Data lakes are becoming increasingly prevalent for big data management and data analytics. In contrast to traditional ‘schema-on-write’ approaches such as data warehouses, data lakes are repositories storing raw data in its original formats and providing a common access interface. Despite the strong interest raised from both academia and industry, there is a large body of ambiguity regarding the definition, functions and available technologies for data lakes. A complete, coherent picture of data lake challenges and solutions is still missing. This survey reviews the development, architectures, and systems of data lakes. We provide a comprehensive overview of research questions for designing and building data lakes. We classify the existing approaches and systems based on their provided functions for data lakes, which makes this survey a useful technical reference for designing, implementing and deploying data lakes. We hope that the thorough comparison of existing solutions and the discussion of open research challenges in this survey will motivate the future development of data lake research and practice.

Entering the second decade of the Industrie 4.0 vision, the production sector is facing challenges in taking full advantage of global digitalization. Production research has focused on sophisticated mathematical models ranging from molecular materials modeling to production control to supply chain logistics. These models help simulate and control the related physical system but the variety of individual situations and behaviors is captured only as statistical uncertainty. The emergence of data-driven methods adds statistical or AI models learned from real-time production data to Digital Twins, and ideally allows for continuous synchronization (twinning) between physical and virtual system. However, the complexity of today’s production systems precludes Digital Twins covering more than just a few system perspectives, especially if realtime performance is required. To achieve better performance and more precise context adaptation, the interdisciplinary research cluster “Internet of Production” at RWTH Aachen University is exploring the concept of Digital Shadows. We conceptualize Digital Shadows as a generalization of compact views on dynamic processes, whose defining “query” combines condensed measurement data with efficient simplified mathematical models. Their small size makes Digital Shadows amenable to dynamic function allocation in hybrid cloud–edge settings. In addition to showing the similarities and differences to the traditional view concept, we also present a conceptual embedding of Digital Shadows in the context of large distributed system architectures, and sovereign data exchange in international Data Space communities. Two production use case experiences demonstrate that Digital Shadows can be valuable carriers of deep and reusable engineering knowledge for technical and ecological progress.

Data lakes are becoming increasingly prevalent for big data management and data analytics. In contrast to traditional ‘schema-on-write’ approaches such as data warehouses, data lakes are repositories storing raw data in its original formats and providing a common access interface. Despite the strong interest raised from both academia and industry, there is a large body of ambiguity regarding the definition, functions and available technologies for data lakes. A complete, coherent picture of data lake challenges and solutions is still missing. This survey reviews the development, architectures, and systems of data lakes. We provide a comprehensive overview of research questions for designing and building data lakes. We classify the existing approaches and systems based on their provided functions for data lakes, which makes this survey a useful technical reference for designing, implementing and deploying data lakes. We hope that the thorough comparison of existing solutions and the discussion of open research challenges in this survey will motivate the future development of data lake research and practice.

The advent of Industry 4.0 has led a wide variety of engineering fields to incorporate more automation into their existing work processes. Various engineering sectors intend to imbibe aspects of Industry 4.0 technologies by leveraging Internet of Things coupled with Machine Learning and Artificial Intelligence for process optimization. This, in turn, has led to the surge of cross-domain data integration strategies which when enriched with domain specific knowledge creates dynamic models, termed as Digital Shadows. In this paper, we present the adaptation of the Digital Shadow modeling approach to die casting processes. We propose a generic pipeline for the creation of the model and test the efficacy of such an approach by transforming a predictive analytics model into a digital shadow model. For the predictive modeling, we present a novel approach of image based pixel classification which accurately predicts the occurrence as well as the location of damages on the cast object surfaces.

Topic modeling is a machine learning technique that identifies latent topics in a text corpus. There are several existing tools that allow end-users to create and explore topic models using graphical user interfaces. In this paper, we present a visual analytics system for dynamic topic models that goes beyond the existing breed of tools. First, it decouples the Web-based user interface from the underlying data sets, enabling exploration of arbitrary text data sets in the Web browser. Second, it allows users to explore dynamic topic models, while existing tools are often limited to static topic models. Finally, it comes with a tool server in the backend that allows the design and execution of scientific workflows to build topic models from any data source. The system is demonstrated by building and exploring a dynamic topic model of CIKM proceedings published since 2001.

Advances in mobile communication technologies lead to a coalescence of location-based, multimedia services for user communities. However, easy development and maintenance of device-independent mobile services are still challenging. We have developed a service-oriented framework for mobile multimedia processing based on international standards like MPEG-7. Quality of mobile service experience is constantly monitored in framework. The scenario “Virtual Campfire” is used in the German excellence cluster UMIC (Ultra High-Speed Information and Communication) to demonstrate future mobile social software with real-time multimedia processing, semantic enrichment of multimedia materials by user communities and complex collaboration over the mobile we like storytelling on different mobile devices. Adaptive Web access, service calls and service monitoring are to be demonstrated as the prototype, which offers approaches to meeting the aforementioned challenges.

Multimedia information systems have been developed into service-ware. With the paradigms of web services, service oriented architectures (SOA), and Web 2.0 widgets, multimedia has become truly ubiquitous. However, interoperability, scalability, reliability and security are arising challenges at mobile multimedia service development. This paper focuses on the analysis, design, development and evaluation of a middleware that allows access from mobile devices to a bundle of multimedia services. The services are based on the international multimedia metadata description standard MPEG-7. The implementation is based on new generation of service-oriented application servers called Lightweight Application Server (LAS). Mobile web services refer to the fact that mobile servers host web services. A prototype was developed as a proof of concept, showing how to access MPEG-7 based multimedia services from a Mobile Host and the analysis results of providing MPEG-7 based multimedia services in the form of web services from the Mobile Host to other mobile devices. An alternative solution is to apply enterprise service bus technology as the middleware. The performance evaluation results of both approaches show the reliable accessibility of MPEG-7 based multimedia services via the enterprise service bus solution.

Due to the astonishing development in memory and processing capabilities of hand held devices such as smart phones, it is not a dream anymore to enable mobile devices not only as conventional web service requesters but even as providers. The willingness and enthusiasm of service providers place abundant services at the disposal. But this abundance makes the efficiency of service discovery a critical issue. Centralized registries have severe drawbacks in such a scenario due to the dynamic and spontaneous nature of mobile peers. In the quest for a more appropriate approach for mobile web service discovery, we observed P2P to share very similar characteristics with behaviors of peers in mobile network. Hence we tried to find alternate mobile web service discovery mechanisms by using the features of the P2P networks like JXTA modules. The scalability analysis of the approach proves that the discovery can scale to the needs of large cellular networks.

Nowadays various mobile platforms from PDA, smart phones to iPhones can deliver road warriors or trippers much mobile information. However, most mobile applications are lacking the "social intelligence" of real companionship. One reason is that community context and spatiotemporal context information are not well taken into consideration. In this paper we propose an ontology-based context model using OWL/RDF. With the enhanced interoperability substantial context information can be expressed and reasoned across systems. Based on the context model and the middleware Context-Aware Adaptation Service (CAAS), we introduce a mobile tourist guide as proof- of-concept that provides users context-aware information. We employ the MPEG-7 and MPEG-21 metadata standards to realize multimedia adaptation to device preferences. The evaluation result proves the feasibility of the context model and shows the easy extensibility of CAAS.

Health and mobility of elderly people is gaining importance in aging societies. New communication-based methods to provide health services with personal health care devices are considered promising elements of first-class medical care services for everybody. To achieve this vision, several technological issues have to be solved: (i) body sensors to monitor vital functions have to be developed; (ii) these sensors should be integrated into textile structures to guarantee ease of use and patient acceptance; (iii)the collected sensor data has to be analyzed to detect emergency situations and to reduce the data volume; (iv) relevant data has to be integrated with other information systems in the work environment of medical experts. These challenges are addressed within the HealthNet project at RWTH Aachen University. The goal of the project is to develop a framework in which health professional scan remotely monitor and diagnose mobile patients. The described demonstration presents our results of the first three issues mentioned above while focusing on the employed data mining and management techniques.

The ESPRIT Project DWQ (Foundations of Data Warehouse Quality) aimed at improving the quality of DW design and operation through systematic enrichment of the semantic foundations of data warehousing. Logic-based knowledge representation and reasoning techniques were developed to control accuracy, consistency, and completeness via advanced conceptual modeling techniques for source integration, data reconciliation, and multi-dimensional aggregation. This is complemented by quantitative optimization techniques for view materialization, optimizing timeliness and responsiveness without losing the semantic advantages from the conceptual approach. At the operational level, query rewriting and materialization refreshment algorithms exploit the knowledge developed at design time. The demonstration shows the interplay of these tools under a shared metadata repository, based on an example extracted from an application at Telecom Italia.

The paper surveys performance models for distributed and replicated database systems. Over the last 20 years (1980-2000), a variety of such performance models have been developed and they differ in: (1) which aspects of a real system are or are not captured in the model (e.g., replication, communication, nonuniform data access, etc.); and (2) how these aspects are modeled. We classify the different alternatives and modeling assumptions and discuss their interdependencies and expressiveness for the representation of distributed databases. This leads to a set of building blocks for analytical performance models. To illustrate the work that is surveyed, we select a combination of these proven modeling concepts and give an example of how to compose a balanced analytical model of a replicated database. We use this example to show how to derive meaningful performance values and to discuss the applicability and expressiveness of performance models for distributed and replicated databases. Finally, we compare the analytical results to measurements in a distributed database system.

Research and products for the integration of heterogeneous legacy source databases in data warehousing have addressed numerous data quality problems in or between the sources. Such a solution is marketed by Team4 for the decision support of mobile sales representatives, using advanced view maintenance and replication management techniques in an environment based on relational data warehouse technology and Lotus Notes-based client systems. However, considering total information supply chain management, the capture of poor operational data, to be cleaned later in the data warehouse, appears sub-optimal. Based on the observation that decision support clients are often closely linked to operational data entry, we have addressed the problem of mapping the data warehouse data quality techniques back to data quality measures for improving OLTP data. The solution requires a warehouse-to-OLTP workflow which employs a combination of view maintenance and view update techniques.

ADR (Atomic Delayed Replication) is a controllable replication manager implemented on top of commercial distributed relational databases. ADR's goal is to enable various well-defined trade-offs between database coherence, throughput and response time in large database networks, e.g. for telecom applications. By combining a strategy for distributed database design with a specific replication protocol, ADR preserves the ACID properties with a controlled relaxation of coherence between primary and secondary copies. We first discuss formal characteristics of ADR, and present the implementation techniques required to realize these formal characteristics on top of commercial distributed database technology. Then, after reviewing a validated analytical performance model for the approach, we demonstrate its flexibility by summarizing experiences with two industrial ADR applications in telecommunications management, both jointly developed with Philips Laboratories. One is database support for the integrated operation and evolution of Intelligent Network telephone services, where secondary copies are held within a distributed database system optimized for throughput and availability during schema evolution. The other concerns database support for mobile phones in a City-wide DECT setting (Digital Enhanced Cordless Telecommunications), where secondary copies are held in main memory caches outside the DBMS.

We show three interrelated tools intended to improve different aspects of the quality of data warehouse solutions. Firstly, the deductive object manager ConceptBase is intended to enrich the semantics of data warehouse solutions by including an explicit enterprise-centered concept of quality. The positive impact of precise multidimensional data models on the client interface is demonstrated by CoDecide, an Internet-based toolkit for the flexible visualization of multiple, interrelated data cubes. Finally, MIDAS is a hybrid data mining system which analyses multi-dimensional data to further enrich the semantics of the meta database, using a combination of neural network techniques, fuzzy logic and machine learning.

CoDecide is an experimental user interface toolkit that offers an extension to spreadsheet concepts specifically geared towards support for cooperative analysis of the kinds of multi-dimensional data encountered in data warehousing. It is distinguished from previous proposals by direct support for drill-down/roll-up analysis without redesign of an interface; more importantly, CoDecide can link multiple views on a data cube for synchronous or asynchronoous cooperation by multiple analysts, through a conceptual model visualizing the problem dimensions on so-called tapes. Tapes generalize the ideas of ranging and pivoting in current data warehouses for the multi-perspective and multi-user case. CoDecide allows the rapid composition of multi-matrix interfaces and their linkage to underlying data sources. A LAN version of CoDecide has been used in a number of design decision support applications. A WWW version representing externally materialized views on databases is currently under development.

Special features of process control expert systems (PCX) make it both necessary and feasible to test them in a comprehensive manner. FAITH, an automated regression testing environment for PCX, integrates five specially adapted testing techniques, exploiting external specifications gained from the process control environment. FAITH also offers a set of metrics which can be used to predict testability during the early phases of PCX development. FAITH has been developed for a major German chemicals company where it is routinely used for certifying PCX, and for guiding design-for-testability.

Cooperation is the organizational motivation behind computer networks. In these networks, information systems progress from their traditional file cabinet role to become advanced communications media that enable cooperation across boundaries of space and time. The Third ICIS Workshop, held at Dagstuhl Castle, Germany, in April 1992 addressed the question: what does this observation entail for computer science research, practice, and education? Research implications. Cooperation technology provides interfaces between people rather than between humans and machines. The simplistic distinctions of CSCW research in the 1980’s (synchronous vs. asynchronous, local vs. distributed, message passing vs. information sharing) detract from the central goal that coordination should not get in the way of human interaction. On the one hand, CSCW operates in a coherent organizational and technological framework. Real-time group interfaces must be embedded in process-oriented repositories for long-term cooperation; change management is the crucial research issue. On the other hand, CSCW must be enriched with domain information. Studies of the usage and organizational embedding of information technology cannot be delegated to the social sciences alone because they do not have the answers either. Business implications. “Killer applications” that prove the value of CSCW beyond electronic mail and videoconferencing have yet to emerge. One suggestion is to develop theory and product ideas in the context of actual applications through direct links between researchers and users. A more vendor-oriented approach focuses on developing core technology on which application-specific services can be delivered. This latter infrastructure market, though important, is obviously much smaller; it is the services that pay back the investments. Educational implications. Curricula do not adequately reflect the changing role of computer scientists in the workplace. This is even now endangering the traditionally good position of computer science graduates on the labor market. In accordance with the market shares above, there must be a stronger component of application experience and students must be explicitly taught to work in interdisciplinary teams. Since curricula are already very full, this implies that some traditional areas of computer science may have to be reduced — a painful but necessary process.

The WibQuS project investigates distributed computer and communication support for Total Quality Management in industrial organizations. An interdisciplinary study of this task reveals three aspects of intelligent cooperation required from such a system which we call conceptual, technical, and social integration. We use the repository standard IRDS to characterize these aspects. A solution concept derived from this characterization employs advanced conceptual modeling techniques to derive interoperability among technical subsystems and coordination technology for the human subsystem semi-automatically while taking important social factors into account.

Repositories provide the information system's support to layer software environments. Initially, repository technology has been dominated by object representation issues. Teams are not part of the ball game. In this paper, we propose the concept of sharing processes which supports distribution and sharing of objects and tasks by teams. Sharing processes are formally specified as classes of non-deterministic finite automata connected to each other by deduction rules. They are intended to coordinate object access and communication for task distribution in large development projects. In particular, we show how interactions between both sharings improve object management.

Information systems support for design environments emphasizes object management and tends to neglect the growing demand for team support. Process management is often tackled by rigid technological protocols which are likely to get in the way of group productivity and quality. Group tools must be introduced in an unobtrusive way which extends current practice yet provides structure and documentation of development experiences. The concept of sharing processes allows agents to coordinate the sharing of ideas, tasks, and results by interacting protocol automata which can be dynamically adapted to situational requirements. Inconsistency is managed with equal emphasis as consistency. The sharing process approach has been implemented in a system called ConceptTalk which has been experimentally integrated with design environments for information and hypertext systems.

We present a framework for the development of information systems based on the premise that the knowledge that influences the development process needs to somehow be captured, represented, and managed if the development process is to be rationalized. Experiences with a prototype environment developed in ESPRIT project DAIDA demonstrate the approach. The project has implemented an environment based on state-of-the-art languages for requirements modeling, design and implementation of information systems. In addition, the environment offers tools for aiding the mapping process from requirements to design and then to implementation, also for representing decisions reached during the development process. The development process itself is represented explicitly within the system, thus making the DAIDA development framework easier to comprehend, use, and modify.

We describe Telos, a language intended to support the development of information systems. The design principles for the language are based on the premise that information system development is knowledge intensive and that the primary responsibility of any language intended for the task is to be able to formally represent the relevent knowledge. Accordingly, the proposed language is founded on concepts from knowledge representations. Indeed, the language is appropriate for representing knowledge about a variety of worlds related to a particular information system, such as the subject world (application domain), the usage world (user models, environments), the system world (software requirements, design), and the development world (teams, metodologies). We introduce the features of the language through examples, focusing on those provided for desribing metaconcepts that can then be used to describe knowledge relevant to a particular information system. Telos' fetures include an object-centered framework which supports aggregation, generalization, and classification; a novel treatment of attributes; an explicit representation of time; and facilities for specifying integrity constraints and deductive rules. We review actual applications of the language through further examples, and we sketch a formalization of the language.

Decision Support Systems (DSSs), computer-based systems intended to assist managers in preparing and analyzing decisions, have been single-user systems for most of the past decade. Only recently has DSS research begun to study the implications of the fact that most complex managerial decisions involve multiple decision makers and analysts. A number of tools for facilitating group decisions have been proposed under the label Group Decision Support Systems (GDSSs). One of the most important functions of a GDSS is to provide problem-oriented services for communication among decision makers. On the basis of an analysis of the communication requirements in various group decision settings, this paper presents an architecture for defining and enforcing dynamic application-level protocols that organize decision group interaction. The architecture has been implemented on a network of personal computers in Co-oP, a GDSS for cooperative group decision making based on interactive, multiple-criteria decision methods.

An optimizing translation mechanism for the dynamic interaction between a logic-based expert system written in PROLOG and a relational database accessible through SQL is presented. The mechanism makes use of an intermediate language that decomposes the optimization problem and makes the proposed approach target-language independent. It can either facilitate expert system - database interaction, e.g., when integrating expert systems into business systems, or augment existing databases with (external) deductive capabilities.

Database queries explicitly containing existential and universal quantification become increasingly important in a number of areas such as integrity checking, interaction of databases and AI systems, heterogeneous databases, and statistical databases. Using a concept of range nesting in relational calculus expressions, the paper describes evaluation algorithms and transformation methods for an important class of quantified relational calculus queries called perfect expressions. This class includes well-known classes of "easy" queries such as tree queries (with free and existentially quantified variables only), and complacent (disconnected) queries.

In the database language PASCAL/R, the programming language PASCAL and concepts based on the relational data model are integrated. The paper investigates transformation strategies used in the PASCAL/R system to evaluate queries with existential and universal quantifiers. Intermediate data structures are described using a high-level language tool called a reference to a selected variable. The predicate calculus approach used in PASCAL/R offers new insight into recently proposed query optimization techniques and allows some of them to be extended.