Daniel Wilms

Daniel Wilms
SPREAD GmbH

Diplom

About

18
Publications
7,457
Reads
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128
Citations
Citations since 2016
18 Research Items
128 Citations
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201620172018201920202021202201020304050
201620172018201920202021202201020304050

Publications

Publications (18)
Preprint
Full-text available
With almost every new vehicle being connected, the importance of vehicle data is growing rapidly. Many mobility applications rely on the fusion of data coming from heterogeneous data sources, like vehicle and ”smart-city” data or process data generated by systems out of their control. This external data determines much about the behaviour of the re...
Conference Paper
Full-text available
Vehicle software architectures have been evolving over the last twenty years to support data-driven functionalities. Several enterprises from different domains are currently focusing on improving their data architectures by re-defining the underlying data models to enable core support for analytics and artificial intelligence. Moreover, a common de...
Preprint
Full-text available
The variety of vehicle data has motivated contributors from the automotive industry to develop and maintain the so-called Vehicle Signal Specification. As the semantics of the specification are limited to a tree-like hierarchy and data types, it has been considered for the foundation of a more expressive model in an ontology form. Since the first d...
Preprint
Full-text available
A vehicle produces a wide variety of data streams. To maximize their immediate use, we require to interpret their meaning and express it semantically. Putting data into a semantic representation is also known as semantization. On the one hand, existing approaches to analyze sensor data are often use-case specific and do not consider its streaming-n...
Preprint
Full-text available
Software architectures in automotive have evolved over the last twenty years to support data-driven functionalities. Currently, several enterprises from different domains are focusing on improving their architectures by redefining the underlying data models to enable core support for analytics and artificial intelligence. Additionally, a common des...
Poster
Full-text available
Despite the high value of vehicle data, their "Big Data" characteristics make it necessary to apply an intelligent data management approach to fit the world of connected devices. Moreover, the existing variety of data formats implies the undesired repetition of data engineering pipelines. Although semantic technologies and graph data models have pr...
Conference Paper
Full-text available
Modern vehicles produce big data with a wide variety of formats due to missing open standards. Thus, abstractions of such data in the form of descriptive labels are desired to facilitate the development of applications in the automotive domain. We propose an approach to reduce vehicle sensor data into semantic outcomes of dangerous driving events b...
Conference Paper
The Web of Things offers a platform-independent solution for interacting with connected devices. An important vertical of the WoT is the transportation domain with, at its core, autonomous systems and among others, connected vehicles. They can be seen as complex artefacts , as they are composed of many sensors and actuators, legacy specifications a...
Preprint
Full-text available
Modern vehicles are equipped with connectivity capabilities which will eventually open promising business opportunities. However , intelligent applications depend on high-quality and structured data which is difficult to obtain from the vehicle (i.e., several sensors, time-series data, different formats, etc.). Moreover, services and functions in t...
Conference Paper
Full-text available
Application developers in the automotive domain have to deal with thousands of different signals, represented in highly heterogeneous formats, and coming from various car architectures. This situation prevents the development and connectivity of modern applications. We hypothesize that a formal model of car signals, in which the definition of signa...
Poster
Full-text available
We propose a car signal ontology named VSSo that provides a formal definition of the numerous sensors embedded in car regardless of the vehicle model and brand, re-using the work made by the GENIVI alliance with the Vehicle Signal Specification (VSS). We observe that recent progress in machine learning enables to predict a number of useful informat...
Conference Paper
Car signal data is usually hard to access, understand and integrate for non automotive domain experts. In this paper, we use semantic technologies for enriching signal data in the automotive industry and access it through Web of Things interactions. This combination allows the access and integration of car data from the web. We built VSSo, a Vehicl...
Conference Paper
Full-text available
In this paper, we use semantic technologies for enriching trajectory data in the automotive industry for offline analysis. We proposed to re-use a combination of existing ontologies and we designed a Vehicle Signal Specification ontology to provide an environment in which we developed an application that analyzes the variations of signal values and...
Conference Paper
Full-text available
In this paper, we present the design and implementation of DrIveSCOVER, a recommender system for places and events in case of an in-car use, where the driving conditions such as weather and local traffic are taken into account. We integrate multiple data sources using semantic technologies and we devise recommending functions that are presented in...

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Projects

Projects (2)
Project
Create value out of vehicle data streams by: - Demystifying unstructured vehicle data through semantic annotations - Linking semantic data streams to other domains - Generating new knowledge through graph data reasoning