40,923 research outputs found
Dynamic Provenance for SPARQL Update
While the Semantic Web currently can exhibit provenance information by using
the W3C PROV standards, there is a "missing link" in connecting PROV to storing
and querying for dynamic changes to RDF graphs using SPARQL. Solving this
problem would be required for such clear use-cases as the creation of version
control systems for RDF. While some provenance models and annotation techniques
for storing and querying provenance data originally developed with databases or
workflows in mind transfer readily to RDF and SPARQL, these techniques do not
readily adapt to describing changes in dynamic RDF datasets over time. In this
paper we explore how to adapt the dynamic copy-paste provenance model of
Buneman et al. [2] to RDF datasets that change over time in response to SPARQL
updates, how to represent the resulting provenance records themselves as RDF in
a manner compatible with W3C PROV, and how the provenance information can be
defined by reinterpreting SPARQL updates. The primary contribution of this
paper is a semantic framework that enables the semantics of SPARQL Update to be
used as the basis for a 'cut-and-paste' provenance model in a principled
manner.Comment: Pre-publication version of ISWC 2014 pape
The Pan-STARRS Moving Object Processing System
We describe the Pan-STARRS Moving Object Processing System (MOPS), a modern
software package that produces automatic asteroid discoveries and
identifications from catalogs of transient detections from next-generation
astronomical survey telescopes. MOPS achieves > 99.5% efficiency in producing
orbits from a synthetic but realistic population of asteroids whose
measurements were simulated for a Pan-STARRS4-class telescope. Additionally,
using a non-physical grid population, we demonstrate that MOPS can detect
populations of currently unknown objects such as interstellar asteroids.
MOPS has been adapted successfully to the prototype Pan-STARRS1 telescope
despite differences in expected false detection rates, fill-factor loss and
relatively sparse observing cadence compared to a hypothetical Pan-STARRS4
telescope and survey. MOPS remains >99.5% efficient at detecting objects on a
single night but drops to 80% efficiency at producing orbits for objects
detected on multiple nights. This loss is primarily due to configurable MOPS
processing limits that are not yet tuned for the Pan-STARRS1 mission.
The core MOPS software package is the product of more than 15 person-years of
software development and incorporates countless additional years of effort in
third-party software to perform lower-level functions such as spatial searching
or orbit determination. We describe the high-level design of MOPS and essential
subcomponents, the suitability of MOPS for other survey programs, and suggest a
road map for future MOPS development.Comment: 57 Pages, 26 Figures, 13 Table
archivist: An R Package for Managing, Recording and Restoring Data Analysis Results
Everything that exists in R is an object [Chambers2016]. This article
examines what would be possible if we kept copies of all R objects that have
ever been created. Not only objects but also their properties, meta-data,
relations with other objects and information about context in which they were
created.
We introduce archivist, an R package designed to improve the management of
results of data analysis. Key functionalities of this package include: (i)
management of local and remote repositories which contain R objects and their
meta-data (objects' properties and relations between them); (ii) archiving R
objects to repositories; (iii) sharing and retrieving objects (and it's
pedigree) by their unique hooks; (iv) searching for objects with specific
properties or relations to other objects; (v) verification of object's identity
and context of it's creation.
The presented archivist package extends, in a combination with packages such
as knitr and Sweave, the reproducible research paradigm by creating new ways to
retrieve and validate previously calculated objects. These new features give a
variety of opportunities such as: sharing R objects within reports or articles;
adding hooks to R objects in table or figure captions; interactive exploration
of object repositories; caching function calls with their results; retrieving
object's pedigree (information about how the object was created); automated
tracking of the performance of considered models, restoring R libraries to the
state in which object was archived.Comment: Submitted to JSS in 2015, conditionally accepte
Reflections on the future of research curation and research reproducibility
In the years since the launch of the World Wide Web in 1993, there have been profoundly transformative changes to the entire concept of publishingâexceeding all the previous combined technical advances of the centuries following the introduction of movable type in medieval Asia around the year 10001 and the subsequent large-scale commercialization of printing several centuries later by J. Gutenberg (circa 1440). Periodicals in printâfrom daily newspapers to scholarly journalsâare now quickly disappearing, never to return, and while no publishing sector has been unaffected, many scholarly journals are almost unrecognizable in comparison with their counterparts of two decades ago. To say that digital delivery of the written word is fundamentally different is a huge understatement. Online publishing permits inclusion of multimedia and interactive content that add new dimensions to what had been available in print-only renderings. As of this writing, the IEEE portfolio of journal titles comprises 59 online only2 (31%) and 132 that are published in both print and online. The migration from print to online is more stark than these numbers indicate because of the 132 periodicals that are both print and online, the print runs are now quite small and continue to decline. In short, most readers prefer to have their subscriptions fulfilled by digital renderings only
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