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The NASA-ADS Abstract Service provides a sophisticated search capability for the literature in Astronomy, Planetary Sciences, Physics/Geophysics, and Space Instrumentation. The ADS is funded by NASA and access to the ADS services is free to anybody worldwide without restrictions. It allows the user to search the literature by author, title, and abstract text. The ADS database contains over 3.6 million references, with 965,000 in the Astronomy/Planetary Sciences database, and 1.6 million in the Physics/Geophysics database. 2/3 of the records have full abstracts, the rest are table of contents entries (titles and author lists only). The coverage for the Astronomy literature is better than 95% from 1975. Before that we cover all major journals and many smaller ones. Most of the journal literature is covered back to volume 1. We now get abstracts on a regular basis from most journals. Over the last year we have entered basically all conference proceedings tables of contents that are available at the Harvard Smithsonian Center for Astrophysics library. This has greatly increased the coverage of conference proceedings in the ADS. The ADS also covers the ArXiv Preprints. We download these preprints every night and index all the preprints. They can be searched either together with the other abstracts or separately. There are currently about 260,000 preprints in that database. In January 2004 we have introduced two new services, full text searching and a personal notification service called "myADS". As all other ADS services, these are free to use for anybody.
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This version of the HST Archive Primer provides the basic information a user needs to know to access the HST archive via StarView the new user interface to the archive. Using StarView, users can search for observations interest, find calibration reference files, and retrieve data from the archive. Both the terminal version of StarView and the X-windows version feature a name resolver which simplifies searches of the HST archive based on target name. In addition, the X-windows version of StarView allows preview of all public HST data; compressed versions of public images are displayed via SAOIMAGE, while spectra are plotted using the public plotting package, XMGR. Finally, the version of StarView described here features screens designed for observers preparing Cycle 5 HST proposals.
We have developed and deployed a new data archive for the Gemini Observatory. Focused on simplicity and ease of use, the archive provides a number of powerful and novel features including automatic association of calibration data with the science data, and the ability to bookmark searches. A simple but powerful API allows programmatic search and download of data. The archive is hosted on Amazon Web Services, which provides us excellent internet connectivity and significant cost savings in both operations and development over more traditional deployment options. The code is written in python, utilizing a PostgreSQL database and Apache web server.
multiple world coordinate systems, three dimensional event file binning, image smoothing, region groups and tags, the ability to save images in a number of image formats (such as JPEG, TIFF, PNG, FITS), improvements in support for integrating external analysis tools, and support for the virtual observatory. In particular, a full-featured web browser has been implemented within D S 9 . This provides support for full access to HEASARC archive sites such as SKYVIEW and W3BROWSE, in addition to other astronomical archives sites such as MAST, CHANDRA, ADS, NED, SIMBAD, IRAS, NVRO, SA0 TDC, and FIRST. From within DS9, the archives can be searched, and FITS images, plots, spectra, and journal abstracts can be referenced, downloaded and displayed The web browser provides the basis for the built-in help facility. All DS9 documentation, including the reference manual, FAQ, Know Features, and contact information is now available to the user without the need for external display applications. New versions of DS9 maybe downloaded and installed using this facility. Two important features used in the analysis of high energy astronomical data have been implemented in the past year. The first is support for binning photon event data in three dimensions. By binning the third dimension in time or energy, users are easily able to detect variable x-ray sources and identify other physical properties of their data. Second, a number of fast smoothing algorithms have been implemented in DS9, which allow users to smooth their data in real time. Algorithms for boxcar, tophat, and gaussian smoothing are supported.
The SSC Multimedia Archive is an automated electronic system to manage images, acquired both by film and digital cameras, for the Public Affairs Office (PAO) at Stennis Space Center (SSC). Previously, the image archive was based on film photography and utilized a manual system that, by today s standards, had become inefficient and expensive. Now, the SSC Multimedia Archive, based on a server at SSC, contains both catalogs and images for pictures taken both digitally and with a traditional, film-based camera, along with metadata about each image. After a "shoot," a photographer downloads the images into the database. Members of the PAO can use a Web-based application to search, view and retrieve images, approve images for publication, and view and edit metadata associated with the images. Approved images are archived and cross-referenced with appropriate descriptions and information. Security is provided by allowing administrators to explicitly grant access privileges to personnel to only access components of the system that they need to (i.e., allow only photographers to upload images, only PAO designated employees may approve images).
The way geospatial data is searched, managed, processed and used has changed significantly in recent years. A data archive such as the one at the Alaska Satellite Facility (ASF), one of NASA's twelve interlinked Distributed Active Archive Centers (DAACs), used to be searched solely via user interfaces that were specifically developed for its particular archive and data sets. ASF then moved to using an application programming interface (API) that defined a set of routines, protocols, and tools for distributing the geospatial information stored in the database in real time. This provided a more flexible access to the geospatial data. Yet, it was up to user to develop the tools to get a more tailored access to the data they needed. We present two new approaches for serving data to users. In response to the recent Nepal earthquake we developed a data feed for distributing ESA's Sentinel data. Users can subscribe to the data feed and are provided with the relevant metadata the moment a new data set is available for download. The second approach was an Open Geospatial Consortium (OGC) web feature service (WFS). The WFS hosts the metadata along with a direct link from which the data can be downloaded. It uses the open-source GeoServer software (Youngblood and Iacovella, 2013) and provides an interface to include the geospatial information in the archive directly into the user's geographic information system (GIS) as an additional data layer. Both services are run on top of a geospatial PostGIS database, an open-source geographic extension for the PostgreSQL object-relational database (Marquez, 2015). Marquez, A., 2015. PostGIS essentials. Packt Publishing, 198 p. Youngblood, B. and Iacovella, S., 2013. GeoServer Beginner's Guide, Packt Publishing, 350 p.
This study aims to classify abstract content based on the use of the highest number of words in an abstract content of the English language journals. This research uses a system of text mining technology that extracts text data to search information from a set of documents. Abstract content of 120 data downloaded at www.computer.org. Data grouping consists of three categories: DM (Data Mining), ITS (Intelligent Transport System) and MM (Multimedia). Systems built using naive bayes algorithms to classify abstract journals and feature selection processes using term weighting to give weight to each word. Dimensional reduction techniques to reduce the dimensions of word counts rarely appear in each document based on dimensional reduction test parameters of 10% -90% of 5.344 words. The performance of the classification system is tested by using the Confusion Matrix based on comparative test data and test data. The results showed that the best classification results were obtained during the 75% training data test and 25% test data from the total data. Accuracy rates for categories of DM, ITS and MM were 100%, 100%, 86%. respectively with dimension reduction parameters of 30% and the value of learning rate between 0.1-0.5.
Large scale feature searches of accumulated collections of medical imagery are required for multiple purposes, including clinical studies, administrative planning, epidemiology, teaching, quality improvement, and research. To perform a feature search of large collections of medical imagery, one can either search text descriptors of the imagery in the collection (usually the interpretation), or (if the imagery is in digital format) the imagery itself. At our institution, text interpretations of medical imagery are all available in our VA Hospital Information System. These are downloaded daily into an off-line computer. The text descriptors of most medical imagery are usually formatted as free text, and so require a user friendly database search tool to make searches quick and easy for any user to design and execute. We are tailoring such a database search tool (Liveview), developed by one of the authors (Karshat). To further facilitate search construction, we are constructing (from our accumulated interpretation data) a dictionary of medical and radiological terms and synonyms. If the imagery database is digital, the imagery which the search discovers is easily retrieved from the computer archive. We describe our database search user interface, with examples, and compare the efficacy of computer assisted imagery searches from a clinical text database with manual searches. Our initial work on direct feature searches of digital medical imagery is outlined.