In this work we discuss SDSPbMM, an integrated Strategy for Data Stream Processing based on Measurement Metadata, applied to an outpatient monitoring scenario. The measures associated to the attributes of the patient ...In this work we discuss SDSPbMM, an integrated Strategy for Data Stream Processing based on Measurement Metadata, applied to an outpatient monitoring scenario. The measures associated to the attributes of the patient (entity) under monitoring, come from heterogeneous data sources as data streams, together with metadata associated with the formal definition of a measurement and evaluation project. Such metadata supports the patient analysis and monitoring in a more consistent way, facilitating for instance: i) The early detection of problems typical of data such as missing values, outliers, among others;and ii) The risk anticipation by means of on-line classification models adapted to the patient. We also performed a simulation using a prototype developed for outpatient monitoring, in order to analyze empirically processing times and variable scalability, which shed light on the feasibility of applying the prototype to real situations. In addition, we analyze statistically the results of the simulation, in order to detect the components which incorporate more variability to the system.展开更多
Data, information and knowledge are recognized as useful assets for analysis, recommendation and decision making at any business level of an organization. Providing the right information for decision making considerin...Data, information and knowledge are recognized as useful assets for analysis, recommendation and decision making at any business level of an organization. Providing the right information for decision making considering different user-requirements, projects and situations is, however, a difficult issue. A frequently-neglected challenge is to cope with the influence of contextual issues affecting the success of outcomes and decisions. Particularly, when conducting quality evaluations in software organizations, it is of paramount importance to identify beforehand the contextual issues affecting outcomes and interpretations for measurement and evaluation projects. Therefore, the relevant context information should be clearly identified, specified and recorded for performing more robust analysis and recommendations. In this work, a domain-independent context model and a mechanism to integrate it to any application domain is presented. The context model is built upon a measurement and evaluation framework enabling quantification and semantic capabilities. The context model is then integrated in the mentioned framework itself to enable recommendations in meas- urement and evaluation projects.展开更多
文摘In this work we discuss SDSPbMM, an integrated Strategy for Data Stream Processing based on Measurement Metadata, applied to an outpatient monitoring scenario. The measures associated to the attributes of the patient (entity) under monitoring, come from heterogeneous data sources as data streams, together with metadata associated with the formal definition of a measurement and evaluation project. Such metadata supports the patient analysis and monitoring in a more consistent way, facilitating for instance: i) The early detection of problems typical of data such as missing values, outliers, among others;and ii) The risk anticipation by means of on-line classification models adapted to the patient. We also performed a simulation using a prototype developed for outpatient monitoring, in order to analyze empirically processing times and variable scalability, which shed light on the feasibility of applying the prototype to real situations. In addition, we analyze statistically the results of the simulation, in order to detect the components which incorporate more variability to the system.
文摘Data, information and knowledge are recognized as useful assets for analysis, recommendation and decision making at any business level of an organization. Providing the right information for decision making considering different user-requirements, projects and situations is, however, a difficult issue. A frequently-neglected challenge is to cope with the influence of contextual issues affecting the success of outcomes and decisions. Particularly, when conducting quality evaluations in software organizations, it is of paramount importance to identify beforehand the contextual issues affecting outcomes and interpretations for measurement and evaluation projects. Therefore, the relevant context information should be clearly identified, specified and recorded for performing more robust analysis and recommendations. In this work, a domain-independent context model and a mechanism to integrate it to any application domain is presented. The context model is built upon a measurement and evaluation framework enabling quantification and semantic capabilities. The context model is then integrated in the mentioned framework itself to enable recommendations in meas- urement and evaluation projects.
