1,520 research outputs found
A New Approach to Tagging Data in the Astronomical Literature
Data Tags are strings used in journals to indicate the origin of the
archival data and to enable the reader to recover the data. The NASA/IPAC
Infrared Science Archive (IRSA) has recently introduced a new approach to production
of data tags and recovery of data from them. Many of the data access
services at the IRSA return filtered data sets (such as subsets of source catalogs)
and dynamically created products (such as image cutouts); these dynamically
created products are not saved permanently at the archive. Rather than tag the
data sets from which the query result sets are drawn, the archive tags the query
that generates the results. A single tag can, then, encode a complex dynamic
data set and simplifies the embedding of tags in manuscripts and journals. By
logging user queries and all the parameters for those query as Data Tags, IRSA
can re-create the query and rerun the IRSA service using the same search parameters
used when the Data Tag was created. At the same time, the logs give
a simple count of the actual numbers of queries made to the archive, a powerful
metric of archive usage unobtainable from the Apache web server logs. Currently,
IRSA creates tags for queries to more than 20 data sets, including the
Infrared Astronomical Satellite (IRAS), Cosmic Evolution Survey (COSMOS)
and Spitzer Space Telescope Legacy Data Sets. These tags are returned by the
spatial query engine, Atlas. IRSA plans to create tags for queries to the rest
of its services in late Spring 2007. The archive provides a simple web interface
which recovers a data set that corresponds to the input data tag. Archived data
sets may evolve in time due to improved calibrations or augmentations to the
data set. IRSA’s query based approach guarantees that users always receive the
best available data sets
Spitzer data at the NASA/IPAC Infrared Science Archive (IRSA)
The NASA/IPAC Infrared Science Archive (IRSA) curates and serves science
data sets from NASA’s infrared and submillimeter projects and missions,
including IRAS, 2MASS, MSX, SWAS, ISO, IRTS and from the Spitzer Space
Telescope. All Spitzer data can be accessed from IRSA’s Spitzer mission page
at: http://irsa.ipac.caltech.edu/Missions/spitzer.html
Spitzer Legacy Enhanced Products along with ancillary data are delivered
in six month intervals starting from Fall 2004, until Fall 2006. IRSA continually
ingests the Spitzer data and the ancillary data, and these data are made
accessible through IRSA’s query engines. Legacy products for the C2D, FEPS,
GLIMPSE, GOODS, SINGS and SWIRE projects are accessible through a common
interface http://irsa.ipac.caltech.edu/applications/Atlas. This
engine returns the spatial footprints of observations and provides access to all
flavors of released data sets, including, where appropriate, previews of image
mosaics, 3-color image mosaics and spectra
Chapter 11: Web-based Tools—VO Region Inventory Service
As the size and number of datasets available through the VO grows, it becomes increasingly
critical to have services that aid in locating and characterizing data pertinent
to a particular scientific problem. At the same time, this same increase makes
that goal more and more difficult to achieve. With a small number of datasets, it is
feasible to simply retrieve the data itself (as the NVO DataScope service does). At
intermediate scales, “count” DBMS searches (searches of the actual datasets which
return record counts rather than full data subsets) sent to each data provider will
work. However, neither of these approaches scale as the number of datasets expands
into the hundreds or thousands.
Dealing with the same problem internally, IRSA developed a compact and extremely
fast scheme for determining source counts for positional catalogs (and in
some cases image metadata) over arbitrarily large regions for multiple catalogs in a
fraction of a second. To show applicability to the VO in general, this service has
been extended with indices for all 4000+ catalogs in CDS Vizier (essentially all published
catalogs and source tables).
In this chapter, we will briefly describe the architecture of this service, and then
describe how this can be used in a distributed system to retrieve rapid inventories of
all VO holdings in a way that places an insignificant load on any data supplier. Further,
we show and this tool can be used in conjunction with VO Registries and catalog
services to zero in on those datasets that are appropriate to the user’s needs.
The initial implementation of this service consolidates custom binary index file
structures (external to any DBMS and therefore portable) at a single site to minimize
search times and implements the search interface as a simple CGI program. However,
the architecture is amenable to distribution. The next phase of development will focus
on metadata harvesting from data archives through a standard program interface and
distribution of the search processing across multiple service providers for redundancy
and parallelization
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Tica: an environment for exploring tangible vs. screen-based programming
This paper describes Tica, an environment designed to explore the differences between tangible and screen based interfaces when teaching programming to children aged 5–7 years. Tica comprises several components: a tangible programming language and a screen based equivalent, an Android app to interpret the programming languages and record data, and a physical robot that can be programmed using either the tangible or screen-based language. Tica was designed using a learner-centred approach, with a specific focus on the needs and abilities of the target user group.
Once implemented, an initial pilot study was carried out with 14 adults. Although participants using the screen-based interface completed problems more quickly than those using the tangible interface, participants using the tangible interface reported a higher level of enjoyment. Next steps include a more extensive study with the target population as well as some refinements to the Tica environment
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