246,793 research outputs found
First-Order Provenance Games
We propose a new model of provenance, based on a game-theoretic approach to
query evaluation. First, we study games G in their own right, and ask how to
explain that a position x in G is won, lost, or drawn. The resulting notion of
game provenance is closely related to winning strategies, and excludes from
provenance all "bad moves", i.e., those which unnecessarily allow the opponent
to improve the outcome of a play. In this way, the value of a position is
determined by its game provenance. We then define provenance games by viewing
the evaluation of a first-order query as a game between two players who argue
whether a tuple is in the query answer. For RA+ queries, we show that game
provenance is equivalent to the most general semiring of provenance polynomials
N[X]. Variants of our game yield other known semirings. However, unlike
semiring provenance, game provenance also provides a "built-in" way to handle
negation and thus to answer why-not questions: In (provenance) games, the
reason why x is not won, is the same as why x is lost or drawn (the latter is
possible for games with draws). Since first-order provenance games are
draw-free, they yield a new provenance model that combines how- and why-not
provenance
Requirements for Provenance on the Web
From where did this tweet originate? Was this quote from the New York Times modified? Daily, we rely on data from the Web but often it is difficult or impossible to determine where it came from or how it was produced. This lack of provenance is particularly evident when people and systems deal with Web information or with any environment where information comes from sources of varying quality. Provenance is not captured pervasively in information systems. There are major technical, social, and economic impediments that stand in the way of using provenance effectively. This paper synthesizes requirements for provenance on the Web for a number of dimensions focusing on three key aspects of provenance: the content of provenance, the management of provenance records, and the uses of provenance information. To illustrate these requirements, we use three synthesized scenarios that encompass provenance problems faced by Web users toda
Provenance Threat Modeling
Provenance systems are used to capture history metadata, applications include
ownership attribution and determining the quality of a particular data set.
Provenance systems are also used for debugging, process improvement,
understanding data proof of ownership, certification of validity, etc. The
provenance of data includes information about the processes and source data
that leads to the current representation. In this paper we study the security
risks provenance systems might be exposed to and recommend security solutions
to better protect the provenance information.Comment: 4 pages, 1 figure, conferenc
Security Issues in a SOA-based Provenance System
Recent work has begun exploring the characterization and utilization of provenance in systems based on the Service Oriented Architecture (such as Web Services and Grid based environments). One of the salient issues related to provenance use within any given system is its security. Provenance presents some unique security requirements of its own, which are additionally dependent on the architectural and environmental context that a provenance system operates in. We discuss the security considerations pertaining to a Service Oriented Architecture based provenance system. Concurrently, we outline possible approaches to address them
Towards Automatic Capturing of Manual Data Processing Provenance
Often data processing is not implemented by a work ow system or an integration application but is performed manually by humans along the lines of a more or less specified procedure. Collecting provenance information during manual data processing can not be automated. Further, manual collection of provenance information is error prone and time consuming. Therefore, we propose to infer provenance information based on the read and write access of users. The derived provenance information is complete, but has a low precision. Therefore, we propose further to introducing organizational guidelines in order to improve the precision of the inferred provenance information
Provenance Circuits for Trees and Treelike Instances (Extended Version)
Query evaluation in monadic second-order logic (MSO) is tractable on trees
and treelike instances, even though it is hard for arbitrary instances. This
tractability result has been extended to several tasks related to query
evaluation, such as counting query results [3] or performing query evaluation
on probabilistic trees [10]. These are two examples of the more general problem
of computing augmented query output, that is referred to as provenance. This
article presents a provenance framework for trees and treelike instances, by
describing a linear-time construction of a circuit provenance representation
for MSO queries. We show how this provenance can be connected to the usual
definitions of semiring provenance on relational instances [20], even though we
compute it in an unusual way, using tree automata; we do so via intrinsic
definitions of provenance for general semirings, independent of the operational
details of query evaluation. We show applications of this provenance to capture
existing counting and probabilistic results on trees and treelike instances,
and give novel consequences for probability evaluation.Comment: 48 pages. Presented at ICALP'1
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