Modeling continuous integration practice differences in industry software development

Although the repair of ventral abdominal wall hernias is one of the most commonly performed operations, many aspects of their treatment are still under debate or poorly studied. In addition, there is a lack of good definitions and classifications that make the evaluation of studies and meta-analyses in this field of surgery difficult. Under the auspices of the board of the European Hernia Society and following the previously published classifications on inguinal and on ventral hernias, a working group was formed to create an online platform for registration and outcome measurement of operations for ventral abdominal wall hernias. Development of such a registry involved reaching agreement about clear definitions and classifications on patient variables, surgical procedures and mesh materials used, as well as outcome parameters. The EuraHS working group (European registry for abdominal wall hernias) comprised of a multinational European expert panel with specific interest in abdominal wall hernias. Over five working group meetings, consensus was reached on definitions for the data to be recorded in the registry. A set of well-described definitions was made. The previously reported EHS classifications of hernias will be used. Risk factors for recurrences and co-morbidities of patients were listed. A new severity of comorbidity score was defined. Post-operative complications were classified according to existing classifications as described for other fields of surgery. A new 3-dimensional numerical quality-of-life score, EuraHS-QoL score, was defined. An online platform is created based on the definitions and classifications, which can be used by individual surgeons, surgical teams or for multicentre studies. A EuraHS website is constructed with easy access to all the definitions, classifications and results from the database. An online platform for registration and outcome measurement of abdominal wall hernia repairs with clear definitions and classifications is offered to the surgical community. It is hoped that this registry could lead to better evidence-based guidelines for treatment of abdominal wall hernias based on hernia variables, patient variables, available hernia repair materials and techniques.

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EuraHS: the development of an international online platform for registration and outcome measurement of ventral abdominal wall hernia repair.

Knowledge-based Configuration incorporates knowledge representation formalisms to capture complex product models and reasoning methods to provide intelligent interactive behavior with the user. This book represents the first time that corporate and academic worlds collaborate integrating research and commercial benefits of knowledge-based configuration. Foundational interdisciplinary material is provided for composing models from increasingly complex products and services. Case studies, the latest research, and graphical knowledge representations that increase understanding of knowledge-based configuration provide a toolkit to continue to push the boundaries of what configurators can do and how they enable companies and customers to thrive.Includes detailed discussion of state-of-the art configuration knowledge engineering approaches such as automated testing and debugging, redundancy detection, and conflict management Provides an overview of the application of knowledge-based configuration technologies in the form of real-world case studies from SAP, Siemens, Kapsch, and more Explores the commercial benefits of knowledge-based configuration technologies to business sectors from services to industrial equipment Uses concepts that are based on an example personal computer configuration knowledge base that is represented in an UML-based graphical language

Knowledge-Based Configuration: From Research to Business Cases

Summary 1. Plant traits are fundamental for understanding and predicting vegetation responses to global changes, and they provide a promising basis towards a more quantitative and predictive approach to ecology. As a consequence, information on plant traits is rapidly accumulating, and there is a growing need for efficient database tools that enable the assembly and synthesis of trait data. 2. Plant traits are highly heterogeneous, exhibit a low degree of standardization and are linked and interdependent at various levels of biological organization: tissue, organ, plant and population. Therefore, they often require ancillary data for interpretation, including descriptors of the biotic and abiotic environment, methods and taxonomic relationships. 3. We introduce a generic database structure that is tailored to accommodate plant trait complexity and is consistent with current theoretical approaches to characterize the structure of observational data. The over-arching utility of the proposed database structure is illustrated based on two independent plant trait database projects. 4. The generic database structure proposed here is meant to serve as a flexible blueprint for future plant trait databases, improving data discovery, and ensuring compatibility among them.

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A generic structure for plant trait databases

Recently, Semantic Wikis showed reasonable success as collaboration platforms in the context of social semantic applications. In this paper, we present a novel approach, that interprets the concept of Semantic Wikis as a knowledge engineering environment, that effectively help to build decision-support systems. We introduce the Semantic Wiki KnowWE, that provides the possibility to define and maintain ontologies together with strong problem-solving knowledge. Thus, the wiki can be used to collaboratively build decision-support systems. These enhancements require extensions of the standard Semantic Wiki architecture by a task ontology for problem-solving and an adapted reasoning process. We discuss these extensions in detail, and we describe a case study in the field of medical emergency systems.

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KnowWE: a Semantic Wiki for knowledge engineering

In spite of their industrial success, the development of intelligent systems is still a complex and risky task. When building intelligent systems, we see that domain knowledge is often present at different levels of formalization-ranging from text documents to explicit rules. In this paper, we describe the knowledge formalization continuum as a metaphor to help domain specialists during the knowledge acquisition phase. To make use of the knowledge formalization continuum, the agile use of knowledge representations within a knowledge engineering project is proposed, as well as transitions between the different representations, when required. We show that a semantic wiki is a flexible tool for engineering knowledge on the knowledge formalization continuum. Case studies are taken from one industrial and one academic project, and they illustrate the applicability and benefits of semantic wikis in combination with the knowledge formalization continuum.

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Engineering intelligent systems on the knowledge formalization continuum

This paper presents a collaborative knowledge engineering approach based on the widespread wiki technique.The interface of a standard wiki system is extended to allow for the capture, the maintenance and the use of knowledge systems.

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KnowWE: community-based knowledge capture with knowledge wikis

Knowledge wikis extend normal wikis by the representation of explicit knowledge. In contrast to semantic wikis the defined knowledge is mainly used for knowledge–intensive tasks like collaborative recommendation and classification. In this paper, we introduce a prototype implementation of a knowledge wiki, and we discuss appropriate markups for problem–solving knowledge to be used in knowledge wikis. The main aspect of the proposed markups is their simplicity and compactness, since it is aimed that these markups are used by normal wiki users. Case studies report on practical experiences we have made with the development of various knowledge wikis.

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Markups for Knowledge Wikis.

A couple of semantic wikis have been proposed to serve as collaborative knowledge engineering environments – however, the knowledge of almost all systems is currently based on the expressiveness of OWL (Lite/DL). In this paper we present the concept of a semantic knowledge wiki that extends the capabilities of semantic wikis by strong problem-solving methods. We show how problem-solving knowledge is connected with standard ontological knowledge using an upper ontology. Furthermore, we discuss different possibilities to formalize problemsolving knowledge, for example by semantic knowledge annotation, structured text and explicit markups.

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Jochen Reutelshoefer

Papers

KnowWE: a Semantic Wiki for knowledge engineering

Engineering intelligent systems on the knowledge formalization continuum

KnowWE: community-based knowledge capture with knowledge wikis

Markups for Knowledge Wikis.

Ad-Hoc Knowledge Engineering with Semantic Knowledge Wikis.