This paper describes the development of the ldquoEBoxrdquo, a system that provides integrated access to a wide variety of information sources relevant to providing situational awareness during emergency response situations. The EBox exemplifies a novel information integration approach in which both pre-existing data and real-time information streams are obtained from multiple sources and are rapidly and intelligently ingested and registered to faclilitate efficient and integrated access at a later time. We describe the design and development of the EBox, and the deployment experience in a drill and demonstration exercise. We further describe key technical challenges that remain and our ongoing research efforts in addressing such challenges.

In this paper we develop a disambiguation algorithm and then study its impact on People Search. The proposed algorithm first uses extraction techniques to automatically extract `significant' entities such as the names of other persons, organizations, and locations on each Web page. In addition, it extracts and parses HTML and Web related data on each Web page, such as hyperlinks and email addresses. The algorithm then views all this information in a unified way: as an entity-relationship graph where entities (e.g., people, organizations, locations, Web pages) are interconnected via relationships (e.g., `Web page-mentions-person', relationships derived from hyperlinks, etc). The algorithm gains its power by being able to analyze several types of information: attributes associated with the entities (e.g., TF/IDF for Web pages) and, most importantly, direct and indirect interconnections that exist among entities in the ER graph. We next outline our approach in Section 2 and then compare it with the state of the art solutions in Section 3.

This paper describes our work on developing technology for rapidly assembling information portals that provide integrated access to and analysis of information from multiple sources in the case of any disaster. Many recent disasters (the S.E. Asian Tsunamis, the London subway bombings, the Katrina hurricane, to name a few) have demonstrated that a lot of valuable information becomes available in the hours and days immediately following the disaster, and such information is indeed valuable to disaster managers or even citizens in their response. In this paper we describe our work on developing information portals for disasters in general; we describe many key information processing capabilities and challenges that we consider important in such portals and also describe our approach to developing such capabilities.

In this paper we describe an approach and system for managing enterprise semi-structured data that is high-throughput, nimble, and scalable. We present the NETMARK system, which provides for a "schemaless" way of managing semi-structured documents. We describe in particular detail the unique underlying data storage approach and efficient query processing mechanisms given this storage system. We present an extensive benchmark evaluation of the NETMARK system and also compare it with related XML management systems. At the heart of the approach is the philosophy of a focus on most common data management requirements in the enterprise, and not burdening users and application developers with unnecessary complexity and formal schemas.

The goal of EII systems is to provide uniform access to multiple data sources without having to first load them into a data warehouse. Since the late 1990's, several EII products have appeared in the marketplace and significant experience has been accumulated from fielding such systems. This collection of articles, by individuals who were involved in this industry in various ways, describes some of these experiences and points to the challenges ahead.

This paper describes an approach to achieving data integration across multiple sources in an enterprise, in a manner that does not require heavy investment in database and middleware maintenance. This "lean" approach to integration leads to cost-effectiveness and scalability of data integration in the enterprise.

There is currently great interest in building information mediators that can integrate information from multiple data sources such as databases or Web sources. The query response time for such mediators is typically quite high, mainly due to the time spent in retrieving data from remote sources. We present an approach for optimizing the performance of information mediators by selectively materializing data. We first present our overall framework for materialization in a mediator environment. The data is materialized selectively. We outline the factors that are considered in selecting data to materialize. We present an algorithm for identifying classes of data to materialize by analyzing one of the factors which is the distribution of user queries. We present results with an implemented version of our optimization system for the Ariadne information mediator, which show the effectiveness of our algorithm in extracting patterns of frequently accessed classes from user queries. We also demonstrate the effectiveness of approach in optimizing mediator performance by materializing such classes.

The Web is based on a browsing paradigm that makes it difficult to retrieve and integrate data from multiple sites. Today, the only way to do this is to build specialized applications, which are time-consuming to develop and difficult to maintain. We have addressed this problem by creating the technology and tools for rapidly constructing information agents that extract, query, and integrate data from web sources. Our approach is based on a uniform representation that makes it simple and efficient to integrate multiple sources. Instead of building specialized algorithms for handling web sources, we have developed methods for mapping web sources into this uniform representation. This approach builds on work from knowledge representation, databases, machine learning and automated planning. The resulting system, called Ariadne, makes it fast and easy to build new information agents that access existing web sources. Ariadne also makes it easy to maintain these agents and incorporate new sources as they become available.

There is currently great interest in building information mediators that can integrate information from multiple data sources such as databases or Web sources. The query response time in such mediators is typically quite high. We present an approach for optimizing the performance of information mediators by selectively materializing data. We first present our overall framework for materialization in a mediator environment. We then stress the need to materialize data selectively and outline the factors that must be considered to select data to materialize. We present an algorithm for identifying classes of data to materialize by analyzing one of the factors which is the distribution of user queries. We present results with an implemented version of our optimization system for the Ariadne information mediator which show significant performance improvement over no materialization and existing schemes such as page level caching.

The Web is based on a browsing paradigm that makes it difficult to retrieve and integrate data from multiple sites. Today, the only way to achieve this integration is by building specialized applications, which are time-consuming to develop and difficult to maintain. We are addressing this problem by creating the technology and tools for rapidly constructing information mediators that extract, query, and integrate data from web sources. The resulting system, called Ariadne, makes it feasible to rapidly build information mediators that access existing web sources.

To simplify the task of obtaining information from the vast number of information sources that are available on the World Wide Web (WWW), the authors are building information mediators for extracting and integrating data from multiple Web sources. In a mediator based approach, wrappers are built around individual information sources to translate between the mediator query language and the individual sources. They present an approach for semi-automatically generating wrappers for structured Internet sources. The key idea is to exploit formatting information in Web pages to hypothesize the underlying structure of a page. From this structure the system generates a wrapper that facilitates querying of a source and possibly integrating it with other sources. They demonstrate the ease with which they are able to build wrappers for a number of Web sources using their implemented wrapper generation toolkit.