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Background Team-sport players have a particularly high injury risk. Although female sex is considered a risk factor, it is still unknown whether female and male team-sport players, in fact, differ in their injury rates. We aimed to compare injury rates between female and male players by systematically reviewing and meta-analyzing injury surveillance studies of both sexes in order to evaluate sex-specific differences in team-sport injuries. Methods Studies that prospectively collected injury data for high-level female and male players (age ≥16 years) in basketball, field hockey, football (soccer), handball, rugby (union and sevens), and volleyball were included. Two reviewers (AZ and AL) independently assessed study quality and extracted data for overall, match, training, and severe injuries (>28 days’ time loss) as well as data regarding injury locations and types. Incidence rate ratios (IRRs) were pooled in a meta-analysis, and meta-regression analysis was performed when 10 or more studies were available. Results Of 20 studies, 9 studies reported injury data from football, 3 studies from rugby, 3 studies from handball, 1 study from basketball, 1 study from field hockey, 2 studies from volleyball, and 1 study from basketball and field hockey. For overall injuries, the pooled IRR (0.86; 95% confidence interval (95%CI): 0.76−0.98) indicated significantly more injuries in male than in female players. For injury location, the pooled IRR showed higher injury rates in male athletes than in female athletes for upper extremity, hip/groin, thigh, and foot injuries. Female players had a significantly higher rate of anterior cruciate ligament injuries (IRR = 2.15, 95%CI: 1.27−3.62) than male players. No significant sex-specific differences in IRR were found for match, training, severe injuries, concussions, or ankle sprains. Conclusion Our meta-analysis provides evidence for sex-specific differences in the injury rates in team sports. Further epidemiological studies including both sexes in sports other than football are needed in order to strengthen the evidence.

The importance of the Internet for job procurement is increasing for the reason that three quarters of the people in the employment age are online. On the other hand because ever more companies are publishing their job offers on the Web. However, due to the large number of openings published online it is almost impossible for job seekers and job portals to gain an overview of the entire employment market. Since job offers lack semantically meaningful annotations, the search and integration into databases are made highly difficult. Applying Semantic Web technologies to the e-recruitment process provides advantages for all participants in the market. In this paper we describe a method for analysing the domain-specific language of an application domain. We use this method to describe the e-recruitment process and the necessary ontologies for annotating job offers and job applications. In conclusion, we present the prototypical implementation of the scenario based on Semantic Web, especially semantic matching.

The objective of this chapter is to describe and evaluate an approach for the automated analysis of business process models. It is described why an automated way of process analysis is necessary and why it is beneficial to use our approach. As business process models are moving in the center of decision making, it is important for the corresponding decision makers to get transparent, fast, and comprehensive results of process analysis. Dealing with huge amount of data this is only possible with automated support. Based on a comprehensive literature study, we identified different deviations and conflicts that usually arise in business process modeling projects. The class of semantic building block-based languages which combines structural modeling elements with corresponding domain semantics can help avoiding these conflicts. Beside the conceptual development of the language class we conducted an empirical evaluation of PICTURE, a business process modeling language that is an instantiation of semantic building block-based languages. Our results show that (a) our derived language class is applicable, (b) modeling conflicts significantly can be reduced, and (c) modeled data can be analyzed automatically.

This work presents an auto-completion mechanism for supporting the creation of executable business process models. Currently, process modeling tools provide only little support to identify the relevant services that are needed to execute the process model – the selection of appropriate services is left to the skills of the modeler. A novel solution technique for this problem is proposed here as the combination of (1) a context-based analysis, (2) by taking pre and post-conditions into account, and by (3) evaluating the non-functional properties of the functionally and context-wise fitting services.

Within the public sector domain there is great potential for business process optimization through ICT. However, until today these possibilities remain largely unexploited. To measure the impact of ICT-investments all processes of a public administration have to be taken into account. The PICTURE modelling method has been proposed as a way to efficiently model the whole process landscape of a public administration. Based on the processes captured, the impact of certain ICT functionalities can be analyzed. ICT investment decisions become more transparent towards the political leadership which are the decision makers in the public sector. This paper has two research objectives: First, an architecture for an semi-automated evaluation of ICT investment decisions is introduced. Second, the practical feasibility of the architecture is shown based on an investment decision for a document management system.

The chapter sketches a holistic approach to semantically validating conceptual models. The quality and thus the validation of conceptual models are of high economic importance. However, only little empirical work has focused on their evaluation so far. This raises the question whether a holistic approach to determining the quality of conceptual models is available yet. In order to describe the current state of research and to expose the so far neglected research fields we develop a two dimensional framework. With the help of this framework we can identify a notable shortcoming on conceptual model evaluation. We can show that there is actually no approach that covers all aspects of the framework. Hence, we describe a procedure model that integrates different evaluation techniques. This procedure model provides a starting point to further elaborate on a holistic evaluation approach.

In this paper a domain specific process modelling method for public administrations is presented. The public sector is facing an increased service level demand from citizens and companies which comes along with reduced financial scope. Higher process efficiency as well as time and cost savings are required to cope with this challenge. However, reorganisation projects in public administrations with established generic process modelling methods could only identify limited reorganisation potential and just led to small local improvements [1]. Therefore, we have created the domain specific modelling approach PICTURE. The PICTURE-method applies the domain vocabulary to efficiently capture the process landscape of a public organisation. Thus, PICTURE creates process transparency and is able to detect holistic reorganisation potentials within the entire administration.