## 5 Assessment
### Case Study
Since our adapter concept enables us to provide privacy filters tailored to each type of data source, any data restriction is done in an appropriate manner. This ensures that certain types of data are only shared correctly or not at all (e.g., blood glucose data), while for others the accuracy can be reduced (e.g., location data). This way, the data meet the privacy requirements of the data subjects as well as the quality requirements of the physicians. In a discussion with parents and physicians at a diabetes workshop, both sides were generally satisfied with this, as the PMP transparently communicates the data usage of an application, while its privacy control does not render the application unusable. Specification of Tailored Data Products.Our second case study focuses on how effectively domain experts can specify tailored data products with our approach. For this purpose, we collaborated with food chemists. The number of people suffering from food allergies is constantly increasing. These allergies are in some cases life-threatening, which is  
Figure 8: Screenshots of the Health Game ‘Candy Castle’ Enhanced with PMP Features for Privacy Control. (**a**) Main Map of the Game. (**b**) Data Collection. (**c**) Privacy Control. why it is crucial that all ingredients are correctly indicated on a food product. Furthermore, control authorities are required to check the food products on a regular basis. Even the smallest particles of an allergen must be reliably detected even at the molecular level [233]. In our specific use case, we want to identify nut seeds in chocolate samples, since nut seeds are among the most prevalent food allergens which can trigger severe allergic shocks [234]. As part of the data preparation, the food chemists first determine the mass-to-charge ratio of the food samples with a mass spectrometer and use a chromatographic system to separate, identify, and quantify each component of the sample. The analysis data generated in this way are then checked against a protein sequence database to identify hazelnut or walnut peptides in the sample. Peptides are fragments of proteins, i.e., even the smallest traces of nut seeds can be detected this way. The samples for which the database indicates a match are marked. Only the marked samples need to be further analyzed, e.g., using peptide analysis software for manual analysis by a food chemist [235]. The data pipeline, which therefore has to be specified, has to identify and isolate all samples with marker peptides from the bulk of all samples and forward them to the peptide analysis software for in-depth analysis. Listing 1 shows the corresponding part of the ontology that is used to configure the data preparation in the REFINERY Platform as RDF/XML code. First of all, the partition of the Raw Data Zone has to be selected in which the captured peptide data on the chocolate samples are available, namely the partition with the label 'chocolate' (line 4 resp. line 4). For the data contained in this partition, the attribute 'walnut' (line 4) and the attribute 'hazelnut' (line 4) have to be processed. The processing logic to obtain high-level information is defined in line 4 as a simple lambda expression. The expression evaluates to true if and only if a data object has one of the two markers 'walnut' or 'hazelnut' or both of them. This expression is applied as a filter (line 4). Therefore, only the samples that have at least one of the two markers are stored in the Use Case Zone 'allergens' (line 4). This zone then serves as input data for the peptide analysis software, which can access it via the Data Delivery Zone. The feedback from the food chemists was positive, as this model-based description of complex data pipelines is feasible even without extensive programming knowledge. A significant advantage is that the domain experts do not have to deal with the different programming interfaces of the different data systems. Instead, they can describe the data preparation process at a higher level that abstracts from such programming details.