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Generic Provenance Management for Linked Dataspaces
Abstract
The emergence of Linked Data accelerates the demand
for mechanisms which can support users in the
assessment of data quality and trustworthiness on the
Web. In this process, the ability to track the historical
trail behind information resources on the Web plays a
fundamental role in the Linked Data Web. Applications
consuming or generating Linked Data on the Web need
to become provenance-aware, i.e., being able to
capture and consume provenance descriptors
associated with the data. This brings provenance as a
key requirement for a wide spectrum of applications.
This work focuses on the creation of this infrastructure,
describing a generic provenance management
framework for the Web using Semantic Web tools and
standards to address the core challenges of provenance
management on the Web.
1. Introduction
The advent of Linked Data in the last years as the defacto
standard to publish data on the Web, and its
uptake by early adopters, defines a clear trend towards a
Web where users will be able to easily aggregate,
consume and republish data. With Linked Data, Web
information can be repurposed with a new level of
granularity and scale. In this scenario, tracking the
historical trail behind an information artifact plays a
fundamental role for data consumers, allowing users to
determine the suitability and quality of a piece of
information.
To provide the additional provenance data, Linked Data
applications will demand mechanisms to track and
manage provenance information. This new common
requirement is inherent to the level of data integration
provided by Linked Data and it is not found in most
systems consuming information from “data silos”,
where the relationship among data sources and
applications is, in general, more rigid. This work
focuses on the provision of a provenance management
infrastructure having as a motivation supporting Linked
Data applications.
2. Description of the Approach
The central goal behind this work is to provide a set of
core functionalities that enable users to develop
provenance-aware applications, both from the
consumption (discovery/query/access) and from the
capture (logging/ publishing) perspectives. The
architecture of the proposed approach maximizes the
encapsulation of provenance capture and consumption
André Freitas, Seán O’Riain, Edward Curry
Digital Enterprise Research Institute (DERI)
National University of Ireland, Galway
{firstname.lastname@deri.org}
124
functionalities, separating provenance into a distinct
layer.
Two strong requirements in the construction of the
framework are the minimization of efforts in software
adaptations (changes in the original system to make a
system provenance-aware) and the provision of a
expressive provenance model. To satisfy the
requirements above, the proposed approach employed
the following strategies:
- Provenance capture by software reflection and
annotation.
- An Expressive and accessible API for
provenance queries.
- Use of Semantic Web standards & tools.
The final solution includes a provenance management
framework [1] (Prov4J) and a provenance ontology
(W3P) [2]. Further details on both artifacts can be found
in [1] and [2].
3. Evaluation
The framework was evaluated using a provenance
dataset which was generated using aggregated business
news and opinions collected from data sources on the
Web. These data elements defined the ground artifacts
which were further curated and analyzed in a financial
analysis workflow simulator. Based on the generated
provenance workflow, a provenance query set was
created, covering 51 types of provenance queries. The
framework was evaluated in terms of query expressivity
and completeness, query execution time and coverage of
the W3C Provenance Incubator group requirements for
mapping Provenance on the Web [3].
The framework achieved high query expressivity (80%
of the queries were addressed), with an average query
execution time of 250 ms. The approach also presented
a medium coverage in relation to the W3C Provenance
Incubator group requirements.
References
[1]. André Freitas, Tomas Knap, Sean O’Riain, Edward Curry, W3P:
Building an OPM based provenance model for the Web. In Future
Generation Computer Systems , 2010.
[2] André Freitas, Arnaud Legendre, Sean O'Riain, Edward Curry,
Prov4J: A Semantic Web Framework for Generic Provenance
Management. In The Second International Workshop on Role of
Semantic Web in Provenance Management (SWPM 2010), Springer,
Workshop at International Semantic Web Conference (ISWC),
Shanghai, China, 2010.
[3] Requirements for Provenance on the Web,
http://www.w3.org/2005/Incubator/prov/wiki/User_Requirements