values: for a particular Object the value of size might be In most cases, a particular semantic unit is unambiguously a property of only one type of entity. The size of an Object is clearly a property of the Object entity. In some cases, however, a semantic unit applies equally to two or more types of entity. For example, Events have outcomes. If a migration event creates a file that has lost some important feature, the loss of that feature might be considered an outcome of the Event, and therefore a property of the Event entity. Alternatively, it might be considered an attribute of the new file, and therefore a property of the Object entity. When a semantic unit applies equally to multiple entity types, the semantic unit is associated with only one type of entity in the Data Dictionary. The data model relies upon links between the different entities to make these relationships clear. In the example above, the loss of the feature is treated as a detailed outcome of the Event, where the Event contains the identifier of the Object involved. What is important is that this association is arbitrary and is not meant to imply that a particular implementation is required. In some cases a semantic unit takes the form of a container that groups a set of related semantic units. For example, a semantic unit identifier groups the two semantic units identifiertype and identifiervalue. The grouped subunits are called semantic of the container. Some containers are defined as extension containers, to allow the use of metadata encoded according to an external schema. This enables PREMIS to be extended with metadata elements that are more granular, non-core, or otherwise out of scope for the Data Dictionary. A relationship is a statement of association between instances of entities. Relationship can be interpreted broadly or narrowly, and expressed in many different ways. For example, the statement Object A is of format B could be considered a relationship between A and B. The PREMIS model, however, treats format B as a property of Object A. PREMIS reserves 6 Data Dictionary for Preservation Metadata: PREMIS version 2.0

14 INTRODUCTION relationship for associations between two or more Object entities or between entities of different types, such as an Object and an Agent. More on Objects The Object entity has three subtypes: file, bitstream, and representation. A file is a named and ordered sequence of bytes that is known by an operating system. A file can be zero or more bytes and has a file format, access permissions, and file system characteristics such as size and last modification date. A bitstream is contiguous or non-contiguous data within a file that has meaningful common properties for preservation purposes. A bitstream cannot be transformed into a standalone file without the addition of file structure (headers, etc.) and/or reformatting the bitstream to comply with some particular file format. A representation is the set of files, including structural metadata, needed for a complete and reasonable rendition of an Intellectual Entity. For example, a journal article may be complete in one PDF file; this single file constitutes the representation. Another journal article may consist of one SGML file and two image files; these three files constitute the representation. A third article may be represented by one TIFF image for each of 12 pages plus an XML file of structural metadata showing the order of the pages; these 13 files constitute the representation. Files, bitstreams, and filestreams A file in the PREMIS data model is similar to the idea of a computer file in ordinary usage: a set of zero or more bytes known to an operating system. Files can be read, written, and copied. Files have names and formats. A bitstream as defined in the PREMIS data model is a set of bits embedded within a file. This differs from common usage, where a bitstream could in theory span more than one file. A good example of a file with embedded bitstreams is a TIFF file containing two images. According to the TIFF file format specification a TIFF file must contain a header containing some information about the file. It may then contain one or more images. In the PREMIS data model each of these images is a bitstream and can have properties such as identifiers, location, inhibitors, and detailed technical metadata (e.g., color space). Some bitstreams have the same properties as files and some do not. The image embedded within the TIFF file clearly has properties different from the file itself. However, in another example, three TIFF files could be aggregated within a larger tar file. In this case the three TIFF files are also embedded bitstreams, but they have all the properties of TIFF files. The PREMIS data model refines the definition of bitstream to include only an embedded bitstream that cannot be transformed into a standalone file without the addition of file structure (e.g., headers) or other reformatting to comply with some particular file format specification. Examples of these bitstreams include an image within a TIFF 6.0 file, audio data within a WAVE file, or graphics within a Microsoft Word file. Data Dictionary for Preservation Metadata: PREMIS version 2.0 7

15 INTRODUCTION Some embedded bitstreams can be transformed into standalone files without adding any additional information, although a transformation process such as decompression, decryption, or decoding may have to be performed on the bitstream in the extraction process. Examples of these bitstreams include a TIFF within a tar file, or an encoded EPS within an XML file. In the PREMIS data model these bitstreams are defined as filestreams, that is, true files embedded within larger files. Filestreams have all of the properties of files, while bitstreams do not. In the Data Dictionary, the column for File applies to both files and filestreams. The column for Bitstream applies to the subset of bitstreams that are not filestreams and that adhere to the stricter PREMIS definition of bitstream. The location (contentlocation in the Data Dictionary) of a file would normally be a location in storage; while the location of a filestream or bitstream would normally be the starting offset within the embedding file. Representations The goal of many preservation repositories is to maintain usable versions of intellectual entities over time. For an intellectual entity to be displayed, played, or otherwise made useable to a human, all of the files making up at least one version of that intellectual entity must be identified, stored, and maintained so that they can be assembled and rendered to a user at any given point. A representation is the set of files required to do this. PREMIS chose the term representation to avoid the term manifestation as it is used in the Functional Requirements for Bibliographic Records (FRBR). 6 In FRBR a manifestation entity is all the physical objects that bear the same characteristics in respect to both intellectual content and physical form. In the PREMIS model a representation is a single digital instance of an intellectual entity held in a preservation repository. A preservation repository might hold more than one representation for the same intellectual entity. For example, the repository might acquire a single image (say, Statue of a horse ) as a TIFF file. At some point the repository creates a derivative JPEG2000 file from the TIFF and keeps both files. Each of these files would constitute a representation of Statue of a horse. In a more complicated example, Statue of a horse might be a part of an article consisting of that TIFF image and a file of SGML-encoded text. If the repository created a JPEG2000 version of the TIFF, it would hold two representations of the article: the TIFF and the SGML files would make up one representation, while the JPEG2000 and the SGML files would make up another representation. How those representations are stored is implementation specific. A repository might chose to store a single copy of the SGML file, which would then be shared between representations. Alternately, the repository could choose to duplicate the SGML file and store two identical copies of it. The two representations would then consist of the TIFF and SGML copy 1, and the JPEG2000 and SGML copy 2. Not all preservation repositories will be concerned with representations. A repository might, for example, preserve file objects only and rely on external agents to assemble these objects into usable representations. If the repository does not manage representations, it does not need to record metadata about them. 8 Data Dictionary for Preservation Metadata: PREMIS version 2.0

16 INTRODUCTION Intellectual Entities and Objects The relationship between Intellectual Entities and Objects can be illustrated by a couple of examples: Example 1, Animal Antics: The book Animal Antics was published in A library digitized Animal Antics, creating one TIFF file for each of 189 pages. As structural metadata, it created an XML file showing how the images are assembled into a complete book. The library then performed OCR on the TIFF images, ultimately creating a single large text file that was marked up by hand in SGML. The library submitted 189 TIFF files, one XML file, and one SGML file to a preservation repository. To the repository Animal Antics is an Intellectual Entity: it is a reasonable unit that can be described as a whole, with properties such as an author, a title, and a publication date. The repository has two representations, one consisting of 189 TIFF files and an XML file, and the other consisting of one SGML file. Each representation could render a complete version of Animal Antics, albeit with different functionalities. The repository will record metadata about two representation objects and 191 file objects. Animal Antics (an intellectual entity) Representation 1 Representation 2 XML SGML TIFF 1 TIFF 189 Figure 2: Animal Antics Intellectual Entity Example Example 2, Welcome to U: Welcome to U, submitted to a preservation repository as an AVI (Audio Video Interleaved) file, is a 10-minute movie introducing new students to a university campus. Welcome to U is an Intellectual Entity. The repository has one representation, which consists of a single AVI file. The repository s preservation strategy requires that it manage the audio bits of the AVI file separately from the video bits. The repository will record metadata about one representation object, one file object, and two bitstream objects. Data Dictionary for Preservation Metadata: PREMIS version 2.0 9

17 INTRODUCTION More on Events The Event entity aggregates metadata about actions. A preservation repository will record events for many reasons. Documentation of actions that modify (that is, create a new version of) a digital object is critical to maintaining digital provenance, a key element of authenticity. Actions that create new relationships or alter existing relationships are important in explaining those relationships. Even actions that alter nothing, such as validity and integrity checks on objects, can be important to record for management purposes. For billing or reporting purposes some repositories may track actions such as requests for dissemination or reports. It is up to the repository which actions to record as Events. Some actions may be considered too trivial to record, or may be recorded in other systems (as, for example, routine file backups may be recorded in storage management systems). It is also an implementation decision whether to record events that occur before an object is ingested into the preservation repository, for example, derivation from an earlier object, or changes of custody. In theory, events following the deaccessioning of an Intellectual Entity could also be recorded. For example, a repository might first deaccession an Intellectual Entity, then delete all file Objects associated with that entity, and record each deletion as an Event. In the data model Objects are associated with Events in two ways. If an Object is related to a second Object through (because of) an Event, the Event identifier is recorded in the relationship container as the semantic component relatedeventidentification. If the Object simply has an associated Event with no relationship to a second Object, the Event identifier is recorded in the container linkingeventidentifier. (For more information on relationships, see page 13.) For example, assume a preservation repository ingests an XML file (object A) and creates a normalized version of it (object B) by running a program (event 1). In the metadata for object B, this could be recorded in relationship as follows: relationshiptype = derivation relationshipsubtype = derived from relatedobjectidentification relatedobjectidentifiertype = local relatedobjectidentifiervalue = A relatedobjectsequence = not applicable relatedeventidentification relatedeventidentifiertype = local relatedeventidentifiervalue = 1 relatedeventsequence = not applicable Continuing with this example, assume that after object B is created it is validated by running another program (event 2). In this case event 2 pertains only to object B, not to the relationship between B and A. The link to event 2 would be recorded as linkingeventidentifier: linkingeventidentifiertype = local linkingeventidentifiervalue = 2 10 Data Dictionary for Preservation Metadata: PREMIS version 2.0

18 INTRODUCTION A given Object can be associated in these two ways with any number of Events. All events have outcomes (success, failure, etc.). Some events also have outputs; for example, the execution of a program creates a new file object. The semantic units eventoutcome and eventoutcomedetail are intended for documenting qualitative outcomes. For example, if the event is an act of format validation, the value of eventoutcome might be a code indicating the object is fully valid. Alternatively, it might be a code indicating the object is not fully valid, and eventoutcomedetail could be used to describe all anomalies found. If the program performing the validation writes a log of warnings and error messages, a second instance of eventoutcomedetail could be used to store or point to that log. If an event creates objects that are stored in the repository, those objects should be described as entities with a complete set of applicable metadata and associated with the event by links. More on Agents Agents are clearly important but are not the focus of the Data Dictionary, which defines only a means to identify the agent and a classification of agent type (person, organization, or software). While more metadata is likely to be necessary, this is left to other initiatives to define. The data model diagram shows an arrow from the Agent entity to the Event entity, but no arrow from Agent to the Object entity. Agents influence Objects only indirectly through Events. Each Event can have one or more related Objects and one or more related Agents. Because a single Agent can perform different roles in different Events, the role of the Agent is a property of the Event entity, not of the Agent entity. More on Rights Many efforts are concerned with metadata related to intellectual property rights and permissions, from rights expression languages to the <indecs> framework. However, only a small body of work addresses rights and permissions specifically related to digital preservation. After the publication of the first edition of the PREMIS Data Dictionary, the Library of Congress in its capacity as PREMIS Maintenance Agency commissioned a paper, Rights in the PREMIS Data Model, by Karen Coyle 7. This paper discussed copyright, licenses, and statute as three bases for establishing intellectual property rights, and recommended an expansion of the rights information in the Data Dictionary to include information on these bases. Consequently, the permissionstatement in the original Data Dictionary was replaced with the rightsstatement in this version. In this revision the Editorial Committee relied heavily upon the Coyle paper, background materials such as Peter Hirtle's excellent Digital Preservation and Copyright, 8 and the California Digital Library's draft copyrightmd schema 9. It should be noted that the proposed uses of copyrightmd and PREMIS rights are rather different. The copyrightmd schema is intended to document factual information to allow a human being to make an informed copyright assessment of a given work. The PREMIS rightsstatement is intended to allow a preservation repository to determine whether it has the right to perform a certain action in an automated fashion, with some documentation of the basis for the assertion. Data Dictionary for Preservation Metadata: PREMIS version

19 INTRODUCTION General Topics on the Structure and Use of the Data Dictionary The semantic units defined in the PREMIS Data Dictionary are bound together by a few structural conventions that help organize the Data Dictionary and support its implementation. These conventions include the use of identifiers; the manner in which relationships are handled in the Data Dictionary; and the 1:1 Principle relating metadata to Objects. Identifiers Instances of Objects, Events, Agents, and Rights statements are uniquely identified by a set of semantic units collected under Identifier containers. These semantic units follow an identical syntax and structure, regardless of entity type: [entity type]identifier [entity type]identifiertype: domain in which the identifier is unique [entity type]identifiervalue: identifier string The following examples illustrate the use of this syntax to identify an Object residing in Harvard s Digital Repository Service (DRS), and an event that occurs under the auspices of the NRS (Name Resolution Service): Example 1: Identifying an Object ObjectIdentifier ObjectIdentifierType: NRS ObjectIdentifierValue: Example 2: Identifying an Event EventIdentifier EventIdentifierType: NRS EventIdentifierValue: In both examples, the identifier type is NRS, which indicates that the identifier is unique within the domain of the Name Resolution Service that assigns identifiers for the Digital Repository Service. Identifier type should be defined as specifically as possible, and provide sufficient information to indicate the relevant naming authority, as well as how to build the identifier value. For example, it would have been permissible to use URL for ObjectIdentifierType in the first example, since the identifier value is unique in that domain, but NRS conveys more information about the domain in which the identifier is created and used. If all identifiers are local to repository system, it is unlikely that identifier type would need to be explicitly recorded for each identifier in the system. This is an example of a semantic unit whose information is known implicitly by context or policy, and is therefore not implemented as a metadata element in the preservation system. However, if the repository exchanges digital objects and their associated metadata with other repositories, identifier type should be explicitly supplied. 12 Data Dictionary for Preservation Metadata: PREMIS version 2.0

20 INTRODUCTION Identifiers can be created internally or externally to the repository. The PREMIS Data Dictionary does not require or even recommend a specific identifier scheme; this is an implementationspecific issue and is therefore outside the scope of the Data Dictionary. The Data Dictionary simply provides a general syntax that can be used to express identifier type and value, regardless of the specific scheme chosen. It is recommended, however, that repositories choose persistent identification schemes wherever possible. Identifiers are repeatable for Objects and Agents; they are not repeatable for Rights and Events. Objects and Agents often have multiple identities in a global environment, and across systems, and therefore are likely to have multiple identifiers. Rights and Events are considered to have a context limited to a particular preservation repository, and therefore do not require multiple identifiers. Identifiers are used as references to establish relationships between entities in the PREMIS data model. Relationships are discussed in the next section. Relationships between Objects As noted earlier, an Object in a repository can be related to one or more other Objects in the repository. The PREMIS Data Dictionary supplies semantic units to support documentation of relationships between Objects. The working group began its exploration of this topic by collecting examples from existing preservation metadata projects. It found a wide range of metadata facts expressed as relationships for example, is migrated from, is keyed text of, is thumbnail of. In some cases these relationship statements combine more than one fact (e.g., is keyed text of combines is a keyed text and is derived from ). The group also reviewed the element refinements for the Dublin Core Relation element (IsPartOf, IsFormatOf, IsVersionOf, etc.) and concluded that most relationships among objects appear to be variants of these three basic types: structural, derivation, and dependency. Structural relationships show relationships between parts of objects. The structural relationships between the files that constitute a representation of an Intellectual Entity are clearly essential preservation metadata. If a preservation repository can t put the pieces of a digital object back together, it hasn t preserved the object. For a simple digital object (e.g., a photograph) structural information is minimal: the file constitutes the representation. Other digital objects such as e-books and Web sites can have quite complex structural relationships. Derivation relationships result from the replication or transformation of an Object. The intellectual content of the resulting Object is the same, but the Object s instantiation, and possibly its format, are different. When file A of format X is migrated to create file B of format Y, a derivation relationship exists between A and B. Many digital objects are complex, and both structural and derivation information can change over time as a result of preservation activities. For example, a digitized book represented by 400 TIFF page images might after migration become four PDF files each containing 100 pages. A structural relationship among objects can be established by an act of derivation before the objects were ingested by the repository. For example, a word-processing document could have Data Dictionary for Preservation Metadata: PREMIS version

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