Reuse of high-level information requests: leveraging the investment

Vertical information management (VIM) is a term coined to describe a particular set of information management activities. These activities support decision makers working within various levels of a management hierarchy, who seek information from potentially large, distributed heterogeneous, and federated information sources. Decision makers usually require information beyond what is stored. Yet, the collected data is a valuable resource. This as particularly important for scientific experimental results where the samples are expensive to collect and analyze, as in environmental remediation and restoration. One sample from a storage tank containing nuclear waste can cost over $1000000. A fundamental assumption of the 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”). The authors observe that current practice often involves manual processing and negotiation to select relevant information and to fill gaps. They present a VIM framework for the specification, refinement, and partitioning of a high-level information request resulting in the extraction, collection, aggregation, and abstraction of the underlying data. This framework captures the specification of the information and the summarization steps used in a highly manual process to leverage the investment against future information requests. The work has been supported, in part, by the Department of Energy´s Pacific Northwest National Laboratory