Semantic Web Services SS 2018 Applications Anna Fensel

Where are we? # Title 1 Introduction 2 Web Science + Cathy O’Neil’s talk: “Weapons of Math Destruction” 3 Service Science 4 Web services 5 Web 2. 0 services 6 Semantic Web + ONLIM APIs (separate slideset) 7 Semantic Web Service Stack (WSMO, WSML, WSMX) 8 OWL-S and the others 9 Semantic Services as a Part of the Future Internet and Big Data Technology 10 Lightweight Annotations 11 Linked Services 12 Applications 13 Mobile Services 2

Outline • Motivation (Note: also covered individually for each use case in the technical solution part) • Technical solution – DIP • DIP Introduction and overview • DIP Technical solution • DIP demonstrators – SUPER • • SUPER Introduction and overview SUPER Technical solution SUPER methodology and demonstrators SUPER Demo/video – Further specific use cases in projects • Transport: e. Freight • Manufacturing: MSEE • Health: Onto. Health – Current business trends • Microservices • Blockchains • Summary • References 3 3

MOTIVATION 4

Motivation and Learning Goals • Semantic Web Services (SWS) were shown to be useful in theory… …now we also want to see more projects, scenarios and examples of systems where this technology can be used. • This lecture will enable you to: – Identify and describe relevant scenarios for the SWS usage – from different sectors, learn how the solutions are typically modelled, – See how specific SWS technologies can be used for specific use cases, – Explore the potential of the SWSs in the context of new developments, such as microservices and blockchains, – Identify the practical challenges and limitations of the SWS technology. 5 5

DIP EU project on Data, Information, Process Interoperation with Semantic Web Services 6

DIP INTRODUCTION AND OVERVIEW 7

DIP – Introductory Demo/Video (http: //www. sti-innsbruck. at/results/movies/dip-promotion-video ) ~ 9 min 8

DIP overview Client Services 9

DIP overview Client • Let’s consider a client that wants to go on holiday. • The client describes the holiday on her/his own terms – Blue sky, white sand beach, clear water Services Broker • Available services: weather, hotel, travel services • DIP platform acts as a broker • To fulfil user request, DIP discovers, selects, composes and invoke services • DIP provides personalized applications on the fly, from available services 10

DIP objectives • Combine Semantic Web technology with Web Services for Semantic Web Services • Apply Semantic Web Services as an infrastructure in real world scenarios within an organization and between organizations and its customers/partners. • Make Semantic Web Services technology a reality. 11

DIP TECHNICAL SOLUTION 12

DIP – Overall Framework WSMO – Web Service Modelling Ontology WSML – Web Service Modelling Language WSMX – Web Service Execution Environment 13

Web Service Modeling Ontology (WSMO) Objectives that a client wants to achieve by using Web Services Provide the formally specified terminology of the information used by all other components Semantic description of Web Services: - Capability (functional) - Interfaces (usage) Connectors between components with mediation facilities for handling heterogeneities 14 14

Web Service Modeling Language (WSML) • WSML Variants - allow users to make the trade-off between the provided expressivity and the implied complexity on a perapplication basis ∩ ∩ 15

Web Service Execution Environment (WSMX) • … is comprehensive software framework for runtime binding of service requesters and service providers, • … interprets service requester’s goal to – – discover matching services, select (if desired) the service that best fits, provide data/process mediation (if required), and make the service invocation, • … is reference implementation for WSMO, • … has a formal execution semantics, and • … is service oriented, event-based and has pluggable architecture – Open source implementation available through Source Forge, – based on microkernel design using technologies such as JMX. 16

DIP Architecture 17

DIP Architecture – Components (1) • Core component – Managing exchange of messages between components • Communication manager – Handles all external communications • Parser – Parse WSML content of incoming messages into WSMO 4 j • Discovery – Find Web services matching supplied Goals • Qo. S Discovery – Find and order service on the basis of Qo. S parameters • Process Mediator – Handle mismatches client and service choreographies 18

DIP Architecture – Components (2) • Data Mediator – Handle mismatches between ontologies • Choreography Engine – Execute behaviour described by a choreography • Orchestration Engine – Execute the composition defined by an orchestration • Resource Manager – Persist WSMO and operational data • WSML Reasoner – At the heart of the architecture 19

DIP Architecture - behavioural view 20

DIP DEMONSTRATORS 21

Emergency Weather Planning • Winter 2003 - weather chaos in southern England due to 1 cm of snow. • People spent more than 20 hours blocked on motorways 22

Emergency Weather Planning • In an emergency situation, relevant information is needed to assist planning and decision making. • Such information elements range from demographic data, weather forecasts and sensor data, available transportation means to the presence of helpful agents (people), etc. • Different agencies own different relevant data and emergency related knowledge, which needs to be shared with the other partners during an emergency. 23

e. Merges • e. Merges is a decision support system that assists the Emergency Office in the tasks of retrieving, processing, displaying, and interacting with relevant information, more quickly and accurately • Using e. Merges governmental agencies are able to extend their knowledge about the emergency situation they are dealing with by making use of different functionalities based on data held by other agencies which otherwise might not be accessible to them or slow to obtain. 24

e. Merges Ontologies 25

e. Merges Ontologies • • Archetypes ontology provides very high level abstractions (e. g. container, house, agent, etc. ) to which entities from the real world have to be mapped HCI ontology maps an object to its particular representation. For example some interfaces need “pretty names” selecting a feature to privileged display (e. g. on hovering on the object); 26

Generic Application Structure Web Application SWS SWS WS WS IT systems DB Organisation 1 Web Application SWS WS SWS Semantic Web Services (WSMX/IRS-III) Services Abstraction WS IT systems Presentation DB Legacy Systems Organisation 2 27

Generic Application Structure (1) • Legacy System layer: consists of existing data sources and IT systems provided by each of the involved governmental parties • Service Abstraction layer: exposes the functionalities of the legacy systems as Web services, abstracting from the hardware and software platforms of the legacy systems. Whenever a new service is available at this layer, it will be semantically described and properly linked to existing semantic descriptions. 28

Generic Application Structure (2) • Semantic Web Service layer: given a goal request this layer, will • discover a candidate set of Web services, • select the most appropriate, • mediate any mismatches at the data, ontological or business process level, and • invoke the selected Web services whilst adhering to any data, control flow and Web service invocation requirements • Presentation layer: is a Web application accessible through a standard Web browser. 29

e. Merges User Interface 30

e. Merges Prototype Architecture Accommodation Goal Environment Goal Smart Filter Services Presence Goal Environment Services MET-Office-Goals Google Maps API Google Web Toolkit AJAX View. Essex Services Buddy. Space Services Server Buddy. Space Goals Emergency-GIS-Domain MET-Office-Domain SGIS-Spatial Affordances = Goals Emergency-GIS-Goals Archetypes 31

DIP – e. Merges Demo/Video (http: //www. sti-innsbruck. at/results/movies/dip-e. Merges/) ~ 10 min 32

SUPER EU project on Business Process Management that applied WSMO 33

SUPER INTRODUCTION AND OVERVIEW 34

SUPER – Introductory Demo/Video (http: //www. sti-innsbruck. at/results/movies/super-overview-movie/) ~ 3 min 35

SUPER • SUPER = Semantics Utilized for Process management within and between Enterprises (SUPER) • The major objective of SUPER was to raise Business Process Management (BPM) to the business level, where it belongs, from the IT level where it mostly resides now. • This objective requires that BPM is accessible at the level of semantics of business experts 36

Business Process and Business Process Management • “A business process or business method is a collection of related, structure activities or tasks that produce a specific service or product for a particular customer or customers. ” http: //en. wikipedia. org/wiki/Business_process • “Business process management (BPM) is a management approach focused on aligning all aspects of an organization with the wants and needs of clients. It is a holistic approach that promotes business effectiveness and efficiency while striving for innovation, flexibility, and integration with technology” http: //en. wikipedia. org/wiki/Business_process_management 37

Business process in a company • Business Processes –. . . drive all company‘s activities –. . . represent the core assets of a company –. . . give decision makers control over the company’s activities –. . . deliver services faster and more efficiently to the customer –. . . allow a company to react to changing market conditions How do I get the big picture of my activities? How do I communicate my business process in a common fashion? How do I keep track of all evolutions in my business? How do I make sure my businesses get more efficient and more profitables? 38

The critical Business / IT Divide Querying the Process Space • reduce costs • increase product quality • improve throughput times • less training • less support required • increase forecast accuracy Bridging Business-IT gap • reduce implementation costs • implementing the real requirements • faster implementation • less support requests • align implementation 39

SUPER approach to address the critical Business / IT Divide 40

SUPER – How Semantics Help • Semantic technology improves the utility of BPM by creating a semantic „glue“ between different layers, artefacts and models • Links between business artefacts help to keep the „big picture“ and to improve the overall understanding of complex relationships and interdependencies • By unifying the vocabulary and explicating differences in a structured way, semantics support the understanding of business people and technicians 41

SUPER – Scientific objectives • Construction and assessment of technological framework for Semantic Business Process Management (SBPM) • Acquiring new generic languages suited for representation of processes, different process models and goal description having in mind all aspects of system behaviour (e. g. costs, dependencies, constraints, other data flows, time limitations) • Creation of automated annotation techniques of already existing BPs, their fragments, IT components, etc • Development of process query tools • Adjustment existing reasoners to the specific needs of SUPER • Elaboration of industrial-strength mediation procedures for automated coupling between business and IT perspectives • Augmentation of SWS foundations on the basis of new experiences obtained from their deployment to large-scale test environments 42

SUPER – Technical objectives • Building horizontal ontologies in aim to annotate both complete BPs and their fragments • Assembling vertical ontologies for the chosen implementation domain • Complete inventory of tools supporting every stage of SBPM 43

SUPER TECHNICAL SOLUTION 44

SUPER Ontology Stack 45

SUPER Ontology Stack 46

WSMO Web Service Modeling Ontology (http: //www. wsmo. org) Objectives that a client may have when consulting a Web Service Provide the formally specified terminology of the information used by all other components Semantic description of Web Services: • Capability (functional) • Non-functional properties • Interfaces (usage) Connectors between components with mediation facilities for handling heterogeneities 47

SUPER Ontology Stack 48

Business Domain Ontologies • Business Functions Ontology – describes functions carried out within the company (e. g. marketing, finance, HR • Business Process Resources Ontology – describes tangible and abstract resources required • Business Roles Ontology – roles in the organization (e. g. Designer, Process Modeler, IT Expert, CEO) • Business Modeling Guidelines Ontology – generic business policies and rules for domains like law, finance, etc. 49

SUPER Ontology Stack 50

SUPER Ontology Stack • Upper-Level Process Ontology (UPO) represent highlevel concepts for Business Process Modelling. It is the top-level ontology in SUPER, used as the unifying ontology for other ontologies • Business Process Modelling Ontology (BPMO) represent high-level business process workflows. BPMO has a bridging purpose between the business level and the execution level of processes • Semantic Event-driven Process Chains notation Ontology (s. EPC) aims to support the annotation (automatic or semi-automatic) of process models created with EPC tools 51

SUPER Ontology Stack 52

SUPER Ontology Stack • Semantic Business Process Modeling Notation Ontology (s. BPMN) formalises the core subset of BPMN graphical notation • Semantic BPEL Ontology (s. BPEL) extends the BPEL ontology with a SWS based interaction model. • Behavioral Reasoning Ontology (BRO) allows for reasoning over the behaviours of business processes using WSML axioms • Events Ontology (EVO) is a reference model for capturing logging information utilised both by the execution engines (SBPELEE and SEE) and by the analysis tools 53

SUPER Architecture SUPER Execution SUPER Tooling Semantic BPEL Execution Engine SBP Monitoring SBP Modelling SBP Analysis & Management Tool Semantic Execution Environment Deployment Semantic Service Bus Event Sink Protocol Binder SBP Composition SBP Mediation SBP Discovery Data Mediation Reasoner Transformation SUPER Platform Services Semantic Web Services Execution History Business Process Library SUPER Repositories 54

SUPER Architecture • The central component of the architecture is the Semantic Service Bus (SSB) which provides a communication infrastructure for the SUPER components. Components communicate over the bus by sending and receiving normalized messages. • SUPER Tooling comprises tools to support different phases of the Semantic Business Process (SBP) lifecycle: – SBP Modeling Tool - used during the design time for SBP modeling – SBP Monitoring and Management Tool provides an up-to-date picture over the SBP and Semantic Web services (SWS) execution state and provides simple management functionality – SBP Analysis Tool is used for Process Mining and Reverse Business Engineering (RBE) purposes • SUPER Repositories are used for storing artefacts which are produced, utilized and exchanged by the SUPER components – SBP Library stores artefacts which are created during process modelling, i. e. process models, process fragments, and process mediators – SWS Repository stores artefacts related to Semantic Web services – Execution History stores the audit trail of the executed process instances 55

SUPER Architecture • SUPER Platform Services comprise the basic services which provide their functionalities for all SUPER tools and components – – – • Transformation Services translate among different formats of SUPER artifacts SBP Mediation resolves heterogeneity problems between different business processes Data Mediation is responsible for handling ontology level heterogeneitie SBP Composition combines services and processes in order to implement activities of the process, where activities can be implemented by one or more services SBP Discovery finds SBP candidates fulfilling criteria specified as WSMO Goals SBP Reasoner provides process behavioural logic-based inference engine capable of reasoning with SUPER ontologies SUPER Execution comprise two execution environments/engines: – Semantic BPEL Execution Engine is a BPEL 2. 0 compliant process engine, which supports the extensions of BPEL 4 SWS and is integrated into the Semantic Service Bus (SSB) – Semantic Execution Environment (SEE) enables discovery, selection, mediation, invocation and interoperability between Semantic Web services (SWS). SEE is a middleware operating on WSMO descriptions enabling flexible interaction between Service Requesters and Service Providers 56

SUPER METHODOLOGY AND DEMONSTRATORS 57

SUPER Methodology Framework The SUPER methodology is a set of phases, methods and techniques to perform activities using SUPER technologies. Like a traditional BPM methodology, the SUPER methodology owns a proper business process “life cycle”, that is enriched with the semantic connotation of the overall SUPER framework. 58

Semantic Business Process Modelling • Semantic Business Process Modelling (SBPM) is the first step of the SUPER Life Cycle • SBPM is concerns with a streamlined, comprehensive, and easy- touse representative model of the real enterprise business processes • Development of the Business Processes Model based on the Business Process Modelling Ontology (BPMO) • Use of a Semantic Process Modelling Environment – WSMO Studio – Integrated BPMO Editor 59

Example: TID Prototype 60

TID Modelling – Demo/Video (http: //www. sti-innsbruck. at/results/movies/tid-modeling-tool-developed-super ) ~ 5 min 61

Benefits of SUPER Modelling • Business Process Modelling Notation (BPMN) independence (BPMO representation) • Discovery of existing Business Processes exploiting the semantic information – Search on specified Business Function, Domain and Patterns – Search on specified Business Goals, KPIs and Business Rules • Automatic validation and simulation of the BPM • Better readibility of models through a clear semantic 62

BPMO Editor Demo/Video (http: //www. sti-innsbruck. at/results/movies/bpmo-editor-part-wsmostudio-developedsuper ) ~ 10 min 63

Semantic Business Process Configuration • Semantic Business Process Configuration (SBPC) is the second phase of the SUPER SBP Life Cycle. It uses the outputs of the SBP Modeling phase and provides inputs for the third phase, the Semantic Business Process Execution • During this phase Modelled Business Processes are configured 64

Semantic Business Process Configuration steps: 1. Derive s. BPEL from BPMO This step enables the translation from the BPMO instance (coming from the SBP Modeling phase) to an s. BPEL ontology 2. Search for possible SWS This step consist in discovery of SWS. Even if the services will be executed in the SBP Execution phase, an early service discovery could be extremely useful to reduce the effort of the service selection before the execution 65

Semantic Business Process Configuration 3. Examine potential data mismatches In this step data have to be examined to identify potential data mismatches. 4. Define data mappings and mediatiors If potential data mismatches are identified in the previous step interface mappings and data mediators have to be created 5. Validate and refine the process In this step the process is validate and potentially refined. The validation is seen as a sort of “compiler” that checks the correctness of the semantic process description before the execution of the process. 66

Semantic Business Process Execution • Modeled and configured Semantic Business Processes are executed • Execution history for SBP Analysis is produced • Automates business activities • Minimizes time-to-offer • Supports – Execution of semantic BPEL processes (BPEL 4 SWS) – Discovery and execution of Semantic Web Services (SWS) 67

Semantic Business Process Execution Scenario SUPER Tooling A user initiates the semantic BPEL During the execution, execution events are 1 SBPELEE delegates the invocation of After the process execution has been 2 6 process by sending a service request published to Execution History for SEE queries the SWS repository to SEE returns the result of “Achieve 3 5 SEE invokes the selected SWS to SEE by passing the WSMO Goal finished, the result is returned to the user. 4 through the Semantic Service Bus to persistence and to the Monitoring Tool for discover the desired SWS. Goal” to SBPELEE. to it. SBPELEE. tracking process executions. Monitoring Tool Request Service 1 6 Semantic Web Service (SWS) Return Result 4 2 5 Invoke Service Achieve Goal Return result to engine Semantic BPEL Execution Engine (SBPELEE) Semantic Execution Environment (SEE) SUPER Execution Environment 3 Semantic Service Bus (SSB) Discover Service Semantic Web Services Execution History SUPER Repositories 68

Semantic Business Process Execution Scenario • • Step 1: A user initiates the semantic BPEL process by sending a service request through the Semantic Service Bus to Semantic BEPEL Execution Engine (SBPELEE ). Step 2: SBPELEE delegates the invocation of SWS to Semantic Execution Environment (SEE) by passing the WSMO Goal to it. Step 3: SEE queries the SWS repository to discover the desired SWS. Step 4: SEE invokes the selected SWS. Step 5: SEE returns the result of “Achieve Goal” to SBPELEE. Step 6: After the process execution has been finished, the result is returned to the user. During the execution, execution events are published to Execution History for persistence and to the Monitoring Tool for tracking process executions. 69

Example: Nexcom Customer Order Management Process Customer uses a client application to start the Nexcom process 1 6 Nexcom process is deployed as a semantic BPEL process 2 5 Supplier exposes its process as SWS. Supplier 70

Benefits from SUPER SBP Execution • Nexcom Use case requirements addressed by the SUPER SBP Execution phase – Supplier matching supported by Semantic Web Service discovery and invocation from within semantic business processes – Allows for more flexible traffic routing – Automates supplier matching and traffic routing process taking into account all existing suppliers – Minimizes time-to-offer 71

SBP Execution Demo/Video (http: //www. sti-innsbruck. at/results/movies/sbp-execution-developed-in-super/) ~ 11 min 72

Semantic Business Process Analysis • Analysis of executed processes • Support of various analysis goals – – Overview over process usage Detect business exceptions Detect technical exceptions Compare As-Is with To-Be • Analysis methods – Semantic Process Mining – Semantic Reverse Business Engineering Semantic Business Process Analysis Semantic Business Process Execution Semantic Business Process Modelling Semantic Business Process Configuration 73

Semantic Reverse Business Engineering (RBE) How do I get the relevant information to redesign and improve my business processes? • Scenario based analysis with predefined content to ensure continuous business improvement – As-Is-Analysis Provide details and statistics about executed processes – Exception analysis Focus on business exceptions (deviation from the standard processes) – Standardisation & Harmonisation Check compliance of processes between organisational units or with predefined guidelines – User & Role analysis Check user and role behaviour and authorizations 74

Scenario Based Analysis RBE Ontology I am interested in all exceptions of the sales process Business Function Ontology Exception Analysis Sales Process How many sales orders were cancelled? Business questions are executed Only business questions semantically The query results are assigned to Exception Analysis on the Execution History Repository formatted and aggregated for and to the Sales Process (log file) either directly or the business user are to be selected through Process Mining Analysis Results Which sales orders are locked for further processing? Business Question Repository How many sales orders are delayed? Where are the bottlenecks in the sales process? Execution History Repository Process Mining 7575

Scenario Based Analysis • • • The business user who wants to perform a specific analysis needs to select the relevant business questions (BQ). If we had just a few questions, this operation could be performed manually. But since we deal with a rich set of BQs, we need a smarter way to select them. Therefore the business user has just to select the relevant concepts within the SUPER ontologies (e. g. , he wants to perform an exceptional analysis, within the sales processes) In this way, the analysis tool is able to automatically select the BQs annotated with those concepts. These Business Questions are either directly executed on the execution history repository or “brought” to the process mining environment. This is dependent on the question. Some business questions can directly be answered (RBE approach), some business questions can only be answered using process mining. Once the respective queries (either triggered by the Business Question repository directly or by the Process Mining environment) are executed on the Execution history repository the query results are formatted and aggregated for the business user. 76

Analysis Results How many sales orders were cancelled? Which sales orders are locked for further processing? ► ► ► Get overview about system usage Find out exceptions within process flow Check conformance to defined Process model Find bottlenecks Get basis information to apply 6 -sigma methodology 77

SBP Analysis Demo/Video (http: //www. sti-innsbruck. at/results/movies/sbp-analysis-developed-in-super/ ) ~ 11 min 78

SUPER DEMO/VIDEO 79

SUPER Demo/Video http: //www. sti-innsbruck. at/results/movies/super-integrated/ ~ 20 min 80

FURTHER SPECIFIC USE CASES IN PROJECTS 81

Transport: e-Freight 82

Manufacturing: MSEE The MSEE 2015 Vision stems upon two complementary pillars, which have characterized the last 10 years of research about Virtual Organizations, Factories and Enterprises: Service Oriented Architectures (SOA) and Digital Business Ecosystems (DBE). • The first Grand Challenge for MSEE project is to make SSME (Service Science, Management and Engineering) evolve towards Manufacturing Systems and Factories of the Future, i. e. : – from a methodological viewpoint to adapt, modify, extend SSME concepts so that they could be applicable to traditionally product-oriented enterprises; – from an implementation viewpoint to instantiate Future Internet service oriented architectures and platforms for global manufacturing service systems. • The second Grand Challenge for MSEE project is to transform current manufacturing hierarchical supply chains into manufacturing open ecosystems, i. e. : – to define and implement business processes and policies to support collaborative innovation in a secure industrial environment; – to define a new collaborative architecture for ESA, to support business-IT interaction and distributed decision making in virtual factories and enterprises. MSEE (Manufacturing Service Ecosystem) was a research project funded by EU, 2011 -2014. 83

Health: Onto. Health - Goals • • • Conceptualize and implement a workflow-enabled IHE * -based transinstitutional information system architecture Determine and categorize functional respectively informational needs as well as non-functional requirements of health care professionals Design and implementation of a semantic service grid for Electronic Health Records based on the information system architecture Identify and prototypically implement selected common clinical services for the semantic service grid Evaluate all concepts with regard to their usefulness and ability to support health professionals * IHE = Integrating Healthcare Enterprise Onto. Health is a research project funded by FWF (Austrian Service Fund), 2013 -2017. 84

Health: Onto. Health – Expected Results • • an IHE-based information system that allows native, dynamic workflow support regardless of the type of the clinical workflow; a user-centered, workflow-oriented and (semi-) formal model to describe functional/informational needs as well as additional non-functional requirements to support automated, semantics-based service orchestration in a clinical context; a semantic-services-enabled EHR (semantic services grid) framework that allows for the (semi-) automatic, dynamic orchestration of services along clinical workflows and problems; selected common services in the context of diabetes Onto. Health is a research project funded by FWF (Austrian Service Fund), 2013 -2017. 85

CURRENT BISINESS TRENDS MICROSERVICES For this part, follow presentation of S. Newman: “Principles of Microservices” (2015), http: //www. slideshare. net/spnewman/principles-of-microservices-velocity 86

CURRENT BISINESS TRENDS BLOCKCHAINS For this part, follow presentation of J. Domingue (2016): “Blockchains a new platform for semantically enabled transactions”, http: //www. slideshare. net/johndomingue/blockchains-a-new-platform-for -semantically-enabled-transactions-public 87

SUMMARY 88 88

DIP achievements • DIP provides an Open Source Architecture for Semantic Web Services – DIP Architecture, DIP API, WSMO 4 J • DIP provides a set of comprehensive tools – WSMX, IRS-III, WSMO Studio, Hybrid Reasoning tool • Real Use Case Implementations have been developed in DIP – Diverse scenarios e. g. e. Merges for emergency weather planning • Standards Impact – W 3 C Member Submissions, OASIS 89

SUPER achievements • SUPER bridges the gap between Business experts and IT experts in setting up new products and processes. • SUPER provides a new set of integrated BPM tools for – Modeling – Automated Composition of Processes • SUPER uses Semantics to gain a new level of automation for the modeling and configuration of business processes. • SUPER tools are based on open standards to guarantee independence from particular vendors. • SUPER enables lower development costs and short time -to-market for new services and products. 90

Further Projects and Current Trends • Semantic Web Services have been applied in a large number of areas: manufacturing, health, transport… • Trends towards fragmentation of labor – technology is following, opening new potentials for Semantic Web Services – Microservices as paradigm – Blockchains as collaboration, payment and trust solution 91

REFERENCES 92 92

References • Mandatory reading: • Referenced materials (movies, slideshares) in this presentation • E-Freight (EC summary): https: //cordis. europa. eu/project/rcn/94475_en. html • MSEE (archived website): http: //interop-vlab. eu/msee/ • Onto. Health: http: //ontohealth. org 93

References • Wikipedia and other links: – – – http: //en. wikipedia. org/wiki/Business_Process_Modeling_Notation http: //en. wikipedia. org/wiki/Semantic_Web_Services http: //en. wikipedia. org/wiki/Business_process_management http: //en. wikipedia. org/wiki/WSMO 94

Next Lecture # Title 1 Introduction 2 Web Science + Cathy O’Neil’s talk: “Weapons of Math Destruction” 3 Service Science 4 Web services 5 Web 2. 0 services 6 Semantic Web + ONLIM APIs (separate slideset) 7 Semantic Web Service Stack (WSMO, WSML, WSMX) 8 OWL-S and the others 9 Semantic Services as a Part of the Future Internet and Big Data Technology 10 Lightweight Annotations 11 Linked Services 12 Applications 13 Mobile Services 95

Questions? 96