lm2008.bib
@COMMENT{{This file has been generated by bib2bib 1.66}}
@COMMENT{{Command line: bib2bib -oc lm2008.keys -ob lm2008.bib -c 'export = "yes" and year=2008' ../lm.bib ../euprovenance.bib ../ops.bib}}
@ARTICLE{Moreau:CACM08,
AUTHOR = {Luc Moreau and Paul Groth and Simon Miles and Javier Vazquez and
John Ibbotson and Sheng Jiang and Steve Munroe and Omer Rana and
Andreas Schreiber and Victor Tan and Laszlo Varga},
TITLE = {{The Provenance of Electronic Data}},
JOURNAL = {Communications of the ACM},
YEAR = {2008},
URL = {http://www.ecs.soton.ac.uk/~lavm/papers/cacm08.pdf},
EUPUB = {yes},
PASOA = {yes},
EXPORT = {yes},
OPTKEY = {},
VOLUME = {51},
NUMBER = {4},
PAGES = {52--58},
MONTH = APR,
OPTNOTE = {},
OPTANNOTE = {},
ABSTRACT = {In the study of fine art, provenance refers to the documented history
of some art object. Given that documented history, the object attains an
authority that allows scholars to appreciate its importance with respect to
other works, whereas, in the absence of such history, the
object may be treated with some skepticism. Our IT landscape is evolving as
illustrated by applications that are open, composed dynamically, and that
discover results and services on the fly. Against this challenging background,
it is crucial for users to be able to have confidence in the results produced
by such applications. If the provenance of data produced by computer
systems could be determined as it can for some works of art, then users,
in their daily applications, would be able to interpret and judge the quality
of data better. We introduce a provenance lifecycle and
advocate an open approach based on two key principles to support a notion of
provenance in computer systems: documentation of execution and user-tailored
provenance queries.}
}
@INBOOK{Moreau:HPC08,
AUTHOR = {Paul Groth and Steve Munroe and Simon Miles and Luc Moreau},
ALTEDITOR = {},
TITLE = {In Lucio Grandinetti (ed.), HPC and Grids in Action},
CHAPTER = {{Applying the Provenance Data Model to a Bioinformatics Case}},
PUBLISHER = {IOS Press},
YEAR = {2008},
PASOA = {yes},
EXPORT = {yes},
URL = {http://www.ecs.soton.ac.uk/~lavm/papers/hpc08.pdf},
OPTKEY = {},
OPTVOLUME = {},
OPTNUMBER = {},
OPTSERIES = {},
OPTTYPE = {},
OPTADDRESS = {},
OPTEDITION = {},
MONTH = JAN,
OPTPAGES = {},
OPTNOTE = {},
OPTANNOTE = {},
ABSTRACT = {Scientists and, more generally end users of computer systems, need
to be able to trust the data they use. Understanding the origin or
provenance of data can provide this trust. Attempts have been made
to develop systems for recording provenance, however, most are not
generic and cannot be applied in a general manner across different
systems and different technologies. Moreover, many existing systems
confuse the concept of provenance with its representation. In this
article, we discuss an open, technology neutral model for
provenance. The model can be applied across many different systems
and makes the important distinction between provenance and the way
it can be generated from a concrete representation of process. The
model is described and applied to a grid-based example
bioinformatics application.}
}
@ARTICLE{Wei:JAAMA08,
AUTHOR = {Yan Zheng Wei and Nicholas R. Jennings and Luc Moreau and
Wendy Hall},
TITLE = {User evaluation of a market-based recommender system},
JOURNAL = {Journal of Autonomous Agents and Multi-Agent Systems},
YEAR = {2008},
URL = {http://eprints.ecs.soton.ac.uk/15015/},
EXPORT = {yes},
MAGNITUDE = {yes},
OPTKEY = {},
OPTVOLUME = {},
OPTNUMBER = {},
OPTPAGES = {},
MONTH = JAN,
OPTNOTE = {},
OPTANNOTE = {},
ABSTRACT = {Recommender systems have been developed for a wide variety of
applications (ranging from books, to holidays, to web
pages). These systems have used a number of different
approaches, since no one technique is best for all users in
all `situations. Given this, we believe that to be effective,
systems should incorporate a wide variety of such techniques
and then some form of overarching framework should be put in
place to coordinate them so that only the best
recommendations (from whatever source) are presented to the
user. To this end, in our previous work, we detailed a
market-based approach in which various recommender agents
competed with one another to present their recommendations to
the user. We showed through theoretical analysis and
empirical evaluation with simulated users that an
appropriately designed marketplace should be able to provide
effective coordination. Building on this, we now report on
the development of this multi-agent system and its evaluation
with real users. Specifically, we show that our system is
capable of consistently giving high quality recommendations,
that the best recommendations that could be put forward are
actually put forward, and that the combination of
recommenders perform better than any constituent
recommender.}
}
@ARTICLE{Miles:CISE2008,
AUTHOR = {Simon Miles and Paul Groth and Ewa Deelman and Karan Vahi and
Gaurang Mehta and Luc Moreau},
TITLE = {Provenance: The Bridge Between Experiments and Data},
JOURNAL = {Computing in Science and Engineering},
YEAR = {2008},
EXPORT = {yes},
PASOA = {yes},
URL = {http://www.ecs.soton.ac.uk/~lavm/papers/cise08.pdf},
OPTKEY = {},
VOLUME = {10},
NUMBER = {3},
PAGES = {38--46},
MONTH = {May/June},
OPTNOTE = {},
OPTANNOTE = {},
ABSTRACT = {Current scientific applications are often structured as workflows
and rely on workflow systems to compile abstract experiment
designs into enactable workflows that utilise the best
available resources. The automation of this step and of the
workflow enactment, hides the details of how results have
been produced. Knowing how compilation and enactment
occurred allows results to be reconnected with the experiment
design. We investigate how provenance helps scientists to
connect their results with the actual execution that took
place, their original experiment and its inputs and
parameters.}
}
@TECHREPORT{opm:1.01,
TITLE = {The Open Provenance Model (v1.01)},
AUTHOR = {Luc {Moreau (Editor)} and Beth Plale and Simon Miles and Carole Goble and Paolo Missier and Roger Barga and Yogesh Simmhan and Joe Futrelle and Robert McGrath and Jim Myers and Patrick Paulson and Shawn Bowers and Bertram Ludaescher and Natalia Kwasnikowska and Jan Van den Bussche and Tommy Ellkvist and Juliana Freire and Paul Groth},
MONTH = {July},
YEAR = {2008},
PASOA = {yes},
EXPORT = {yes},
INSTITUTION = {University of Southampton},
URL = {http://eprints.ecs.soton.ac.uk/16148/1/opm-v1.01.pdf},
ABSTRACT = {In this paper, we introduce the Open Provenance Model, a model for provenance that is designed to meet the following requirements: (1) To allow provenance information to be exchanged between systems, by means of a compatibility layer based on a shared provenance model. (2) To allow developers to build and share tools that operate on such a provenance model. (3) To define the model in a precise, technology-agnostic manner. (4) To support a digital representation of provenance for any "thing", whether produced by computer systems or not. (5) To define a core set of rules that identify the valid inferences that can be
made on provenance graphs.
}
}
@PROCEEDINGS{Freire-Koop-Moreau:IPAW08,
TITLE = {{Provenance and Annotation of Data --- International Provenance and Annotation Workshop, IPAW 2008}},
YEAR = {2008},
OPTKEY = {},
OPTBOOKTITLE = {},
EDITOR = {Juliana Freire and David Koop and Luc Moreau},
VOLUME = {5272},
SERIES = {Lecture Notes in Computer Science},
ISBN = {978-3-540-89964-8},
DOI = {10.1007/978-3-540-89965-5},
EXPORT = {yes},
PROVENANCE = {yes},
OPTADDRESS = {},
OPTMONTH = JUNE,
OPTORGANIZATION = {},
PUBLISHER = {Springer-Verlag},
OPTNOTE = {},
OPTANNOTE = {}
}
@INPROCEEDINGS{Aldeco-Perez:BCS2008,
AUTHOR = {Rocio Aldeco-Perez and Luc Moreau},
TITLE = {{Provenance-based Auditing of Private Data Use}},
BOOKTITLE = {BCS International Academic Research Conference, Visions of
Computer Science (In Press)},
YEAR = {2008},
EXPORT = {yes},
PROVENANCE = {yes},
MONTH = SEP,
EXPORT = {yes},
URL = {http://eprints.ecs.soton.ac.uk/16580/},
ABSTRACT = {Across the world, organizations are required to comply
with regulatory frameworks dictating how to manage
personal information. Despite these, several cases
of data leaks and exposition of private data to
unauthorized recipients have been publicly and
widely advertised. For authorities and system
administrators to check compliance to regulations,
auditing of private data processing becomes crucial
in IT systems. Finding the origin of some data,
determining how some data is being used, checking
that the processing of some data is compatible with
the purpose for which the data was captured are
typical functionality that an auditing capability
should support, but difficult to implement in a
reusable manner. Such questions are so-called
provenance questions, where provenance is defined as
the process that led to some data being
produced. The aim of this paper is to articulate how
data provenance can be used as the underpinning
approach of an auditing capability in IT systems. We
present a case study based on requirements of the
Data Protection Act and an application that audits
the processing of private data, which we apply to an
example manipulating private data in a university.}
}
@INPROCEEDINGS{Chen08a,
AUTHOR = {Zheng Chen and Luc Moreau},
TITLE = {Recording Process Documentation in the Presence of Failures},
BOOKTITLE = {Methods, Models and Tools for Fault Tolerance},
YEAR = 2008,
ISBN = {},
PAGES = {},
EXPORT = {yes},
PROVENANCE = {yes},
DOI = {},
URL = {http://eprints.ecs.soton.ac.uk/16588/},
PUBLISHER = {Springer-Verlag},
SERIES = {Lecture Notes in Computer Science},
ADDRESS = {},
NOTE = {In Press},
ABSTRACT = {Scientific and business communities present unprecedented
requirements on provenance, where the provenance of
some data item is the process that led to that data
item. Previous work has conceived a computer-based
representation of past executions for determining
provenance, termed process documentation, and has
developed a protocol, PReP, to record process
documentation in service oriented
architectures. However, PReP assumes a failure free
environment. Failures lead to process documentation
unable to be recorded, losing the evidence that a
process occurred. This is not acceptable in the
applications relying on process documentation and
would cause disastrous consequences. This paper
describes our solution, F-PReP, a protocol for
recording process documentation in the presence of
failures. A complete formalization of the protocol
using Abstract State Machines is also presented.}
}
@INPROCEEDINGS{Chen-Moreau:IPAW08,
AUTHOR = {Zheng Chen and Luc Moreau},
TITLE = {Implementation and Evaluation of a Protocol for Recording Process
Documentation in the Presence of Failures},
BOOKTITLE = {Proceedings of Second International Provenance and Annotation
Workshop (IPAW'08)},
MONTH = JUN,
YEAR = 2008,
ISBN = {978-3-540-89964-8},
PAGES = {92--105},
DOI = {10.1007/978-3-540-89965-5},
EXPORT = {yes},
VOLUME = {5272},
PROVENANCE = {yes},
URL = {http://eprints.ecs.soton.ac.uk/16591/},
PUBLISHER = {Springer-Verlag},
SERIES = {Lecture Notes in Computer Science},
ADDRESS = {Salt Lake City, USA},
ABSTRACT = {The provenance of a particular data item is the process that led to that piece of data. Previous work has enabled the creation of detailed representation of past executions for determining provenance, termed process documentation. However, current solutions to recording process documentation assume a failure free environment. Failures result in process documentation not being recorded, thereby causing the loss of evidence that a process occurred. We have designed F-PReP, a protocol to guarantee the recording of process documentation in the presence of failures. This paper discusses its implementation and evaluates its performance. The result reveals that it introduces acceptable overhead.}
}
@INPROCEEDINGS{Moreau:OPM_IPAW08,
AUTHOR = {Luc Moreau and Juliana Freire and Joe Futrelle and Robert
E. McGrath and Jim Myers and Patrick Paulson},
TITLE = {The Open Provenance Model: An Overview},
EXPORT = {yes},
BOOKTITLE = {Provenance and Annotation of Data and Processes},
DOI = {10.1007/978-3-540-89965-5_31},
PAGES = {323--326},
YEAR = 2008,
VOLUME = 5272,
PUBLISHER = {Springer-Verlag},
SERIES = {Lecture Notes in Computer Science},
ADDRESS = {Salt Lake City, USA},
ABSTRACT = {Provenance is well understood in the context of art or digital libaries, where it respectively refers to the documented history of an art object, or the documentation of processes in a digital object's life cycle. Interest for provenance in the ``e-science community'' [12] is also growing, since provenance is perceived as a crucial component of workflow systems that can help scientists ensure reproducibility of their scientific analyses and processes}
}