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<!--
	This ontology document is licensed under the Creative Commons
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 <channel rdf:about="http://ebiquity.umbc.edu//tag/html/visualization/?t=visualization">
  <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
  <title><![CDATA[UMBC ebiquity RSS Tag Search]]></title>
  <link><![CDATA[http://ebiquity.umbc.edu//tag/html/visualization/?t=visualization]]></link>
  <description><![CDATA[UMBC ebiquity RSS Tag Search for visualization]]></description>
  <items>
    <rdf:Seq>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/485/Generative-Adversarial-Networks-An-Introduction"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/342/Cost-Sensitive-Information-Acquisition-for-Prediction"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/314/Multivariate-Time-Series-Analysis-of-Physiological-and-Clinical-Data"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/178/Finding-knowledge-data-and-answers-on-the-Semantic-Web"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/171/Cost-Sensitive-Classifier-Evaluation-Using-Cost-Curves"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/143/Scalable-Visual-Comparison-of-Biological-Trees-and-Sequences"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/52/Emerging-Technologies-from-IBM-Research-for-Mobile-Workers"/>
      <rdf:li resource="http://ebiquity.umbc.edu/getnews/html/id/30/ELVIS-poster-wins-award"/>
      <rdf:li resource="http://ebiquity.umbc.edu/getnews/html/id/23/UMBC-and-IBM-collaborate-on-autonomic-computing"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/58/Voice-of-WordNet"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1148/SAGEViz-SchemA-GEneration-and-Visualization"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1068/Neural-Bregman-Divergences-for-Distance-Learning"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/891/Compressive-Geospatial-Analytics"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/900/Learning-from-Human-Robot-Interactions-in-Modeled-Scenes"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/726/Visualization-of-Pain-Severity-Events-Using-Semantic-Structures"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/743/Collaborative-data-mining-for-clinical-trial-analytics"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/514/Service-Oriented-Atmospheric-Radiances-SOAR-Gridding-and-Analysis-Services-for-Multisensor-Aqua-IR-Radiance-Data-for-Climate-Studies"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/390/A-Web-Service-Tool-SOAR-for-the-Dynamic-Generation-of-L1-Grids-of-Coincident-AIRS-AMSU-and-MODIS-Satellite-Sounding-Radiance-Data-for-Climate-Studies"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/353/Finding-Data-Knowledge-and-Answers-on-the-Semantic-Web"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/319/Using-the-Semantic-Web-to-Support-Ecoinformatics"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/153/ELVIS-the-Ecosystem-Location-Visualization-and-Information-System"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/205/Enron-wave"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/223/Finding-Data-Knowledge-and-Answers-on-the-Semantic-Web"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/202/Finding-knowledge-data-and-answers-on-the-Semantic-Web"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/225/Finding-knowledge-data-and-answers-on-the-Semantic-Web"/>
    </rdf:Seq>
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 </channel>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/485/Generative-Adversarial-Networks-An-Introduction">
  <title><![CDATA[Generative Adversarial Networks, An Introduction]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/485/Generative-Adversarial-Networks-An-Introduction</link>
  <description><![CDATA[While deep learning has made historic improvements in speech recognition and object recognition in recent years, almost all of these gains have been in supervised learning of now fairly well understood discriminative models. In the larger context of machine learning, less is understood about both unsupervised and generative models, but Generative Adversarial Networks have emerged as a promising approach to making progress in that direction. 

We are going to introduce Generative Adversarial...]]></description>
  <dc:date>2017-02-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/342/Cost-Sensitive-Information-Acquisition-for-Prediction">
  <title><![CDATA[Cost-Sensitive Information Acquisition for Prediction]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/342/Cost-Sensitive-Information-Acquisition-for-Prediction</link>
  <description><![CDATA[Machine learning systems have been increasingly used in our day-to-day
activities now. Just a few examples include handwritten character
recognition systems, product recommendation systems, face detection
features of cameras, speech recognition in hands-free devices, document
ranking by search engines, fraudulent activity detection for credit card
transactions, spam detection, and medical diagnosis. A critical
component of a machine learning system is the "information" needed to
develo...]]></description>
  <dc:date>2010-04-21</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/314/Multivariate-Time-Series-Analysis-of-Physiological-and-Clinical-Data">
  <title><![CDATA[Multivariate Time Series Analysis of Physiological and Clinical Data]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/314/Multivariate-Time-Series-Analysis-of-Physiological-and-Clinical-Data</link>
  <description><![CDATA[Patricia Ordóñez Rozo will talk abut her
PhD research

Multivariate Time Series Amalgams (MTSAs) provide an integrated,
multivariate approach to representing clinical and physiological
data. The hybrid representation automates the personalization of
baselines and thresholds based on a patient’s medical history while
also incorporating traditional baselines and thresholds. The
visualization of this representation captures the rate of change of
provider-selected parameters and the ...]]></description>
  <dc:date>2009-09-23</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/178/Finding-knowledge-data-and-answers-on-the-Semantic-Web">
  <title><![CDATA[Finding knowledge, data and answers on the Semantic Web]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/178/Finding-knowledge-data-and-answers-on-the-Semantic-Web</link>
  <description><![CDATA[Web search engines like Google have made us all smarter by providing ready access to the world's knowledge whenever we need to look up a fact, learn about a topic or evaluate opinions. The W3C's Semantic Web effort aims to make such knowledge more accessible to computer programs by publishing it in machine understandable form.

As the volume of Semantic Web data grows software agents will need their own search engines to help them find the relevant and trustworthy knowledge they need to per...]]></description>
  <dc:date>2006-10-11</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/171/Cost-Sensitive-Classifier-Evaluation-Using-Cost-Curves">
  <title><![CDATA[Cost-Sensitive Classifier Evaluation Using Cost Curves]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/171/Cost-Sensitive-Classifier-Evaluation-Using-Cost-Curves</link>
  <description><![CDATA[The evaluation of classifier performance in a cost-sensitive setting is 
straightforward if the operating conditions (misclassification costs and 
class distributions) are fixed and known. When this is not the case, 
evaluation requires a method of visualizing classifier performance 
across the full range of possible operating conditions. This talk argues 
that the classic technique for classifier performance visualization -- 
the ROC curve – is inadequate for the needs of researchers...]]></description>
  <dc:date>2006-09-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/143/Scalable-Visual-Comparison-of-Biological-Trees-and-Sequences">
  <title><![CDATA[Scalable Visual Comparison of Biological Trees and Sequences]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/143/Scalable-Visual-Comparison-of-Biological-Trees-and-Sequences</link>
  <description><![CDATA[We present the TreeJuxtaposer and SequenceJuxtaposer visualization
applications for comparing and browsing evolutionary trees and genomic
sequences, respectively. These systems use the Focus+Context
navigational metaphor of allowing users to fluidly stretch and shrink
parts of the view, as if manipulating a rubber sheet with the borders
tacked down. We introduce cognitive scalability to this approach by
guaranteeing the visibility of landmarks at all times, so that users can
stay orien...]]></description>
  <dc:date>2006-04-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/52/Emerging-Technologies-from-IBM-Research-for-Mobile-Workers">
  <title><![CDATA[Emerging Technologies from IBM Research for Mobile Workers]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/52/Emerging-Technologies-from-IBM-Research-for-Mobile-Workers</link>
  <description><![CDATA[This talk will include a presentation of several emerging technologies
from IBM Research related to supporting the way knowledge workers work
today including:

 MySpace, a web portal solution that supports personalized,
     role-based access to aplications through an interactive
     visualization of the physical space. MySpace combines localization
     information for colleagues, rooms and devices while aggregating
     data from various sources through a novel and simplified inter...]]></description>
  <dc:date>2004-10-13</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/getnews/html/id/30/ELVIS-poster-wins-award">
  <title><![CDATA[ELVIS poster wins award]]></title>
  <link>http://ebiquity.umbc.edu/getnews/html/id/30/ELVIS-poster-wins-award</link>
  <description><![CDATA[Our ELVIS
poster presented by Joel Sachs and Cyndy Parr at the NBII All-Nodes Meeting was
given an award for the poster generating the most interest.
The poster describes a suite of tools being build as part of the NSF
and USGS sponsored SPIRE project
that is exploring how semantic web technologies can be used by
ecological biologists.

The ELVIS (the Ecosystem Location Visualization and Information
System) tool suite is motivated by the belief that food web structure
plays a role i...]]></description>
  <dc:date>2005-10-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/getnews/html/id/23/UMBC-and-IBM-collaborate-on-autonomic-computing">
  <title><![CDATA[UMBC and IBM collaborate on autonomic computing]]></title>
  <link>http://ebiquity.umbc.edu/getnews/html/id/23/UMBC-and-IBM-collaborate-on-autonomic-computing</link>
  <description><![CDATA[University of Maryland, Baltimore County and IBM Collaborate on 
Autonomic Computing Research

BALTIMORE, February 24, 2005 - IBM today announced a new Shared University Research (SUR) grant awarded a group of faculty researchers of the eBiquity research group at the University of Maryland, Baltimore County to help build a major new center for high performance computational research. 

This SUR grant is part of the latest series of Shared University Research (SUR) awards, bringing IBM's ...]]></description>
  <dc:date>2005-02-24</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/58/Voice-of-WordNet">
  <title><![CDATA[Voice of WordNet]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/58/Voice-of-WordNet</link>
  <description><![CDATA[This is part hacking and part art.  Construct a multimedia, interactive visualization of the wordnet ontology.  The system would display a part of the wordnet graph centered on a particular lexical entry.  It would vocalize part of the entries definition via a standard text to speech application.  After some time (e.g., 10 seconds),  a random neighbor in the graph would be selected and the process repeated. Occasionally, the entire process would start over focused on a random entry to avoid b...]]></description>
  <dc:date>2004-12-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1148/SAGEViz-SchemA-GEneration-and-Visualization">
  <title><![CDATA[SAGEViz: SchemA GEneration and Visualization]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1148/SAGEViz-SchemA-GEneration-and-Visualization</link>
  <description><![CDATA[Schema induction involves creating a graph representation depicting how events unfold in a scenario. We present SAGEViz, an intuitive and modular tool that utilizes human-AI collaboration to create and update complex schema graphs efficiently, where multiple annotators (humans and models) can work simultaneously on a schema graph from any domain. The tool consists of two components: (1) a curation component powered by plug-and-play event language models to create and expand event sequences wh...]]></description>
  <dc:date>2023-12-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1068/Neural-Bregman-Divergences-for-Distance-Learning">
  <title><![CDATA[Neural Bregman Divergences for Distance Learning]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1068/Neural-Bregman-Divergences-for-Distance-Learning</link>
  <description><![CDATA[Many metric learning tasks, such as triplet learning, nearest neighbor retrieval, and visualization, are treated primarily as embedding tasks where the ultimate metric is some variant of the Euclidean distance (e.g., cosine or Mahalanobis), and the algorithm must learn to embed points into the pre-chosen space. The study of non-Euclidean geometries is often not explored, which we believe is due to a lack of tools for learning non-Euclidean measures of distance. Recent work has shown that Breg...]]></description>
  <dc:date>2023-05-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/891/Compressive-Geospatial-Analytics">
  <title><![CDATA[Compressive Geospatial Analytics]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/891/Compressive-Geospatial-Analytics</link>
  <description><![CDATA[Compressive sensing is a randomized data acquisition method that linearly samples sparse or compressible signals at a rate much below the Nyquist-Shannon sampling theorem, and outperforms traditional signal processing techniques through performing both sensing and size reduction tasks simultaneously. Edge-computing is a decentralization approach that provides several properties (specifically reducing the need for moving a large volume of data) via pushing the computation towards the edge of t...]]></description>
  <dc:date>2019-12-09</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/900/Learning-from-Human-Robot-Interactions-in-Modeled-Scenes">
  <title><![CDATA[Learning from Human-Robot Interactions in Modeled Scenes]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/900/Learning-from-Human-Robot-Interactions-in-Modeled-Scenes</link>
  <description><![CDATA[There is increasing interest in using robots in simulation to understand and improve human-robot interaction (HRI). At the same time, the use of simulated settings to gather training data promises to help address a major data bottleneck in allowing robots to take advantage of powerful machine learning approaches. In this paper, we describe a prototype system that combines the robot operating system (ROS), the simulator Gazebo, and the Unity game engine to create human-robot interaction scenar...]]></description>
  <dc:date>2019-07-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/726/Visualization-of-Pain-Severity-Events-Using-Semantic-Structures">
  <title><![CDATA[Visualization of Pain Severity Events Using Semantic Structures]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/726/Visualization-of-Pain-Severity-Events-Using-Semantic-Structures</link>
  <description><![CDATA[Physicians are often required to make critical medical decisions that may be based on previous events in the patient's health history.  However, these events may be very difficult to locate in the patient record due to the large volume of unstructured textual data in the patient's chart.  Even when the chart is housed in an electronic health record (EMR) system, keyword search within the chart may produce many results that are not relevant or that may overlook related expressions and concepts...]]></description>
  <dc:date>2016-02-03</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/743/Collaborative-data-mining-for-clinical-trial-analytics">
  <title><![CDATA[Collaborative data mining for clinical trial analytics]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/743/Collaborative-data-mining-for-clinical-trial-analytics</link>
  <description><![CDATA[his paper proposes a collaborative data mining technique to provide multi-level analysis from clinical trials data. Clinical trials for clinical research and drug development generate large amount of data. Due to dispersed nature of clinical trial data, it remains a challenge to harness this data for analytics. In this paper, we propose a novel method using master data management (MDM) for analyzing clinical trial data, scattered across multiple databases, through collaborative data mining. O...]]></description>
  <dc:date>2015-11-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/514/Service-Oriented-Atmospheric-Radiances-SOAR-Gridding-and-Analysis-Services-for-Multisensor-Aqua-IR-Radiance-Data-for-Climate-Studies">
  <title><![CDATA[Service-Oriented Atmospheric Radiances (SOAR): Gridding and Analysis Services for Multisensor Aqua IR Radiance Data for Climate Studies]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/514/Service-Oriented-Atmospheric-Radiances-SOAR-Gridding-and-Analysis-Services-for-Multisensor-Aqua-IR-Radiance-Data-for-Climate-Studies</link>
  <description><![CDATA[The Aqua spacecraft, launched on May 4, 2002, carries two well-calibrated independent infrared (IR) grating spectrometers Atmospheric Infrared Sounder (AIRS) and Moderate Resolution Imaging Spectrometer (MODIS), which have been continuously returning upwelling IR spectral radiance measurements for over five years. Based on an Aqua Sr. Project Review, estimates of available flight fuel, power, and orbital projections assess the life span of the Aqua satellite, and these two instruments, to be ...]]></description>
  <dc:date>2009-01-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/390/A-Web-Service-Tool-SOAR-for-the-Dynamic-Generation-of-L1-Grids-of-Coincident-AIRS-AMSU-and-MODIS-Satellite-Sounding-Radiance-Data-for-Climate-Studies">
  <title><![CDATA[A Web Service Tool (SOAR) for the Dynamic Generation of L1 Grids of Coincident AIRS, AMSU and MODIS Satellite Sounding Radiance Data for Climate Studies]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/390/A-Web-Service-Tool-SOAR-for-the-Dynamic-Generation-of-L1-Grids-of-Coincident-AIRS-AMSU-and-MODIS-Satellite-Sounding-Radiance-Data-for-Climate-Studies</link>
  <description><![CDATA[Three decades of Earth remote sensing from NASA, NOAA and DOD operational and research satellites carrying successive generations of improved atmospheric sounder instruments have resulted in petabytes of radiance data with varying spatial and spectral resolutions being stored at different data archives in various data formats by the respective agencies. This evolution of sounders and the diversities of these archived data sets have led to data processing obstacles limiting the science communi...]]></description>
  <dc:date>2007-06-19</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/353/Finding-Data-Knowledge-and-Answers-on-the-Semantic-Web">
  <title><![CDATA[Finding Data, Knowledge, and Answers on the Semantic Web]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/353/Finding-Data-Knowledge-and-Answers-on-the-Semantic-Web</link>
  <description><![CDATA[Web search engines like Google have made us all smarter by providing ready access to the world's knowledge whenever we need to look up a fact, learn about a topic or evaluate opinions. The W3C's Semantic Web effort aims to make such knowledge more accessible to computer programs by publishing it in machine understandable form. As the volume of Semantic Web data grows, software agents will need their own search engines to help them find the relevant and trustworthy knowledge they need to perfo...]]></description>
  <dc:date>2007-02-14</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/319/Using-the-Semantic-Web-to-Support-Ecoinformatics">
  <title><![CDATA[Using the Semantic Web to Support Ecoinformatics]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/319/Using-the-Semantic-Web-to-Support-Ecoinformatics</link>
  <description><![CDATA[We describe our on-going work in using the semantic web in
support of ecological informatics, and demonstrate a distributed
platform for constructing end-to-end use cases. Specifically, we
describe ELVIS (the Ecosystem Location Visualization and
Information System), a suite of tools for constructing food webs
for a given location, and Triple Shop, a SPARQL query interface
which allows scientists to semi-automatically construct
distributed datasets relevant to the queries they want to a...]]></description>
  <dc:date>2006-10-13</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/153/ELVIS-the-Ecosystem-Location-Visualization-and-Information-System">
  <title><![CDATA[ELVIS: the Ecosystem Location Visualization and Information System]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/153/ELVIS-the-Ecosystem-Location-Visualization-and-Information-System</link>
  <description><![CDATA[ELVIS (the Ecosystem Location Visualization and Information System) is a suite of tools motivated by the belief that food web structure plays a role in the success or failure of potential species invasions. Because very few ecosystems have been the subject of empirical foodweb studies,  response teams are typically unable to get quick answers to questions like]]></description>
  <dc:date>2005-10-31</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/205/Enron-wave">
  <title><![CDATA[Enron wave]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/205/Enron-wave</link>
  <description><![CDATA[This visualization shows the spread of information in a network.  The network is deived from the Enron email corpus.  Each node represents a person and nodes are linked if there were any email messages sent between the two people.]]></description>
  <dc:date>2006-10-10</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/223/Finding-Data-Knowledge-and-Answers-on-the-Semantic-Web">
  <title><![CDATA[Finding Data, Knowledge, and Answers on the Semantic Web]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/223/Finding-Data-Knowledge-and-Answers-on-the-Semantic-Web</link>
  <description><![CDATA[Web search engines like Google have made us all smarter by providing ready access to the world's knowledge whenever we need to look up a fact, learn about a topic or evaluate opinions. The W3C's Semantic Web effort aims to make such knowledge more accessible to computer programs by publishing it in machine understandable form. As the volume of Semantic Web data grows, software agents will need their own search engines to help them find the relevant and trustworthy knowledge they need to perfo...]]></description>
  <dc:date>2007-05-08</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/202/Finding-knowledge-data-and-answers-on-the-Semantic-Web">
  <title><![CDATA[Finding knowledge, data and answers on the Semantic Web]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/202/Finding-knowledge-data-and-answers-on-the-Semantic-Web</link>
  <description><![CDATA[Web search engines like Google have made us all smarter by providing ready access to the world's knowledge whenever we need to look up a fact, learn about a topic or evaluate opinions. The W3C's Semantic Web effort aims to make such knowledge more accessible to computer programs by publishing it in machine understandable form.

As the volume of Semantic Web data grows software agents will need their own search engines to help them find the relevant and trustworthy knowledge they need to per...]]></description>
  <dc:date>2006-10-08</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/225/Finding-knowledge-data-and-answers-on-the-Semantic-Web">
  <title><![CDATA[Finding knowledge, data and answers on the Semantic Web]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/225/Finding-knowledge-data-and-answers-on-the-Semantic-Web</link>
  <description><![CDATA[Web search engines like Google have made us all smarter by providing ready access to the world's knowledge whenever we need to look up a fact, learn about a topic or evaluate opinions. The W3C's Semantic Web effort aims to make such knowledge more accessible to computer programs by publishing it in machine understandable form. As the volume of Semantic Web data grows, software agents will need their own search engines to help them find the relevant and trustworthy knowledge they need to perfo...]]></description>
  <dc:date>2007-05-09</dc:date>
 </item>
</rdf:RDF>
