Semantically-aided Data-aware Service Workflow Composition

1. Ondrej Habala, Marek Paralič, Viera Rozinajová, Peter Bartalos Marek.Paralic@tuke.sk Technical University of Košice, Slovakia Semantically-aided Data-aware Service Workflow Composition SOFSEM 2009

2. Content SOFSEM 2009 • Introduction - Semantics and Web services • Motivationfor the SEMCO-WS • Architecture of the system for semantic composition of services • Ontologies for Automatic Workflow Management • Support of Collaboration in the SEMCO-WS Environment • Design of the process of automated data reuse - Workflow Composition and Execution Module • Conclusion and Future Work

3. Introduction SOFSEM 2009 • Semantic Web Services (SWS) – extension of Web Service technologies with semantics in order to automate tasks common when using WS • Tasks: publishing, discovery, selection, composition, invocation, deployment and ontology management • SWS frameworks combine semantic description of WS capabilities, input, outputs and behavior with the syntactic description in WSDL and XML-Schema

4. Semantics and Web Services SOFSEM 2009 • Functional Semantics - supposing that the functionality of a WS is fully described by its inputs and outputs, we can apply matching algorithms • Data Semantics – can overcome restrictions of the syntactical and structural description about data • QoS Semantics - after discovering according to the requirements potentially applicable services, the selection of most suitable service is needed • Execution Semantics - involves e.g. flow of actions, communication patterns, message sequence, preconditions and effects of WS invocations • Domain Semantics - healthcare, bio-informatics, telecommunications, military, school administration

5. Motivation SOFSEM 2009 • Meteorological and hydrological experiments • Lot of data is reused in several experiments • Semantic Composition of Web and Grid Services (SEMCO-WS) – tries to deal also with the “what” of automated workflow composition • New environmental risk management application • Knowledge Based Workflow System for Grid Applications (K-Wf Grid) • Successful, but not everything it was hoped to achieve • Simplified workflow construction • Interesting problem

6. Architecture of SEMCO-WS SOFSEM 2009

7. Ontologies for Automatic Workflow Management SOFSEM 2009 • Aims for using an ontology: • better data organization by adding additional metadata describing semantics of the data available in the system (for describing IOPE), • to conceptualize the domain and provide a vocabulary of terms occurring in it (user communication and collaboration), • ontology captures the domain of risk management and related areas (concepts from geography, meteorology, natural disasters and risk management), • user model that contains information about the user's knowledge and relation to the domain entities.

8. Ontologies for Automatic Workflow Management (2) SOFSEM 2009

9. Support of Collaboration SOFSEM 2009 • our aim is to provide knowledge-based collaboration tool • first we designed the communication tool facilitating the users to communicate in standard ways • then we augmented the tool utilizing the semantic information incorporated in ontology - the main aspects: • processing on-line discussion • dividing the discussion according to given criteria into the units • getting the areas of interest that were discussed • according to these areas of interest offering the previousdiscussions to the given topic or providing other relevant documents

10. Workflow Composition and Execution Module SOFSEM 2009 • Petri net model for the workflow description, • Abstract Workflow Composition Tool (AWCT) is responsible for workflow construction and uses backtracking from the final activity to the initial activities of the workflow, • Executable Workflow Composition Tool (EWCT) - Extended process of workflow refinement that changes an abstract workflow into the executable one, • Workflow Execution Engine (WfEE) is the place where workflow is running in, it works on Petri-net principle of passing tokens,

11. Data Components SOFSEM 2009 URLs of services Descriptions of jobs Component database Token database Token metadata All existing tokens (both created by users and produced by jobs/services Semantics of each component: • What type of data it produces • Its input-output transformation description • Its output-input transformation description Semantic description of all tokens in token database – based on required data parameters, it allows to identify the proper token For each component: • Transformation of input tokens into input data • Transformation of output data into output tokens

12. Workflow Construction Process SOFSEM 2009 Component database Token database Token metadata ? ? X <token type=“mm5out”> <x>120</x> <y>250</y> <start>2008-07-21</start> </end>2008-07-22</end> <width>300</width> <height>150</height> </token> We have found a service which is able to produce the required token; however, it requires two input tokens, and the search continues Now we have found services which need only existing input tokens; so we have a workflow and input data, and the application may start We have produced the required output token (which represents the output data), the workflow has finished We start with the semantic description of the required output We look for a token which would satisfy the requirements No such token is found; we look for a service or job which can produce token of such type

13. Workflow Execution Process SOFSEM 2009 map Input places Activity timedata Output places data animation config <inputStruct> <mapFile> map317.tif </mapFile> <dataFile> dispData.bin </dataFile> <density> 12 </density> <startTime> 1280982 </startTime> </inputStruct> <timedata> <timeData> simul-out.txt </timeData> </timedata> <outputStruct> <timeData> simul-out.txt </timeData> <animation> spread.avi </animation> </outputStruct> <map> <mapFile> map317.tif </mapFile> </map> <anim> <animation> spread.avi </animation> </anim> <data> <dataFile> dispData.bin </dataFile> </data> <config> <density> 12 </density> <startTime> 1280982 </startTime> </config> 1. We need input data 2. Input tokens are combined into input data for the service or grid job 3. This input data is used to call the service, or execute the grid job 4. The service/job returns output data 5. The output data is divided into tokens; these are annotated by metadata and stored into the database

14. Prototype implementation of EWCT and WfEE SOFSEM 2009 • The functionality of this module was already tested at the text-mining workflow that links together text mining services,

15. Conclusions and Future Work SOFSEM 2009 • Software solution for automatic service workflow management, which considers not only services, but also existing data in workflow construction, • Ontology describing semantics of the services from which the workflows are being composed, as well as of the available data and of the users which use the software, and of course the domain vocabulary, • Users are able to exchange data and knowledge, and cooperate in the workflow construction and execution process. • Future research: • full management of services using the WSRF family of standards, • richer monitoring during the execution phase in order to get more relevant QoS parameters