Image annotation becomes increasingly important for clinical applications and medical research. In particular, collaborative image annotations can harness the collective intelligence from distributed experts. There are several challenges to support collaborative medical image annotations: i) Medical image annotation includes not only metadata annotation but also multimedia annotation, such as graphical annotation. The latter often requires a heavy-duty tool, which can be difficult to realize in a distributed environment; ii) Annotations need to be well modeled for easy exchange and support of queries, i.e., there is a gap between image annotation and content retrieval; and iii) An annotation platform is needed to provide authoring tools and the collaborative infrastructure. Meanwhile, the Web is evolving quickly on supporting interaction, participation and collaboration enabled by Web 2.0 technologies. Among them, scalable vector graphics (SVG) now becomes a standard language for vector graphics on the Web natively supported by latest Web browsers. In our work, we develop a collaborative image annotation platform, which provides: i) a flexible data model to support both metadata and multimedia annotations on 2-D medical images; ii) SVG based implementation of the data model that can support complex textual, spatial, and collaborative queries on annotations with XQuery; iii) a lightweight native Web browser enabled annotation authoring tool without any plugin needed; and iv) an architecture that provides authoring, storing, querying, and exchanging of annotations, and supports Web-based collaboration.

Image annotation is becoming increasingly important for clinical applications and medical research. Especially, collaborative image annotation can harness the collective intelligence from distributed users. There are several challenges to model medical image annotations: i) Medical image annotation includes not only textual annotation but also graphical annotation, which can consist of multiple areas or layers; ii) To support collaborative annotation from multiple users, collaboration has to be supported and represented in a proper way; Hi) Both textual and graphical annotations should be searchable, e.g., support of spatial queries; iv) annotation history needs to be tracked and searchable in applications such as clinical trials; and v) To enable convenient annotation, and save cost, lightweight system should be provided. Most current medical image annotation applications are workstation based applications, and use proprietary methods to represent annotations, which make it difficult to search, share, and exchange annotations. Meanwhile, the Web is evolving quickly on supporting strong collaboration through several new technologies, including Ajax (Asynchronous JavaScript and XML) and SVG (Scalable Vector Graphics). Especially, SVG now becomes a standard language for vector graphics on the Web, which, indeed, is recently natively supported by latest Web browsers. This brings a new opportunity to support collaborative image annotations on the Web. In our work, we develop a comprehensive data model to support both textual and graphical annotations and their history on 2-D medical images, and implement the data model with the standard language SVG. This data model can support powerful queries on annotations including complex textual, spatial, collaboration, group, and history queries based on standard XML Query language XQuery. Besides, the approach can be used to support collaborative image annotations in a lightweight Web browser environment.

RFID technology provides significant advantages over traditional object-tracking technologies and is increasingly adopted and deployed in real applications. RFID applications generate large volume of streaming data, which have to be automatically filtered, processed, and transformed into semantic data, and integrated into business applications. Indeed, RFID data are highly temporal, and RFID observations form complex temporal event patterns which can be very different for various RFID applications. Thus, it is desirable to have a general RFID data processing framework with a powerful language, for the end users to express a variety of queries on RFID data streams, as well as detecting complex events patterns. While data stream management systems (DSMSs) are emerging for optimized stream data processing, they usually lack the language construct support for temporal event detection. In this paper, we discuss a stream query language to provide comprehensive temporal event detection, through temporal operators and extension of sliding-window constructs. With the integration of temporal event detection, a DSMS has the capability to serve as a powerful system for RFID data processing.

Scientific research becomes increasingly reliant on collaborative effort among multiple institutions and interdisciplinary consortia, through sharing scientific experiments and data and collaboration on analysis of data and results. Besides information sharing, there is a growing need to create a framework to enable collaborative, cross-disciplinary research, which can facilitate a research community into a default mode of collaboration, including: i) enabling scientific researchers to dynamically interact with others, collaboratively author, annotate, review, comment on others' data, and discuss their research; ii) providing a dynamic collaboration environment by harnessing collective contributions from a group of researchers; and iii) facilitating broader participation of people into research projects. While traditional data management and integration systems put much focus on passively integrating existing data, the collaboration among data providers and users is quite limited. In this paper, we present a Web-based collaborative platform to dynamically integrate information for scientific research. Besides data integration, the system provides essential collaboration capabilities to boost user participation and collaboration. The system will not only enable users as active information contributors to bring significant new values to the data, but also provide an environment for scientific researchers to do collaborative research in a large research community.

RFID can be used for identifying, locating, tracking and monitoring physical objects without line of sight, and thus can be used in a wide range of pervasive computing applications. To achieve these goals, RFID data have to be collected, transformed and expressively modeled as their counterparts in the virtual world. To this end, in this paper, we propose a general framework for modeling RFID data. We first explore the fundamental characteristics of RFID applications and classify applications into a set of basic scenarios based on these characteristics. We then develop constructs for modeling each basic scenario, which can be integrated to model complex RFID applications in real world as demonstrated in our case study.

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Scientific research in many fields is increasingly a collaborative effort across multiple institutions and disciplines. Scientific researchers need not only an effective system to manage their data, results, and the experiments that generate the results, but also a platform to integrate, share and search these across multiple institutions. Therefore, researchers are able to reuse experiments, pool expertise and validate approaches. In this paper, we present Sci- Port, a system of experiment management and integration for collaborative scientific research. SciPort’s architecture uses i) a general transformation-based data model to represent and link experiment processes; ii) hierarchical data classification across multiple institutions according to research programs’ goals and organization; iii) metadatacentric representation that concisely captures the context of experiments; and iv) virtual data integration through centralized metadata integration. The system is built for open source, and the metadata-based representation and integration provides a unified framework and tool set to manage and share experiments for scientific research communities.

Document processing and understanding is important for a variety of applications such as office automation, creation of electronic manuals, online documentation and annotation etc. The first step towards this process often involves the extraction of relevant keywords and phrases from the documents so that they can be automatically hyperlinked within and outside the document so that we can create an electronic document. This paper describes a novel method for extracting anchorable information units (AIUs), also known as hotspots from any type of portable document format (PDF) files, which may either be created using either an editor or by scanning in documents. The AIUs are used to make these documents more intelligent for content cross-referencing to/from related multimedia documents within an electronic document publishing environment. Domain specific knowledge about the documents are used to aid the extraction process. Once the location and extent of the texts are found, the content is extracted through the use of an optical character recognition (OCR) software if necessary. For the case of object extraction for highlighting, first the images are extracted and then a variety of image processing algorithms are applied.

The product training manuals for complex machinery often consist of large-scale presentation-based documents with rich media. The content of the manuals is typically required to use up-to-date product information for effective training. Current training authoring tools have limitations in creating such large-scale product training course content in a timely manner due to the labor-intensive and time-consuming authoring processes. This paper presents an automated method to improve the process. It is based on formal specifications to dynamically generate DSSSL document styles for transforming the existing storage-based product documents into large-scale presentation-based product training manuals. The generated manuals are based on SCORM, an industry training course specification.

We highlight major technical requirements for designing and developing future distributed multimedia information systems using Internet technology. The key requirements of this system are to allow users to access and search and to communicate multimedia documents consisting of text, audio, video and images. We emphasize the role of object-oriented technology for information management and real-time communication protocols to guarantee QoS. We present a reference architecture for a Web-based real-time distributed multimedia system which integrates enabling technologies including real-time streaming, multimedia indexing and searching and distributed object management.