First, I’ll talk about TerraLib, a base library used for all components.

types, operators and access methods, 3) provide facilities for active databases (i.e., alerters and triggers) and inferencing including forward- and backward-chaining, 4) simplify the DBMS code for crash recovery, 5) produce a design that can take advantage of optical disks, workstations composed

Advancement in mobile computing technologies has prompted strong needs for database systems that can be used in small devices such as sensors, cellular phones, PDAs, car navigators, and Ultra Mobile PCs (UMPCs). We term the database systems that are customizable for small computing devices as Ubiquitous Database Management Systems (UDBMSs). In this paper, we first review the requirements of the UDBMS. The requirements identified include lightweight DBMSs, selective convergence, flash-optimized storage systems, data synchronization, support of unstructured/semistructured data, complex database operations, selfmanagement, and security. Next, we review existing systems and research prototypes. We review the functionality of UDBMSs including the footprint size, support of standard SQL, transaction management, concurrency control, recovery, indexing, and access control. We then review the supportability of the requirements by those UDBMSs surveyed. We finally present research issues related to the UDBMS. 1.

and using scale-less topological data efficiently in a client-

This package is available as open source. It is based on multi-vantage point trees (MVPT) [3]. This algorithm was chosen as the result of a study where the performance of an algorithm from each of the three major classes of distance-based index algorithm was compared using a suite of biological databases. The original MVPT is a main-memory data structure. We implemented the disk-based MVP index by fitting each index node into a disk page. Lastly, we designed new bulkload heuristics to improve query performance[7]. A special property of our implementation is that once an index for a dataset is constructed, a user may employ any of four different retrieval methods. In addition to range and k-nn queries, the package support range-limited k-nearest neighbor, and approximate range-limited k-nearest neighbor

We describe an interface to relational database management systems using SML and CML. This interface is used within the broad-scale bioinformatics data integration system called Kleisli. It extends the conventional flat relational data model supported by the query language SQL to a complex object data model. As a result, by going through this interface, a conventional flat relational data management system can be used transparently as a complex object store. 1.

detection, SAMOS executes rules attached to the occurred events. 1 Introduction Active database management systems (aDBMSs) [1] have recently found great interest as a topic of database research, and restricted aDBMS-functionality is even offered by some commercial relational systems. An aDBMS implements

METU Object-Oriented DBMS 1 includes the implementation of a database kernel, an object-oriented SQL-like language and a graphical user interface. Kernel functions are divided between a SQL Interpreter and a C++ compiler. Thus the interpretation of functions are avoided increasing the e ciency

in the data warehouse, stream processing, text, and scientific database markets. Assuming that specialized engines dominate these markets over time, the current relational DBMS code lines will be left with the business data processing (OLTP) market and hybrid markets where more than one kind of capability

To be fully usable, digital multimedia contents should be supported by a set of tools to query them, and more generally to manipulate them. This is one of the major goals of an audio database management system (DBMS). Existing work related to audio documents, e.g., radio or television archives