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.

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.