The RDF Model for Application Graphs

RDF provides a machine-readable framework for specifying — in digital library terminology, metadata. This metadata can be used to organize and manage information.

An RDF statement is an arc with a subject that denotes a resource, a predicate that describes characteristics of the resource, and an object, which can be either a URI or a literal value.

The Graph Model

When you design your application graph model, you want it to be expressive of your domain and easy to query on behalf of your most important use cases. You also want to make it easy to evolve the model and queries on a case-by-case basis, as new use cases emerge and your knowledge of the domain grows.

A central component of this goal is ensuring that your application graph data model reflects the underlying semantics and structures of your queries. Generally, this involves using graph primitives – vertices, labels and properties in the case of a property graph and subject-predicate-object triples in the case of RDF – to represent the graph patterns expressed in your queries.

This often results in a hub-and-spoke structure, where a central vertex representing a fact or event is connected to several neighbouring vertices that provide context about that fact or event. For example, a Purchase hub vertex would be connected to the User who made the purchase and the several Product items purchased.

The Semantic Model

The goal of a semantic model is to capture meaning and relationships within a data structure. This contrasts with a traditional data model that is based upon tables, rows and columns.

In a business context, a semantic layer acts as a map between an organization’s current data and the future data it wants to handle. Typically, the semantic layer enables users to use a common business language to answer questions and solve problems.

Semantic models can be very simple or complex, depending on the needs of an organization and its users. For example, a basic online thesaurus portal can simply organize synonyms and related terms into groups.

A more advanced semantic model can also connect classes and their properties to form an ontology. This can then be used to identify and manage relationships between objects. For example, an ontology could be used to automatically link a staff member’s age and date of birth to their occupation, thereby helping recruitment teams to identify relevant applicants and hire the right people.

The Data Model

The RDF data model is based on a simple, flexible, and extensible information architecture. It defines a syntax (RDF XML) that is used to store and communicate metadata, and it imposes structural constraints on XML to support the consistent representation of semantics.

Its basic structure is a directed graph of triples. Each triple consists of a subject, a predicate, and an object. The subjects are identified by a Uniform Resource Identifier (URI), the predicates by a property-type definition, and the objects by literal values.

The data model also provides for a mechanism to restrict the meaning of a literal, enabling it to be used for different purposes in different domains. It also supports the use of a number of existing human-readable and machine-readable vocabularies, to allow metadata to be defined in multiple languages. It also introduces a set of statement-level annotations, which are more efficient than traditional key-value pairs and enable the representation of recurrent events, data provenance, and other attribute-rich data.

The Usage Model

RDF has a special syntax that describes data graphs, much like the XML syntax. It is a labeled-directed graph, which means that each node has some type of label and arcs only go in one direction. The identifiers used to refer to each item of metadata in the graph are called uniform resource identifiers (URI).

A Resource in an RDF model is described by three pieces of information, called a triple: a subject, a predicate and an object. The subject is what the description is about, the predicate describes characteristics of the subject, and the object is what it relates to.

An RDF description of a person may include a person’s age and birthday. This is because of the use of a standard vocabulary for the description of people and their relationships, which is defined by a community of people who want to describe such metadata.

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What is RDF Data?

RDF provides a framework for specifying–in digital library terminology, metadata–that makes information machine-readable. It is based on a graph with subjects, predicates and objects.

The basic statement has a subject in the form of a Uniform Resource Identifier (URI), and an object that can be either a URI or a literal value. Together these are known as a triple.

What is RDF?

RDF enables information to be described in a machine-readable way that software can interpret. It is the basis of technologies such as SPARQL, RDF Schema (RDFS), SKOS, and Web Ontology Languages (OWL).

It describes resources in a way that is unambiguous to software working with it. It does so by describing relationships between subjects, predicates and objects. Each subject, predicate and object is expressed by a triple (subject, attribute, value) that can be mapped to a data structure like XML.

For example, a triple may say that a book has a title and three authors. An XML file representing this description might look something like Figure 6.5. But the XML can be converted into an RDF graph that can then be used by software to perform queries over it. It is this ability to use RDF to describe information that enables the Semantic Web and Linked Data. It is the reason that RDF is often used as a metadata framework for the Web.

RDF Data Model

An RDF statement (also known as a triple) is a labeled, directed graph. An arc between two nodes in the graph represents a relationship between those two things. The nodes represent subjects or objects, and the arrows represent properties (sometimes called predicates).

Each object can be identified by one of three types of identifier: a Uniform Resource Identifier (URI), a literal value, or a blank node. The URIs used in RDF can be resolvable with a standard web protocol, and they may contain characters from any of the world’s languages.

The RDF model is so flexible and simple that it has led to its use in applications unrelated to the Semantic Web activities of the W3C. In particular, it makes it easy to combine information from different sources with a single syntax like Turtle or N-Triples. RDF also supports a variety of ways to store and retrieve information in a database, including the popular triplestores such as Ontotext’s GraphDB.

RDF Schema

In RDF, relationships between data are represented as triples – subjects, predicates and objects. A subject is a URI, a predicate is an RDF property and the object is a resource. The triples can be combined to form graphs, which provide the basis for a basic level of inference.

The semantics of the relationships are provided by the RDF Schema. There are also more sophisticated levels of inference available, using richer languages such as OWL [OWL2-OVERVIEW] and inference rules.

The class of a resource is defined in RDF by its rdfs:Class property. A class has a set, called its class extension, which is the set of all the instances of the class. A resource can be a member of more than one class, and the relationship between classes is expressed using the rdfs:subClassOf and rdfs:superClassOf properties. In addition, RDF has container types: rdf:Bag may contain duplicate values; rdf:Seq is an ordered list; and rdf:Alternative can be used to represent a set of alternatives.

RDF Data Formats

One of the more important and popular W3C standards, RDF is a data format for machine-readable, contextually and semantically rich information. It is used as the foundation for Linked Open Data and provides the building blocks for a web of data that can be interconnected across all platforms, languages and applications.

RDF has features that make it easy to merge datasets even if their underlying schemas differ, and supports the evolution of schemas over time without requiring all the data consumers to change (another powerful feature for today’s fast-changing world). RDF is also an extremely robust data representation’staging’ format, able to support different syntaxes.

The RDF format is based on the XML language and uses URIs to identify resources, property types and values. The syntax for describing RDF is called Turtle and is illustrated in the following example. This demonstrates how a sequence of RDF statements can be arranged to form a graph. Note that this is a simplified version; in real-life you would typically use RDF containers to specify the grouping of multiple items such as fly:list> in Example 10-2 and fly:list id=”haematobia_irritans”> in Example 10-3. These are then joined together using a SELECT query.

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RDA: Resource Description and Access is a new cataloging standard designed to replace the Anglo-American Cataloguing Rules, 2nd Revised (AACR2). It provides instructions and guidelines on formulating bibliographic metadata.

It uses the FRBR and FRAD models as its basis. It also includes a set of vocabularies for content, carrier type and main or added access points.

Definition

Resource Description and Access (RDA) is a new set of rules developed to replace the Anglo-American Cataloguing Rules 2 (AACR2). RDA was designed specifically for the digital world and is being built on foundations established by Functional Requirements for Bibliographic Records and Functional Requirements for Authority Data, two publications that were developed through the International Federation of Library Associations (IFLA).

The development of RDA aims to make libraries more relevant to users in the digital world. While the JSC presents it as a change that will position libraries for the future, its prospects are limited by its fealty to existing metadata surrogates and its adherence to an entity-relationship model that dates back to the 1960s.

The RDA structure, which is closely aligned with the entities and relationships of databases, provides a more flexible framework for describing resources (analog and digital) that are adaptable to new and emerging database structures, and that is compatible with existing records in online library catalogs. The system also provides a more meaningful basis for linking metadata, and makes use of the concept of core elements.

Purpose

When libraries reproduced printed materials in different formats they had to catalog each iteration separately. Eventually, this led to the proliferation of catalog entries for what were essentially the same resources. This was inefficient and drained staff resources.

A new set of rules was needed. Rather than revising AACR2, the Joint Steering Committee for Revision of AACR (JSC) decided to create a completely new standard that would be designed for the digital environment. It was named RDA: Resource Description and Access.

RDA is structured according to internationally established principles, models and standards. The metadata created using the RDA instructions is well formed according to these international standards and can be used in any coding schema including existing records in online library catalogs as well as new and emerging database structures.

The new code is more efficient in its use of cataloging space than AACR2. It also addresses the issues of changing formats and enables libraries to move into the world of linked data.

Formats

Resource Description and Access is a new cataloging standard designed for the digital world. It was developed to replace AACR2 and is the basis for the metadata that will be created for online library catalogues, bibliographic databases, and other user-focused linked data applications. RDA is based on the Functional Requirements for Bibliographic Records (FRBR) conceptual model and provides instructions, guidelines and a vocabulary for formulating bibliographic metadata in order to present information about resources in ways that are more relevant to a user’s task of retrieval and access.

RDA instructions are available online through the RDA Toolkit, by subscription and in print. RDA Vocabularies are a representation of RDA entities, elements and relationship designators in RDF and are available via GitHub and the Resource Description Framework Registry.

The SIL RDA resources on this site provide an introduction to the new standard and will be useful only until the official LC-PCC RDA metadata guidance documents are released. Then they will be the authoritative source of RDA rules and guidelines for SIL catalogers.

Examples

Resource Description staff participate in a wide variety of metadata initiatives to provide increased access to library holdings and resources. These efforts include the development of RDA vocabulary lists and other documentation, coordinating policies and procedures, and providing technical support. Staff also produce a variety of reports that provide specialized services and management information.

A new cataloging standard has been published to replace AACR2: Resource Description and Access (RDA). It was developed through a collaborative process led by the Joint Steering Committee for Revision of Anglo-American Cataloguing Rules. The committee included representatives from the American Library Association, Bibliothèque nationale de France, British Library, National Library of Australia, and Deutsche Nationalbibliothek. RDA is available as a free download, RDA Toolkit, and in print from the ALA Store.

This library science essay explains the background of RDA, including its brief history and the controversy surrounding it. It also demonstrates some of the differences between RDA and AACR2. It also highlights the potential for using the new RDA rules to improve cataloging in digital environments.

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