The Digital Product Passport (DPP) is a concept for collecting and sharing product-related information along the life cycle of product. DPPs are currently subject intense discussion, various development efforts being undertaken. These supported by regulatory activities, especially in case battery passport. aggregation product life-cycle data their respective use, as well these between companies, entrepreneurs, other actors value chain, crucial creation resource-efficient circular economy....

In today’s age of modern information technology, large amounts data are generated every second to enable subsequent aggregation and analysis. However, the IT infrastructures that have been set up over last few decades which should now be used for this purpose very heterogeneous complex. As a result, tasks analyzing data, such as collecting, searching, understanding processing become time-consuming. This makes it difficult realize visions, Internet Production, pursues goal guaranteeing...

Several smart cities around the world have begun monitoring parking areas in order to estimate free spots and help drivers that are looking for parking. The current results indeed promising, however, this approach is limited by high costs of sensors need be installed throughout city achieve an accurate estimation rate. This work investigates extension estimating information from equipped with missing them. To end, similarity values between neighborhoods computed based on background data,...

Gaze tracking is a common technique to study user interaction but also increasingly used as input modality. In this regard, computer vision based systems provide promising low-cost realization of gaze on mobile devices. This paper complements related work focusing algorithmic designs by conducting two users studies aiming i) independently evaluate EyeTab approach and ii) providing the first independent use case driven evaluation its applicability in scenarios. Our elucidates current state...

In the last decade, increasing plurality of materials, media types and software tools within internet has established first steps towards more individualized learning approaches. However, development utilizing Big Data-based algorithms next generation, so-called `Internet Things', leads to a comprehensive approach personalized for very different target groups. Understanding learner's profile interests, goals difficulties, `intelligent agents' accompany guide learner during process in future....

The circular economy (CE) is essential to achieving a sustainable future through resource conservation and climate protection. Efficient use of materials products over time critical aspect CE, helping reduce CO2 emissions, waste consumption. Digital Product Passport (DPP) CE-specific approach that contains information about components their origin, can also provide environmental social impact assessments. However, creating DPP requires collecting analyzing data from many different...

This paper provides an in-depth review of deep learning techniques to address the challenges odometry and global ego-localization using frequency modulated continuous wave (FMCW) radar sensors. In particular, we focus on prediction odometry, which involves determination ego-motion a system by external sensors, loop closure detection, concentrates ego-position typically existing map. We initially emphasize significance these tasks in context sensors underscore motivations behind them. The...

Today, smart city applications are largely based on data collected from different stakeholders. This presupposes that the required sources publicly available. While open platforms already provide a number of urban sources, enterprises and citizens have few opportunities to make their To complicate things further, if is published, processing this extremely time-consuming today, as heterogeneous corresponding homogenization has be carried out by consumers themselves. In paper, we present...

In the last years, enterprises increase their effort to collect large amounts of data from many heterogeneous sources and store it in modern architectures like lakes. However, this approach faces different drawbacks for finding understanding sources. Ontology-Based Data Access (OBDA) originating Semantic Web enables a homogeneous access by using mapping, called semantic model, between source target ontology. OBDA requires detailed ontology, which is usually created ontology engineers domain...

The term dataspace was coined two decades ago [12] and has evolved since then. Definitions range from (i) an abstraction for data management in identifiable scope [15] over (iii) a multi-sided platform connecting participants ecosystem [21] to interlinking towards loosely connected (global) information [17]. Many implementations scientific notions follow different interpretations of the dataspace, but agree on some use semantic technologies. For example, dataspaces such as European Open...

Ontology-based data management and knowledge graphs have emerged in recent years as efficient approaches for managing utilizing diverse large sets. In this regard, research on algorithms automatic semantic labeling modeling a prerequisite both has made steady progress the form of new approaches. The range varies type information used (data schema, values, or metadata), well underlying methodology (e.g., use different machine learning methods external bases). Approaches that been established...

In the age of digitalization, collection and analysis large amounts data is becoming increasingly important for enterprises to improve their businesses processes, such as introduction new services or realization resource-efficient production. Enterprises concentrate strongly on integration, processing data. Unfortunately, majority focuses structured semi-structured data, although unstructured text documents images account largest share all available enterprise One reason this that most not...

In recent years, the efforts of both governmental and commercial institutions to exchange publish data have significantly increased. Data published by these is usually heterogeneous in terms structure semantics, which turn leads a large effort its utilization. One possible solution ensure that can be easily found accessed semantic management. Nevertheless, management has only been able gain limited acceptance everyday work as it requires creation mapping, e.g., form model, between used...

This paper presents the platform ESKAPE, which uses semantic models in addition to data handle batch and streaming on an information focused level. ESKAPE enables users process, query subscribe heterogeneous sources without need consider model, facilitating creation of products from data. Instead using a pre-defined fixed ontology, knowledge graph is expanded by defined upon their sets.

Semantic models are utilized to add context information datasets and make data accessible understandable in applications such as dataspaces. Since the creation of is a time-consuming task that has be performed by human expert, different approaches automate or support this process exist. A recurring problem link prediction, i.e., automatic prediction links between nodes graph, case semantic models, usually based on machine learning techniques. While, general, trained evaluated large reference...

Engineering change management (ECM) is a complex process that requires extensive documentation work and dedicated communication between the parties involved. In addition, increasing complexity of products various fluctuations in market conditions lead to significant increase quantity engineering changes which are reflected throughout stages product's life cycle. Recent studies show lack standards enable exchange information resulting from interaction actors involved process. The advancing...

Since companies generate and store large amounts of data daily in centralized systems such as lakes, understanding sets from different sources is becoming an increasingly complex task dealing with heterogeneity across domains. One solution for describing semantics the use semantic models based on available vocabulary. However, creating detailed can be a challenging users who are not familiar modeling today's tools. To overcome this challenge, we developed intuitive user-friendly interface,...

With the latest advances in digitalization and Industry 4.0, manufacturing industry is collecting more production data. However, with increasing interconnection of machines, not only volume but also variety data being expanded. The life cycles collection, processing, combining, analyzing feeding new findings back into sources are becoming increasingly challenging for scientists to complete. Reference architectures such as RAMI 4.0 provide conceptual guidelines address these problems. In this...