4,572 research outputs found
bdbms -- A Database Management System for Biological Data
Biologists are increasingly using databases for storing and managing their
data. Biological databases typically consist of a mixture of raw data,
metadata, sequences, annotations, and related data obtained from various
sources. Current database technology lacks several functionalities that are
needed by biological databases. In this paper, we introduce bdbms, an
extensible prototype database management system for supporting biological data.
bdbms extends the functionalities of current DBMSs to include: (1) Annotation
and provenance management including storage, indexing, manipulation, and
querying of annotation and provenance as first class objects in bdbms, (2)
Local dependency tracking to track the dependencies and derivations among data
items, (3) Update authorization to support data curation via content-based
authorization, in contrast to identity-based authorization, and (4) New access
methods and their supporting operators that support pattern matching on various
types of compressed biological data types. This paper presents the design of
bdbms along with the techniques proposed to support these functionalities
including an extension to SQL. We also outline some open issues in building
bdbms.Comment: This article is published under a Creative Commons License Agreement
(http://creativecommons.org/licenses/by/2.5/.) You may copy, distribute,
display, and perform the work, make derivative works and make commercial use
of the work, but, you must attribute the work to the author and CIDR 2007.
3rd Biennial Conference on Innovative Data Systems Research (CIDR) January
710, 2007, Asilomar, California, US
Labeling Workflow Views with Fine-Grained Dependencies
This paper considers the problem of efficiently answering reachability
queries over views of provenance graphs, derived from executions of workflows
that may include recursion. Such views include composite modules and model
fine-grained dependencies between module inputs and outputs. A novel
view-adaptive dynamic labeling scheme is developed for efficient query
evaluation, in which view specifications are labeled statically (i.e. as they
are created) and data items are labeled dynamically as they are produced during
a workflow execution. Although the combination of fine-grained dependencies and
recursive workflows entail, in general, long (linear-size) data labels, we show
that for a large natural class of workflows and views, labels are compact
(logarithmic-size) and reachability queries can be evaluated in constant time.
Experimental results demonstrate the benefit of this approach over the
state-of-the-art technique when applied for labeling multiple views.Comment: VLDB201
Answering Regular Path Queries on Workflow Provenance
This paper proposes a novel approach for efficiently evaluating regular path
queries over provenance graphs of workflows that may include recursion. The
approach assumes that an execution g of a workflow G is labeled with
query-agnostic reachability labels using an existing technique. At query time,
given g, G and a regular path query R, the approach decomposes R into a set of
subqueries R1, ..., Rk that are safe for G. For each safe subquery Ri, G is
rewritten so that, using the reachability labels of nodes in g, whether or not
there is a path which matches Ri between two nodes can be decided in constant
time. The results of each safe subquery are then composed, possibly with some
small unsafe remainder, to produce an answer to R. The approach results in an
algorithm that significantly reduces the number of subqueries k over existing
techniques by increasing their size and complexity, and that evaluates each
subquery in time bounded by its input and output size. Experimental results
demonstrate the benefit of this approach
Using Links to prototype a Database Wiki
Both relational databases and wikis have strengths that make them attractive for use in collaborative applications. In the last decade, database-backed Web applications have been used extensively to develop valuable shared biological references called curated databases. Databases offer many advantages such as scalability, query optimization and concurrency control, but are not easy to use and lack other features needed for collaboration. Wikis have become very popular for early-stage biocuration projects because they are easy to use, encourage sharing and collaboration, and provide built-in support for archiving, history-tracking and annotation. However, curation projects often outgrow the limited capabilities of wikis for structuring and efficiently querying data at scale, necessitating a painful phase transition to a database-backed Web application. We perceive a need for a new class of general-purpose system, which we call a Database Wiki, that combines flexible wiki-like support for collaboration with robust database-like capabilities for structuring and querying data. This paper presents DBWiki, a design prototype for such a system written in the Web programming language Links. We present the architecture, typical use, and wiki markup language design for DBWiki and discuss features of Links that provided unique advantages for rapid Web/database application prototyping
Causality and the semantics of provenance
Provenance, or information about the sources, derivation, custody or history
of data, has been studied recently in a number of contexts, including
databases, scientific workflows and the Semantic Web. Many provenance
mechanisms have been developed, motivated by informal notions such as
influence, dependence, explanation and causality. However, there has been
little study of whether these mechanisms formally satisfy appropriate policies
or even how to formalize relevant motivating concepts such as causality. We
contend that mathematical models of these concepts are needed to justify and
compare provenance techniques. In this paper we review a theory of causality
based on structural models that has been developed in artificial intelligence,
and describe work in progress on a causal semantics for provenance graphs.Comment: Workshop submissio
A policy language definition for provenance in pervasive computing
Recent advances in computing technology have led to the paradigm of pervasive computing, which provides a means of simplifying daily life by integrating information processing into the everyday physical world. Pervasive computing draws its power from knowing the surroundings and creates an environment which combines computing and communication capabilities. Sensors that provide high-resolution spatial and instant measurement are most commonly used for forecasting, monitoring and real-time environmental modelling. Sensor data generated by a sensor network depends on several influences, such as the configuration and location of the sensors or the processing performed on the raw measurements. Storing sufficient metadata that gives meaning to the recorded observation is important in order to draw accurate conclusions or to enhance the reliability of the result dataset that uses this automatically collected data. This kind of metadata is called provenance data, as the origin of the data and the process by which it arrived from its origin are recorded. Provenance is still an exploratory field in pervasive computing and many open research questions are yet to emerge. The context information and the different characteristics of the pervasive environment call for different approaches to a provenance support system.
This work implements a policy language definition that specifies the collecting model for provenance management systems and addresses the challenges that arise with stream data and sensor environments. The structure graph of the proposed model is mapped to the Open Provenance Model in order to facilitating the sharing of provenance data and interoperability with other systems. As provenance security has been recognized as one of the most important components in any provenance system, an access control language has been developed that is tailored to support the special requirements of provenance: fine-grained polices, privacy policies and preferences. Experimental evaluation findings show a reasonable overhead for provenance collecting and a reasonable time for provenance query performance, while a numerical analysis was used to evaluate the storage overhead
A Semantic Hierarchy for Erasure Policies
We consider the problem of logical data erasure, contrasting with physical
erasure in the same way that end-to-end information flow control contrasts with
access control. We present a semantic hierarchy for erasure policies, using a
possibilistic knowledge-based semantics to define policy satisfaction such that
there is an intuitively clear upper bound on what information an erasure policy
permits to be retained. Our hierarchy allows a rich class of erasure policies
to be expressed, taking account of the power of the attacker, how much
information may be retained, and under what conditions it may be retained.
While our main aim is to specify erasure policies, the semantic framework
allows quite general information-flow policies to be formulated for a variety
of semantic notions of secrecy.Comment: 18 pages, ICISS 201
- …