Edge IoT Prototyping Using Model-Driven Representations: A Use Case for Smart Agriculture.

Industry 4.0 is positioned at the junction of different disciplines, aiming to re-engineer processes and improve effectiveness and efficiency. It is taking over many industries whose traditional practices are being disrupted by advances in technology and inter-connectivity. In this context, enhanced agriculture systems incorporate new components that are capable of generating better decision making (humidity/temperature/soil sensors, drones for plague detection, smart irrigation, etc.) and also include novel processes for crop control (reproducible environmental conditions, proven strategies for water stress, etc.). At the same time, advances in model-driven development (MDD) simplify software development by introducing domain-specific abstractions of the code that makes application development feasible for domain experts who cannot code. XMDD (eXtreme MDD) makes this way to assemble software even more user-friendly and enables application domain experts who are not programmers to create complex solutions in a more straightforward way. Key to this approach is the introduction of high-level representations of domain-specific functionalities (called SIBs, service-independent building blocks) that encapsulate the programming code and their organisation in reusable libraries, and they are made available in the application development environment. This way, new domain-specific abstractions of the code become easily comprehensible and composable by domain experts. In this paper, we apply these concepts to a smart agriculture solution, producing a proof of concept for the new methodology in this application domain to be used as a portable demonstrator for MDD in IoT and agriculture in the Confirm Research Centre for Smart Manufacturing. Together with model-driven development tools, we leverage here the capabilities of the Nordic Thingy:53 as a multi-protocol IoT prototyping platform. It is an advanced sensing device that handles the data collection and distribution for decision making in the context of the agricultural system and supports edge computing. We demonstrate the importance of high-level abstraction when adopting a complex software development cycle within a multilayered heterogeneous IT ecosystem.

Health-ID: A Blockchain-Based Decentralized Identity Management for Remote Healthcare.

COVID-19 has made eHealth an imperative. The pandemic has been a true catalyst for remote eHealth solutions such as teleHealth. Telehealth facilitates care, diagnoses, and treatment remotely, making them more efficient, accessible, and economical. However, they have a centralized identity management system that restricts the interoperability of patient and healthcare provider identification. Thus, creating silos of users that are unable to authenticate themselves beyond their eHealth application's domain. Furthermore, the consumers of remote eHealth applications are forced to trust their service providers completely. They cannot check whether their eHealth service providers adhere to the regulations to ensure the security and privacy of their identity information. Therefore, we present a blockchain-based decentralized identity management system that allows patients and healthcare providers to identify and authenticate themselves transparently and securely across different eHealth domains. Patients and healthcare providers are uniquely identified by their health identifiers (healthIDs). The identity attributes are attested by a healthcare regulator, indexed on the blockchain, and stored by the identity owner. We implemented smart contracts on an Ethereum consortium blockchain to facilities identification and authentication procedures. We further analyze the performance using different metrics, including transaction gas cost, transaction per second, number of blocks lost, and block propagation time. Parameters including block-time, gas-limit, and sealers are adjusted to achieve the optimal performance of our consortium blockchain.

Semantics-based composition of EMBOSS services.

BACKGROUND: More than in other domains the heterogeneous services world in bioinformatics demands for a methodology to classify and relate resources in a both human and machine accessible manner. The Semantic Web, which is meant to address exactly this challenge, is currently one of the most ambitious projects in computer science. Collective efforts within the community have already led to a basis of standards for semantic service descriptions and meta-information. In combination with process synthesis and planning methods, such knowledge about types and services can facilitate the automatic composition of workflows for particular research questions. RESULTS: In this study we apply the synthesis methodology that is available in the Bio-jETI workflow management framework for the semantics-based composition of EMBOSS services. EMBOSS (European Molecular Biology Open Software Suite) is a collection of 350 tools (March 2010) for various sequence analysis tasks, and thus a rich source of services and types that imply comprehensive domain models for planning and synthesis approaches. We use and compare two different setups of our EMBOSS synthesis domain: 1) a manually defined domain setup where an intuitive, high-level, semantically meaningful nomenclature is applied to describe the input/output behavior of the single EMBOSS tools and their classifications, and 2) a domain setup where this information has been automatically derived from the EMBOSS Ajax Command Definition (ACD) files and the EMBRACE Data and Methods ontology (EDAM). Our experiments demonstrate that these domain models in combination with our synthesis methodology greatly simplify working with the large, heterogeneous, and hence manually intractable EMBOSS collection. However, they also show that with the information that can be derived from the (current) ACD files and EDAM ontology alone, some essential connections between services can not be recognized. CONCLUSIONS: Our results show that adequate domain modeling requires to incorporate as much domain knowledge as possible, far beyond the mere technical aspects of the different types and services. Finding or defining semantically appropriate service and type descriptions is a difficult task, but the bioinformatics community appears to be on the right track towards a Life Science Semantic Web, which will eventually allow automatic service composition methods to unfold their full potential.

Bio-jETI: a framework for semantics-based service composition.

BACKGROUND: The development of bioinformatics databases, algorithms, and tools throughout the last years has lead to a highly distributed world of bioinformatics services. Without adequate management and development support, in silico researchers are hardly able to exploit the potential of building complex, specialized analysis processes from these services. The Semantic Web aims at thoroughly equipping individual data and services with machine-processable meta-information, while workflow systems support the construction of service compositions. However, even in this combination, in silico researchers currently would have to deal manually with the service interfaces, the adequacy of the semantic annotations, type incompatibilities, and the consistency of service compositions. RESULTS: In this paper, we demonstrate by means of two examples how Semantic Web technology together with an adequate domain modelling frees in silico researchers from dealing with interfaces, types, and inconsistencies. In Bio-jETI, bioinformatics services can be graphically combined to complex services without worrying about details of their interfaces or about type mismatches of the composition. These issues are taken care of at the semantic level by Bio-jETI's model checking and synthesis features. Whenever possible, they automatically resolve type mismatches in the considered service setting. Otherwise, they graphically indicate impossible/incorrect service combinations. In the latter case, the workflow developer may either modify his service composition using semantically similar services, or ask for help in developing the missing mediator that correctly bridges the detected type gap. Newly developed mediators should then be adequately annotated semantically, and added to the service library for later reuse in similar situations. CONCLUSION: We show the power of semantic annotations in an adequately modelled and semantically enabled domain setting. Using model checking and synthesis methods, users may orchestrate complex processes from a wealth of heterogeneous services without worrying about interfaces and (type) consistency. The success of this method strongly depends on a careful semantic annotation of the provided services and on its consequent exploitation for analysis, validation, and synthesis. We are convinced that these annotations will become standard, as they will become preconditions for the success and widespread use of (preferred) services in the Semantic Web.

Bio-jETI: a service integration, design, and provisioning platform for orchestrated bioinformatics processes.

BACKGROUND: With Bio-jETI, we introduce a service platform for interdisciplinary work on biological application domains and illustrate its use in a concrete application concerning statistical data processing in R and xcms for an LC/MS analysis of FAAH gene knockout. METHODS: Bio-jETI uses the jABC environment for service-oriented modeling and design as a graphical process modeling tool and the jETI service integration technology for remote tool execution. CONCLUSIONS: As a service definition and provisioning platform, Bio-jETI has the potential to become a core technology in interdisciplinary service orchestration and technology transfer. Domain experts, like biologists not trained in computer science, directly define complex service orchestrations as process models and use efficient and complex bioinformatics tools in a simple and intuitive way.

GeneFisher-P: variations of GeneFisher as processes in Bio-jETI.

BACKGROUND: PCR primer design is an everyday, but not trivial task requiring state-of-the-art software. We describe the popular tool GeneFisher and explain its recent restructuring using workflow techniques. We apply a service-oriented approach to model and implement GeneFisher-P, a process-based version of the GeneFisher web application, as a part of the Bio-jETI platform for service modeling and execution. We show how to introduce a flexible process layer to meet the growing demand for improved user-friendliness and flexibility. RESULTS: Within Bio-jETI, we model the process using the jABC framework, a mature model-driven, service-oriented process definition platform. We encapsulate remote legacy tools and integrate web services using jETI, an extension of the jABC for seamless integration of remote resources as basic services, ready to be used in the process. Some of the basic services used by GeneFisher are in fact already provided as individual web services at BiBiServ and can be directly accessed. Others are legacy programs, and are made available to Bio-jETI via the jETI technology. The full power of service-based process orientation is required when more bioinformatics tools, available as web services or via jETI, lead to easy extensions or variations of the basic process. This concerns for instance variations of data retrieval or alignment tools as provided by the European Bioinformatics Institute (EBI). CONCLUSIONS: The resulting service- and process-oriented GeneFisher-P demonstrates how basic services from heterogeneous sources can be easily orchestrated in the Bio-jETI platform and lead to a flexible family of specialized processes tailored to specific tasks.