Introducing Time into RDF

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Introducing Time into RDF

• Authors
• Claudio Gutierrez, Carlos A. Hurtado, and
  Alejandro Vaisman
• Presented By
• Reza Zamanipour
• zamanipo_at_usc.edu

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Introduction

• This paper presents a framework to incorporate
  temporal reasoning into RDF, yielding temporal
  RDF graphs. We present a semantics for these
  kinds of graphs which includes the notion of
  temporal entailment and a syntax to incorporate
  this framework into standard RDF graphs, using
  the RDF vocabulary plus temporal labels.

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What is RDF?

• metadata model and language recommended by the
  W3C for building an infrastructure of
  machine-readable semantics for the data on the
  Web.
• Everything can be modeled by a set of resources.
• The language to describe them is a set of
  properties, or predicates.
• Descriptions are statements in the
  subject-predicate-object structure
• RDF has a vocabulary that can deal with
  inheritance and typing
• The RDF specification can be seen as a graph.
• Each subject-predicate-object triple is
  represented as a node-edge-node structure.

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Why we need to add time?

• In many cases we need to address some changes in
  the ontology of a document.
• Web pages are changing over time.
• So modeling of time is one of the key primitives
  needed in a query language for Web and
  semi-structured data.
• Some Examples are
• Accessing different versions of an ontology
• Retrieving past info about Web sites
• Querying metadata about resources that are
  temporal in nature (e.g., stocks and news).

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Example

• A Web service ontology introduced by Antoniou and
  Van Harme in A Semantic Web Primer MIT Press,
  2004
• The Web site delivers up-to-date articles about
  sports. Input sports category the customers
  credit card number
• output returns the requested article

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RDF representation of an ontology for a Web
service,, offered by a sports network ESPN
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Change scenario

• Suppose that, at a certain point in time (say
  time instant 2), ESPN sold the rights on Sport
  News to another sports network, Fox Sports thus,
  at time 3, the Web service is offered by the
  latter network.
• The new owners decided (at time instant 4) to
  add a new service They will deliver videos of
  the best plays of the week for all sport events
  covered by the network.
• Changes over the previous RDF graph
• The name, phone, and Web page of the service
  provider must be replaced and
• The new service must be added to the graph.

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• New Service Includes addition of the following
  triples
• play of the week, type, offered service
• play of the week, provided by, Fox Sports
• play of the week, output, video
• play of the week, input, customer card
• video, type, parameter

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Temporal RDF graph for evolution of the Web
services ontology
Link to Previous ver.
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Problems in the new scenario

• when a change occurs, a new document must be
  created and the current document dropped.
• Queries asking for past states of the metadata
  cannot be supported. For instance, we cannot ask
  for the services offered by ESPN at a certain
  point in time
• ontology changes (for instance, new properties
  may be required to describe Web services, or
  another one may cease to be needed

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How to Introduce Time into RDF

• Two different approaches
• Versioning
• Maintaining a snapshot of each state of the
  graph
• Labeling
• Labeling the elements or tuples subject to
  changes

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• Valid time
• The time when data is valid in the modeled
  world.
• Transaction Time
• The time when data is actually stored in the
  database.
• The versioning approach captures transaction
  time, while labeling is mostly used when
  representing valid time.
• For RDF data, labeling is better than versioning
  because
• 1) It preserves the spirit of the distributed
  and extensible nature of RDF
• 2) Large overhear for temporal queries that span
  multiple versions in scenarios where changes are
  frequent and only affecting a few elements.

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Add Time to RDF Graph
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Basic Concept
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Interval-Based Labeling
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• Temporal Entailment
• An RDF graph can be regarded as a knowledge base
  from which new knowledge, i.e., other graphs, may
  be entailed.
• define the semantics as in temporal relational
  databases, i.e., defining the temporal database
  as the union of all of its snapshots
• Some problems with empty nodes.

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• Temporal Query Language
• Two choices for defining the temporal domains
  exist point-based and interval-based, so for
  query languages in temporal databases we have two
  different query languages
• In time-based time variables are individual time
  instants, while in the interval-based
• domain, variables in the queries are range over
  intervals.
• These two kind of query can be changed easily.
  together.

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Contributions

• In this paper, authors present a framework to
  incorporate temporal reasoning into RDF, yielding
  temporal RDF graphs. In particular
• 1. a semantics for temporal RDF graphs in terms
  of the semantics of non-temporal RDF and RDFS
  graphs,
• 2. a study of the properties of temporal RDF
  graphs and the interplay between timestamp and
  snapshot semantics in temporal RDF graphs,
• 3. a syntax to incorporate this framework into
  standard RDF graphs
• 4. complexity bounds which show that entailment
  in temporal RDF graphs does not yield extra
  asymptotic time complexity with respect to
  standard RDF graphs,
• 5. a study of temporal RDF graphs with anonymous
  timestamps
• 6. a sketch of a temporal query language for RDF
  and complexity results for query evaluation.

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Future Work

• Definition of a built-in arithmetic, aggregate
  functions, and a unified semantic for the two
  classes of RDF atemporal and plain. Allow
  closeness and full query composition in a
  temporal query language for RDF.
• Temporal vocabulary with built-in predicates,
  such as an order relation,

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Questions?

• Thank you