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Abstract:

Vertical information management (VIM) supports decision makers working within various levels of a management hierarchy, who seek information from potentially large, distributed, heterogeneous, and federated information sources. Decision makers are often overwhelmed by the volume of data which may be relevant and collectible, but overly detailed (e.g., from the breadth of open source data). Yet, the collected information must maintain its pedigree to allow access to detail on demand. VIM structures a top-down query refinement and bottom-up information collection process. We propose a VIM framework for specifying, refining, and partitioning a high-level information request which results in the extraction, collection, aggregation, and abstraction of the underlying data. A fundamental assumption of this work is that high-level information requests may involve data that is extracted or derived from underlying information sources, as well as data that is not present in the underlying information sources (referred to as "gaps"). We observe that current practice often involves manual processing and negotiation to select relevant information and to fill gaps. This framework includes specification at two levels: an abstract level, independent of the actual information sources used and a representational level to address the representational characteristics of the data within the information sources selected for the query. The top-down query refinement results in the abstract specification and the bottom-up information delivery is captured with the representational specification. This paper presents the VIM framework. 1

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