In a video database, large amount of information involving video, audio, and/or images needs to be stored and managed. Therefore, there is an important need for novel techniques and systems which can provide an efficient retrieval facility of the voluminous data stored in the video database. While `content-based' retrieval provides a direct and an intuitive approach for video data access, it is inadequate from efficient video data management viewpoint. This is because many (semantic) features of video data can not be extracted out from the video itself automatically; moreover, video objects may share annotations or descriptions. Consequently, it is necessary and cost- effective to complement content-based retrieval with high level (declarative) query-based retrieval in the video database system. In this paper, we describe a high level query language called CAROL (for Cluster And ROle Language), which is being developed on top of a versatile object database system. Supported by the underlying object model extended with clusters and roles, CAROL offers a number of interesting features which are seldomly available from another single query language, including top-down search in a context-dependent manner, bottom-up and/or horizontal search in a context-independent manner, besides traditional search supported by conventional object-oriented database systems. This language constitutes an important component of an on-going project aiming at developing a declarative video data retrieval system at the Hong Kong Polytechnic University.