C o m m e N ta r y " " THE VISION: A RAPID LEARNING SYSTEM We envision a so-called federated approach to a national learning system. In a federated system, data remain in place until they are needed elsewhere for a particular purpose. Predicated on a policy framework that ensures public trust in the process, organizations that are members of a learning system are eligible to place queries to all other members who would then provide relevant information to address the query. Following are some examples of how such a learning system might operate.Example 1. An institution that is planning a clinical trial for a new drug to be tested in a specific class of patients wishes to know whether a sufficient number of such patients exists to support the trial as designed. This institution places a query to the learning system: "How many patients who meet these specific eligibility criteria does your institution have?" All members of the learning system would receive the query, and many would reply with an answer expressed as a numerator (the number of patients who fit the criteria) and possibly a denominator (the total number of patients evaluated) as well. This allows the institution that is planning the study to determine whether the proposed sample size is feasible and to develop an appropriately designed strategy for patient recruitment.Example 2. An outbreak of an infectious disease occurs in a specific part of the country, and the disease begins to spread. Once it is apparent that an outbreak has occurred, the learning system is mobilized to track the disease's spread. As new cases are diagnosed, these data are stored in the EHRs at health care practice sites. In response to a daily or more frequent query, electronic case reports are moved from each practice site to aggregation points in the local, state, and national public health system, making possible real-time nationwide surveillance of the spread of the disease.Example 3. A new drug is approved for routine use. The learning system is engaged to monitor the new drug's safety. As patients begin using the new drug, any side effects anticipated from the clinical trials are captured in the EHRs as part of the health care of these patients. In a manner that ensures individual privacy, these findings may be routinely transported in an automated manner from the EHRs in which they are collected to federal oversight agencies and to the company that is manufacturing the drug. In addition, researchers who suspect unanticipated adverse events could send a query to the learning system to ascertain the prevalence of such events in a national sample. In both scenarios, the reports supplied by participating members include not only the occurrence of the event but also contextual data that aid in the interpretation of adverse event information.Example 4. In Example 3, the myriad clinical data obtained from large numbers of patients who are taking a new drug may reveal that patients who display particular physiological characteristics would benefit from a modified dosage of the d...

???The original publication is available at www.springerlink.com???. Copyright Springer. [Full text of this article is not available in the UHRA]The Cognitive Dimensions of Notations framework has been created to assist the designers of notational systems and information artifacts to evaluate their designs with respect to the impact that they will have on the users of those designs. The framework emphasizes the design choices available to such designers, including characterization of the user???s activity, and the inevitable tradeoffs that will occur between potential design options. The resulting framework has been under development for over 10 years, and now has an active community of researchers devoted to it. This paper first introduces Cognitive Dimensions. It then summarizes the current activity, especially the results of a one-day workshop devoted to Cognitive Dimensions in December 2000, and reviews the ways in which it applies to the field of Cognitive Technology

The proposed fault-tolerant data communication setup has two main features: the consecutive transmission scheme that improves the reliability of message transmission, and the adaptive buffer management scheme that prevents message losses due to buffer overflow. The two features together reduce message retransmissions, and produce better channel reliability and system performance. The simulation data confirm that the adaptive buffer management scheme is indeed an effective reliability measure to prevent data overflow.

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