here a new database called “ImageNet”, a largescale ontology of images built upon the backbone of the WordNet structure. ImageNet aims to populate the majority of the 80,000 synsets of WordNet with an average of 500-1000 clean and full resolution images. This will result in tens of millions

Research on ontology is becoming increasingly widespread in the computer science community, and its importance is being recognized in a multiplicity of research fields and application areas, including knowledge engineering, database design and integration, information retrieval and extraction. We

Semantic integration has been a long-standing challenge for the database community. It has received steady attention over the past two decades, and has now become a prominent area of database research. In this article, we first review database applications that require semantic integration

and other research outputs The usage of best practices and procedures in the database community

INTRODUCTION As a result of the rapidly growing number of organizations conducting business over the Web, a large number of heterogeneous information sources (e.g., home pages, tabular data, online digital libraries) is now readily available. The ability to efficiently and effectively share data on the Web is a critical step towards the development of the so-called information superhighway. Existing organizations would form online alliances to deliver integrated value-added information sources (e.g., ecatalogs, information portals). The evolution into the global information infrastructure and the concomitant increase in the available information, is offering a powerful distribution vehicle for organizations that need to coordinate the use of multiple information sources. However, the technology to organize, search, integrate, and evolve these sources has not kept pace with the rapid growth of the available information space. The efficient sharing of Web data is especially challenging

The problem of indexing time series has attracted much research interest in the database community. Most algorithms used to index time series utilize the Euclidean distance or some variation thereof. However is has been forcefully shown that the Euclidean distance is a very brittle distance

. In addition to surveying the state of the art, this paper also identifies some promising research issues, some of which are related to problems that the database research community has worked on for years, but others are only just beginning to be addressed. This overview is based on a tutorial

Abstract. While we can take as a fact \the Web changes everything", we argue that \XML is the means " for such a change to make a sig-ni cant step forward. We therefore regard XML-related research as the most promising and challenging direction for the community of database researchers

Cloud-computing is transforming many aspects of data management. Most recently, the cloud is seeing the emergence of digital markets for data and associated services. We observe that our community has a lot to offer in building successful cloud-based data markets. We outline some of the key

The database research community prides itself on scalable technologies. Yet database systems traditionally do not excel on one important scalability dimension: the degree of distribution. This limitation has hampered the impact of database technologies on massively distributed systems like