Transforming Library Metadata into Linked Library Data

Introduction and Review of Linked Data for the Library Community, 2003–2011

By Virginia Schilling

Introduction

Libraries and other cultural institutions are experiencing a time of huge, tumultuous change. Standards that have been in use for decades have come under increasing pressure to either adapt to new circumstances or to give way entirely to different standards. While it is clear that change is happening, what is less clear is where that change is taking us. If MARC and AACR2 no longer serve us, then what standards will serve? How can we adapt to fundamental differences in how our data is used without rendering decades of legacy data completely worthless? We stand in a moment of uncomfortable chaos. We must forge a new path, but where that path might lead, or even what it looks like, is still unclear.

While some do not believe, perhaps, that any sort of change is necessary at all, Coyle points out that library data, despite being saved and accessed via computers, is designed for the use and consumption of humans (2010b, 6). The 2008 report of The Library of Congress Working Group on the Future of Bibliographic Control observes that “people are not the only users of the data we produce in the name of bibliographic control... so too are machine applications that interact with those data in a variety of ways” (2). Unfortunately, as stated in the Library Linked Data Incubator Group Final Report, library data is not integrated with the Web, much of it is encoded in natural language rather than as data, library standards serve only the library community and no other, and changes in library technology are often completely dependent on the expertise of vendors (Baker, et al. 2011, sec. 3.1). One possible path forward is provided by the standards established by the World Wide Web Consortium (W3C) to build the Semantic Web. Linked data, in particular, is an implementation of these standards that seems to fit well with the legacy metadata produced and maintained by libraries and other cultural institutions.

This essay attempts to provide an overview of the current state of the discussion about linked data as well as provide a solid introduction for practitioners who wish to get involved in the conversation themselves. It draws from a range of sources published between 2003 and 2011 and is organized in five sections: An Overview of Library Metadata, An Overview of Linked Data, The Convergence of Linked Data and Library Metadata, Problems with Linked Data, and Looking to the Future of Linked Library Data.

An Overview of Library Metadata

This discussion starts with a look at our existing library standards and the types of metadata currently in use by libraries and other cultural institutions. Zeng and Qin (2008, 15) define four kinds of metadata standards used in the library profession. Standards for data:

structures like the Dublin Core Metadata Element Set (DCMES)
content like the Anglo-American Cataloging Rules, Second Edition (AACR2)
values like the Library of Congress Subject Headings (LCSH)
exchange like the MARC 21 Format for Bibliographic Data (MARC 21).

Caplan (2003) notes that data structure standards “will normally specify the metadata elements that are included in the scheme by giving each of them a name and a definition” (6). In addition to DCMES, Zeng and Qin discuss other commonly used data structure standards such as VRA Core (39–41), Categories for the Description of Works of Art (CDWA) (32–36), and Encoded Archival Description (EAD) (53–59).

Content standards “specify how values for metadata elements are selected and represented” (Caplan 2003, 6). Caplan traces a brief historical overview of library cataloging standards, starting with Panizzi and finishing with AACR2 and the International Standard Bibliographic Description (ISBD) specification developed by the International Federation of Library Associations and Institutions (IFLA) (54–55). Additionally, Zeng and Qin discuss Describing Archives: A Content Standard (DACS) (59) and Cataloging Cultural Objects: A Guide to Describing Cultural Works and Their Images (CCO) (36).

Zeng and Qin note that data value standards “include controlled term lists, classification schemes, thesauri, authority files, and lists of subject headings” (15). In addition to LCSH, Caplan touches on The Art & Architecture Thesaurus (AAT) (25) and Zeng and Qin discuss The Thesaurus of Graphic Materials (TGM) and Iconclass (42), and the Thesaurus of Geographical Names (TGN) (107–8).

Finally, the data exchange standards are the linchpin of modern library cataloging standards. These allow libraries to exchange metadata reliably and coherently. Standards like MARC 21 mean that a library sending data can always assure that the title element will always contain title information for the library receiving data. Furrie (2009) describes how MARC accomplishes this. “The information from a catalog card cannot simply be typed into a computer to produce an automated catalog. The computer needs a means of interpreting the information found on a cataloging record. The MARC record contains a guide to its data, or little ‘signposts,’ before each piece of bibliographic information (under Part II).”

“MARC... was developed by the Library of Congress (LC) in the mid-1960s, primarily to enable the computer production of catalog cards that could subsequently be distributed through the Cataloging Distribution Service” (Caplan 2003, 12). Zeng and Qin describe one difficulty of continuing to use MARC: integrating MARC and non-MARC data. “To integrate [Dublin Core] records into a MARC-based database, it is necessary to convert [Dublin Core] records into MARC records, and they must be stored, indexed, and exchanged with this format” (25). Coyle (2010b) discusses the use of MARC to exchange bibliographic records created using Resource Description and Access (RDA). “The MARC21 community is investigating to what extent RDA can be expressed in that existing format, but it seems clear that the full flexibility and extensibility of RDA goes beyond what can be done in a record format that is already experiencing difficulties in keeping up with needed changes” (32).

An alternative exchange format is Extensible Markup Language (XML). Caplan describes XML as a “subset” of Standard Generalized Markup Language (SGML) that is “easier to process” (19). SGML “was designed to handle variable-length textual data gracefully. An unlimited number of elements... can be defined, and their names can be descriptive of their contents” (18). She continues, “SGML is inherently hierarchical and can enforce the rules of hierarchy, making it a perfect medium for expressing the types of hierarchical relationships found within collections and among works, expressions, manifestations, and items” (18). Zeng and Qin note MARC’s “inflexible output process” as one of several of its limitations and state that “in contrast, XML-based processing can easily produce different output forms” (25). They also observe that EAD (53–54), Guidelines for ONline Information eXchange (ONIX) (69), and CDWA Lite (36–38) all use XML to exchange data between systems.

In addition to metadata standards, the metadata itself falls generally into three categories: descriptive, administrative and structural (NISO 2004, 1). “Traditional library cataloging viewed as metadata is primarily descriptive” (Caplan, 4). Zeng and Qin, however, note that digital resources are more complex and require more than traditional description.

The purposes of pre-Internet cataloging were twofold: (1) to provide rich bibliographic descriptions and relationships between and among data of heterogeneous items and (2) to facilitate sharing these bibliographic data across library boundaries. While AACR2 and MARC have done a meritorious job in accomplishing those purposes, they fall short on several important fronts in Internet-based resource descriptions, e.g., management of digital rights, preservation of digital objects, and evaluation of resources based on authenticity, user profile, and grade level. (6)

NISO defines administrative metadata as “information to help manage a resource, such as when and how it was created, file type and other technical information, and who can access it” (1). Administrative metadata can also be subdivided into technical metadata (file characteristics), rights management metadata (intellectual property rights), and preservation metadata (preservation of the resource) (Caplan, 5). Structural metadata “indicates how compound objects are put together” (NISO, 1). Caplan characterizes structural metadata as “required to record the relationships between physical files and pages, between pages and chapters, and between chapters and the book as a whole” (5).

These standards and metadata types work together, sometimes inextricably, to form the basis for modern library cataloging and the description of cultural objects. Hillmann and Westbrooks (2004) profile a variety of real-world implementations of metadata standards and types. In an introductory essay for a special issue of Cataloging and Classification Quarterly, Smiraglia (2005) provides a general introduction to metadata and, finally, Wolfe and Lubas (2004) offer a basic slideshow introduction to metadata.

An Overview of Linked Data

Understanding linked data starts with a basic review of the applicable W3C Semantic Web standards. Most importantly, the Resource Description Framework (RDF) provides a theoretical model for understanding relationships between “things.” Manola and Miller (2004) state,

the Resource Description Framework (RDF) is a language for representing information about resources in the World Wide Web. It is particularly intended for representing metadata about Web resources, such as the title, author, and modification date of a Web page, copyright and licensing information about a Web document, or the availability schedule for some shared resource. However, by generalizing the concept of a “Web resource,” RDF can also be used to represent information about things that can be identified on the Web, even when they cannot be directly retrieved on the Web. (sec. 1)

While RDF underpins the whole Semantic Web ecosystem, a host of other technologies also contribute. Riley (2010) notes that while “libraries have ‘records’”, “RDF has ‘statements’ and ‘graphs’” (slides 4-5). “SPARQL [an RDF Query Language] can be used to express queries across diverse data sources, whether the data is stored natively as RDF or viewed as RDF via middleware” (Prud'hommeaux and Seaborne 2008, under “Abstract”). RDF Schema (RDFS) “is a semantic extension... of RDF. It provides mechanisms for describing groups of related resources and the relationships between these resources” (Brickley and Guha 2004, sec. 1).

Web Ontology Language (OWL) “is designed to facilitate ontology development and sharing via the Web, with the ultimate goal of making Web content more accessible to machines” (W3C OWL Working Group 2009, sec. 1). Finally, Simple Knowledge Organization System (SKOS) “aims to provide a bridge between different communities of practice within the library and information sciences involved in the design and application of knowledge organization systems. In addition, SKOS aims to provide a bridge between these communities and the Semantic Web, by transferring existing models of knowledge organization to the Semantic Web technology context, and by providing a low-cost migration path for porting existing knowledge organization systems to RDF” (Miles and Bechhofer 2009, sec. 1.1).

Linked data is simply one practical application of these technologies to real-world data. Berners-Lee (2009) defines his four principles of linked data.

Use URIs as names for things
Use HTTP URIs so that people can look up those names
When someone looks up a URI, provide useful information, using the standards (RDF*, SPARQL)
Include links to other URIs so that they can discover more things. (under “Introduction”)

Heath and Bizer (2011) examine the principles of linked data in detail. Beginning with the first principle, they note that it advocates using URIs to identify not only Web pages, but also objects in the real world, as well as abstract concepts (sec. 2.1). The HTTP URIs required by the second principle allow anyone with a domain name to create URI references (sec. 2.2). The third principle indicates that when someone looks up an existing URI, it should retrieve a description of the resource to which it has been assigned (sec. 2.3). Finally, they discuss the importance of Berners-Lee’s fourth principle of linking to other URIs. They define three types of links (relationship links, identity links and vocabulary links) and state that “such external RDF links are fundamental for the Web of Data as they are the glue that connects data islands into a global, interconnected data space and as they enable applications to discover additional data sources in a follow-your-nose fashion” (sec. 2.5).

Heath and Bizer also present an argument for the adoption of linked data for data presentation on the Web. They state, “Linked data provides a more generic, more flexible publishing paradigm which makes it easier for data consumers to discover and integrate data from large numbers of data sources” and furthermore, they note specifically that linked data provides a unifying data model (RDF), a standardized data access mechanism (HTTP), hyperlink-based data discovery (URIs) and self-descriptive data (vocabulary links) (sec. 2.6).

Dodds and Davis (2011) provide “a pattern catalogue that covers a range of different areas from the design of web scale identifiers through to application development patterns” (under “Introduction”). In a series of five slideshow presentations, Sequeda offers an introduction to linked data (2011a), primers on creating (2011b), publishing (2011c) and consuming (2011d) linked data and finishes by reiterating that “Linked data is a set of best practices for publishing data on the Web” (2011e, slide 2). Raimond and Smethurst (2009) give a more technical introduction to linked data, noting that “everything that's good about the web comes from links” (slide 17). Finally, Linked Data: Connect distributed data across the Web (n.d.), which is on the linkeddata.org website, and the LinkedData wiki (2011) also provide links to additional materials relating to linked data and the Semantic Web.

The Convergence of Linked Data and Library Metadata

Heery (2004) discusses the similarities between linked data and traditional library metadata.

What is perhaps the most striking aspect of the Semantic Web for the library community is the commonality between traditional information management and library interests (constructing vocabularies, describing properties of resources, identifying resources, exchanging and aggregating metadata) and the concerns that are driving the development of Semantic Web technologies. (270)

The difference between them lies in making the implicit relationships found in traditional library metadata, which are obvious to humans, explicit for machine understanding as well. Baker et al. note that the first step is to take our human-understandable, controlled strings of text and link them to unique, persistent identifiers. “Library data cannot be used in a linked data environment without having Uniform Resource Identifiers (URIs) both for specific resources and for library-standard concepts” (sec. 4.3.2). The Library of Congress has begun this process with the development of RDF presentations of its various authorities and vocabularies. Subject headings, names, genre terms, country codes, languages and more have been given URIs (Authorities and Vocabularies n.d., under “Search Authorities & Vocabularies”). As discussed by Coyle (2010b, 26-36), work on defining the data structure elements and various value vocabularies described by RDA in the Open Metadata Registry (formerly the NSDL Registry) has also begun.

Currently the metadata that is generated by the library profession exists in databases that “are made available on the Web only as dynamically formatted pages in response to search requests” (Caplan, 48). Unfortunately “search engines are increasingly becoming the first gate that users approach when searching for any information” (Zeng and Qin, 233) and search engines do not index these “dynamically formatted” pages. Coyle (2010b) notes that “this means that library data cannot participate in the highly linked and linkable information environment on the Web, and this limits the visibility of libraries to Web users” (9). In other words, library metadata simply does not show up in the search results presented to users by search engines.

Baker et al. note, on the other hand, that “Linked data is... about enhancing the Web through the addition of structured data. This structured data... plays a role in the crawling and relevancy algorithms of search engines and social networks, and will provide a way for libraries to enhance their visibility through search engine optimization (SEO)” (sec. 2.1). Exposing library metadata as linked data would mean it could be crawled by the search engine bots and included in the search results presented to users along with articles from Wikipedia and the Internet Movie Database (IMDB).

Beyond the basic search results available from Web browser searches, Bourg (June 24, 2010) muses in a blog post that linked data has the potential to allow serendipity in online searching that does not currently exist. Users cannot search for unknown information or resources. “The scholarly value of serendipity usually comes up in discussions of browsing, and in calls for maintaining large, open, physical collections of library materials.” Coyle notes that “offline, we rely on a web of human connections to help us find information. Online, that web consists of links between resources and rich social interaction.... The library catalog, however, offers little beyond search and retrieve” (2010b, 9). With linked data, searching for the known can become browsing for serendipitous discovery of the unknown simply by following links from one data set to the next.

Linked data builds on the defining feature of the Web: browsable links (URIs) spanning a seamless information space. Just as the totality of Web pages and websites is available as a whole to users and applications, the totality of datasets using RDF and URIs presents itself as a global information graph that users and applications can seamlessly browse by resolving trails of URI links…. The value of linked data for library users derives from these basic navigation principles. Links between libraries and non-library services such as Wikipedia, Geonames, and Musicbrainz will connect local collections into the larger universe of information on the Web. (Baker et al., sec. 2.1)

Coyle (2010a) further explores the idea that current data in Web resources are implicitly linked by human understanding of them, but are not explicitly linked for machine understanding. “You can't … move easily from a statement in an essay about Abraham Lincoln to a list of books about Lincoln, much less a list of relevant books in your local library (let alone a list of resources that are on the shelf and currently available)” (12). By publishing such information as linked data, the explicit connections necessary for the computer will have been added.

The intersection of library metadata and linked data has also resulted in the emergence of domain-applicable tools and real-world implementation of library linked data. The Library Linked Data Community Wiki (2011) provides links to some resources including Linked Library Data events and glossaries of library and Semantic Web terminologies. Byrne and Goddard (2010) include an appendix of Semantic Web tools for libraries, including tools to convert various metadata schemes into RDF, tools for publishing RDF (not necessarily domain-specific), and several projects actively using linked data. Isaac et al. (2011) present an extensive description of library linked data resources divided into three categories: published datasets, value vocabularies (such as LCSH) and metadata element sets (such as RDA or Dublin Core). Vila Suero (2011) details use cases and case studies of library linked data clustered by bibliographic data, authority data, vocabulary alignment, archives and heterogeneous data, citations, digital objects, collections, and social and new uses.

Problems with Linked Data

The problems with implementing linked data at this point in time are myriad. Baker et al. note that the practical focus thus far has been on the generation of linked data ontologies and value vocabularies. “Many metadata element sets and value vocabularies have been published as linked data over the past few years” but “relatively few bibliographic datasets have been made available” (sec. 3.2). Bowen (2010) discusses the need for fundamental changes in how bibliographic data is stored in order to realize the true potential of linked data.

Libraries are tied to MARC-based systems that do not yet facilitate the creation of linked data. Without a body of library data converted to linked data, software developers have little incentive to create new applications that require it. And without a significant number of applications that take advantage of linked data, vendors of current systems have little incentive to implement linked data in a legacy environment. (56)

Bowen also touches on the need to develop tools just for the process of transitioning our existing legacy data to linked data. While describing some of the issues encountered in transitioning MARC data into the eXtenstible Catalog (XC) schema, she concludes that “converting legacy metadata to linked data will require a team of experts, including MARC-based catalogers, specialists in other metadata schemas, software developers, and Semantic Web experts to design and test normalization/conversion algorithms, develop new schemas, and prepare individual records for automated conversion” (57). Finally, Guenther (2004) and Zeng and Qin (2008) both present arguments for using XML to transition out of MARC and into other standards. Zeng and Qin advocate the usage of MARCXML to transition MARC records into XML (24–27). Guenther notes that “XML allows for an easy path for converting existing records and flexibility in display and further transformations” (slide 38).

Moving past the practical concerns, other conceptual problems include establishing the reliability of linked data, copyright and intellectual property issues pertaining to the data being published, and privacy considerations. Hannemann and Kett (2010) ask “is the data correct and do processes exist that guarantee a high data quality? Who is responsible for it? Of the same importance is reliability in time: Is a resource stable enough to be citable, or will it be gone at some point?” (2). Closely related to establishing the reliability of others’ linked data is the problem of providing information about the authenticity and accuracy of one’s own data. “Provenance of data provides useful information such as timeliness and authorship of data. It can be used as a ground basis for various applications and use cases such as identifying trust values for pages or pages fragments.... Moreover, providing provenance meta-data as RDF and making it available on the Web of Data, offers more interchange possibilities and transparency” (Orlandi and Passant 2011, 149).

Publishing linked data also raises questions about ownership and copyright. Byrne and Goddard point to one problem by noting that libraries license much of the content they provide to users and that “a mix of licensed and free content in a linked data environment would be extremely difficult to manage” (under “What are the major obstacles for libraries?”). Baker et al., on the other hand, note that ownership of the metadata itself can be extremely complicated. “Records are frequently copied and the copies are modified or enhanced for use by local catalogers. These records may be subsequently re-aggregated into the catalogs of regional, national, and international consortia” (sec. 3.3.1). They add that “larger agencies are likely to treat records as assets in their business plans and may be reluctant to publish them as Linked Open Data” (sec. 3.3.2).

Also at issue is privacy. “Threats to personal privacy will also increase as boundaries blur between personal information published intentionally, that published conditionally (for example, to specific social networking sites for a specific audience) and information over which the subject has no control” (O'Hara and Shadbolt 2010, 39). Byrne and Goddard agree, noting that “librarians, with their long tradition of protecting the privacy of patrons, will have to take an active role in linked data development to ensure rights are protected” (under “What are the major obstacles for libraries?”).

Finally, Ding et al. (2011) consider the problems with provenance in detail. Hartig and Langegger (2010) approach linked data and its challenges from the perspective of the database community, while Grant (August 14, 2011) in a blog post touches on the challenges for vendors from the vendors’ perspective. Auer and Lehmann (2010) also examine the challenges linked data needs to overcome, including lowering the barriers to entry, and a blog post by Bradley (February 14, 2011) reflects on the concepts of proof and trust in the context of the Semantic Web. Sauermann and Cyganiak (2008) discuss the problems inherent in trying to represent both real-world objects and web pages using URIs.

Looking to the Future of Linked Library Data

Byrne and Goddard state that while linked data “has a long way to go before it is seen as a standard foundation for library data...the majority of issues are non-technical in nature. The technology is ready; it is now a matter of getting libraries and librarians ready as well” (under “What are the major obstacles for libraries?”). Coyle (2010b) advocates for libraries and other cultural institutions as a whole to continue to model and build ontologies with a focus on the structural metadata. “One of the first steps that needs to be taken is to tease out the many components that are encompassed by the RDA text” (9). Sequeda (2011e) offers specific topics for further research: search and ranking, interlinking algorithms, provenance, trust and privacy, dataset dynamics, user interfaces, distributed queries, and evaluation (slide 12).

Byrne and Goddard offer some specific ideas for libraries to get involved in the development of linked data. Quoting Miller (2004, slide 26), they define four roles for libraries: exposing collections via Semantic Web technologies, webifying thesaurus/mappings/services, sharing lessons learned, and advocating for change (under “How can libraries get involved?”). First, Byrne and Goddard note that there is no reason not to experiment with publishing linked data for “small standalone collections” to develop “expertise and technologies within libraries” (under “Exposing collections”). Secondly, they encourage libraries to become involved in current efforts to develop library-related ontologies and value vocabularies. “Supporting and contributing to the efforts underway such as those of the DCMI, as well as web'ifying locally maintained controlled vocabulary is a natural fit for the profession” (under “Web'ifying thesaurus/mappings/services”). Thirdly, they call on librarians to become involved with the linked data community outside of libraries. “Sharing is something that comes naturally to the library community, but... librarians must [also] engage with—and contribute to—wider linked-data-community efforts. The semantic web is about breaking down silos, not building better ones” (under “Sharing Lessons Learned”). Lastly, they urge librarians to advocate for linked data with their own vendors. “Librarians must demand that vendors develop their own data semantically” (under “Persistence”).

Baker et al. recommend additionally that libraries play a key role in the preservation of linked data, both the vocabularies and the published data sets. They note that “Linked data will remain usable twenty years from now only if its URIs persist and can resolve to documentation of their meaning” (sec. 4.4.1). Because of libraries' experience with and commitment to data quality and long-term data maintenance, Baker et al. see an opportunity for libraries to take on the role of curating linked data as an extension of their current functions (sec. 4.4.2).

Conclusion

This has been a simple discussion of a complex topic and barely touches on issues that are debated extensively on blogs, electronic mailing lists, and other Web venues. This is also an area where the status quo can change on a daily basis as new ideas are presented and considered, new tools deployed, and previous predictions disproved.

At this time, efforts to implement Semantic Web and linked data technologies in libraries and other cultural institutions are still in their infancy. We are still establishing the building blocks such as ontologies and value vocabularies, defining the requirements and the constraints for their use and, most importantly, have only just begun building the tools themselves that will become fundamental for libraries to both consume and produce linked data. The barriers to implementation for the average library are still very high. Byrne and Goddard acknowledge this, stating that, “particularly when compared to web 2.0 applications, linked data can seem rather inaccessible; anyone can create a Twitter account or promote user tagging or even contribute to mashups, but the world of linked data, for the moment, remains firmly in the hands of the experts” (under “What are the major obstacles for libraries?”). It is for this reason, Baker et al. recommend that libraries “take an incremental approach to making data available for use on the Web” by starting with “high-priority, low-effort linked data projects” such as authority files and controlled term lists (sec. 4.1.1).

Finally, despite the complexity, frustration, and general chaos involved in transitioning to a newer technology like linked data, it should be recognized that there really may be no choice in the matter. “The participation of digital resource creators and that of the general public in producing and organizing digital information objects has effectively ended the era of librarians' or information professionals' dominance in this field. Metadata creation has become more distributed, participatory, and diversified in methods, practices, and tools” (Zeng and Qin, 297). Libraries can either participate in the larger metadata community via technologies like linked data and the Semantic Web or they can be pushed aside and ignored. This larger community will continue to move forward and farther away from “traditional” library technologies and practices regardless of whether the library profession decides to participate in the process. This then is the challenge currently presented to us: Evolving along with the larger community brings with it all of the hazards inherent in change. Ignoring the transformation taking place risks rendering the data we have assembled so carefully and laboriously over so many years unusable for anyone outside of the library profession.

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