Presentation: Maturity models in BI

On Wednesday 1st October Ayca Tarhan will give a presentation on maturity models in Pav K.16, from 12:30-13:30.


A maturity model is an evolutionary roadmap for implementing the vital practices from one or more domains of organizational process, and Capability Maturity Model (CMM) for software development is considered as an effective model as being utilized by over 5000 businesses from over 70 countries worldwide. The reputation of CMM inspired consultants and researchers in various areas including construction, medical, finance, etc to develop and use maturity models in their own sectors. Business Intelligence (BI) is an area where such models are developed and adopted, and TDWI’s Business Intelligence Maturity Model (BIMM) and Gartner’s Maturity Model for Business Intelligence and Performance Management are the two known models. This presentation will provide first an overview of the definition and structure of a maturity model in general and CMM in specific, and then have a glance into the TDWI’s BIMM and a distinct Business Intelligence Maturity Model aimed for Healtcare domain.

Presentation: Building Clinical Data Repository: Challenges and Efforts

On Tuesday 17th Juni Xudong Lu will give a presentation on Building Clinical Data Repository: Challenges and Efforts in Pav K.16, from 12:30-13:30.


It’s important to integrate the information from standalone information sources to support the clinical workflow and decision making with more complete information of patients. As the evolution of healthcare becomes faster and faster, healthcare information becomes more and more complex and flexible. How to adapt to the change of healthcare information and achieve high quality healthcare information with standardized terminology are the most significant challenges of healthcare information technology and system. We would like to introduce our efforts and progress on these two challenges.

Presentation dr. Louis Rose

Speaker: dr. Louis Rose

Event Details

Title: “Towards A Scalable Cloud Platform for Search-Based Probabilistic Testing”

Abstract: Probabilistic testing techniques that sample input
data at random from a probability distribution can be more effective
at detecting faults than deterministic techniques. However,
if overly large (and therefore expensive) test sets are to be avoided,
the probability distribution from which the input data is sampled
must be optimised to the particular software-under-test. Such an
optimisation process is often resource-intensive. In this paper,
we present a prototypical cloud platform-and architecture-
that permits the optimisation of such probability distributions in
a scalable, distributed and robust manner, and thereby enables
cost-effective probabilistic testing.

Linguistic summaries of time series using fuzzy sets and their applications.

Presentation by Anna Wilbik, Thursday 23 May 14:30-15:30 in Paviljoen K.16.

Title: Linguistic summaries of time series using fuzzy sets and their applications.


I present the concept of linguistic summaries of time series. Basically, the linguistic summaries are interpreted in terms of the number or proportion of elements possessing a certain property. I provide two applications of linguistic summaries: one for analysis of performance of mutual (investment) fund, second in eldercare domain.

In case of mutual funds, summaries of time series we propose refer in fact to the summaries of trends (segments) identified with straight line segments of a piecewise linear approximation of time series. Such summaries exemplified by “among all segments, most are short” or in a more sophisticated form by “among all long segments, most are slowly increasing” can be easily interpreted using Zadeh’s calculus of linguistically quantified propositions.

In a case study from the eldercare domain the goal is to compare different nighttime patterns for change detection. The reasons for studying linguistic summaries for eldercare are twofold: first, linguistic summaries are the natural communication tool for health care providers in a decision support system, and second, due to the extremely large volume of raw data, these summaries create compact features for an automated reasoning for detection and prediction of health changes as part of the decision support system. We have developed a metric distance for our particular form of linguistic summaries. This has allowed the creation of linguistic prototypes from clusters of summaries over some temporal range. Using that, we present a method for detecting anomalies, as observations considerably different from the linguistic prototypes in a moving temporal window. An example demonstrate the utility of this approach.

First BPI Meeting


We had an interesting session with Job Visser on Tuesday 5th at 11.30 am, who is a BEP student doing his BEP project at Breda Hospital.