Class exercise II: Use Case Implementation

1. Class exercise II: Use Case Implementation Deborah McGuinness and Joanne Luciano With Peter Fox and Li Ding CSCI-6962-01 Week 7, October 18, 2010

2. Contents • Review of use case presentations, questions, comments • Implementing a use case – this is where it can get tough and complicated for semantics • Summary • Next week

3. Semantic Web Methodology and Technology Development Process • Establish and improve a well-defined methodology vision for Semantic Technology based application development • Leverage controlled vocabularies, et c. Adopt Technology Approach Leverage Technology Infrastructure Science/Expert Review & Iteration Rapid Prototype Open World: Evolve, Iterate, Redesign, Redeploy Use Tools Evaluation Analysis Use Case Develop model/ ontology Small Team, mixed skills

4. Implementation Basics • Review your use case with team and experts • Go into detail of your ontology; test it using the tools you have • We will look at the use case document and examine the actors, process flow, artifacts, etc. • You will start to develop a design and an architecture (more on architecture and middleware next week) • Keep in mind that it is more flexible to place the formal semantics withinin your interfaces, i.e. between layers and components in your architecture or between ‘users’ and ‘information’ to mediate the exchange

5. Actors • The initial analysis will often have many human actors • Look to see where the human actors can be replaced with machine actors – many will require additional semantics, i.e. knowledge encoding • If you are doing this in a team, take steps to ensure that actors know their role and what inputs, outputs and preconditions are expected • Often, you may be able to ‘run’ the use case (really the model) before you build anything

6. Process flow • Each element in the process flow usually denotes a distinct stage in what will need to be implemented • Often, actors mediate the process flow • Consider the activity diagram (and often a state diagram) as a means to turn the written process flow into a visual one that your experts can review • Make sure the artifacts and services have an entry in the resources section • Often the time you may do some searching

7. Preconditions • Often the preconditions are very syntactic and may not be ready to fit with your semantically-rich implementation • Some level of modeling of these preconditions may be required (often this will not be in your first-pass knowledge encoding, which focuses on the main process flow, i.e. goal, description, etc.) • Beware of using other entities data and services: e.g., policies, access rights, registration, and ‘cost’

8. Artifacts • Add artifacts that the use case generates to the resources list in the table • It is often useful to record which artifacts are critical and which are of secondary importance • Be thinking of provenance and the way these artifacts were produced, i.e. what semantics went into them use this information to produce suitable metadata or annotations • Engage the actors to determine the names of these artifacts and who should have responsibility for them (usually you want the actors to have responsibility for evolution)

9. Reviewing the resources • Apart from the artifacts and actor resources, you may find gaps • Your knowledge encoding is also a resource, make it a first class citizen, i.e. give it a namespace and a URI • Often, a test-bed with local data is very useful at the start the implementation process, i.e. pull the data, maybe even implement their service (database, etc.)

10. Back to the knowledge encoding • Declarative: in CL, OWL (probably OWL-DL), RDF, SKOS? • Need rules? • Need query? • Science expert review and iteration • Means you need something that they can review, with precise names, properties, relations, etc. • The knowledge engineering stage is much like a software engineering process

11. Knowledge engineering • Classes 2, 3, 5 and 6 • Mostly choose OWL-DL (and OWL 2) • We may need to go to OWL 2 for numerical comparisons and if so, separate your owl 1 from OWL 2 representations • The interplay between tools like Protégé and CMAP will be very important in implementing a knowledge base that has ‘just enough’

12. Implementation Basics • Review documented use case now • Go into detail of the ontology • Now we will look at the use case document and examine the actors, process flow, artifacts, etc. • Start thinking of a design and an architecture • Semantics between/ in your interfaces

13. Roles and skill-sets • Facilitator – changes slightly for implementation - sometime the facilitator becomes chief architect, sometimes steps back • Domain experts are needed for expert review (domain literate, know resources; data, applications, tools, etc) • You are the modeler (to extract objects, triples) • You are likely to play the role of a software engineer (architecture, technology) but you can also ask someone for help with this • Document, document, document • It is social – a team effort

14. Use case roles and skill-sets • Time for a self assessment • We will scope for the purpose of learning how to …

15. Implementing • Let’s take a few examples • VSTO • BCO-DMO

16. Summary • By now, the reality of going into complete detail for the knowledge representation should be apparent • Keeping it simple is also very important as you begin to implement • Being prepared to iterate is essential • Now is the time to validate your ontology with domain experts and your team, use the tools • The next stage is to choose your technology components and build and test

17. Environmental Cleanup • To determine the hazardous waste sites in New York State that contained VOC contamination at or above their federal guidance value in groundwater and were remediated via Soil Vapor Extraction. • The goal of this use case is to provide technical staff and stakeholders with the ability to access data for hazardous waste remediation sites across New York State. It allows project managers to find and analyze sites similar to their own in order to make better decisions. It also improves the ability to collaborate both internally and externally.

18. Domain expert • Chris + ?

19. Deep Sea Research Preparation • An oceanographer is preparing for a cruise that will be making use of one of the National Deep Submergence Facility vehicle (operated by the Woods Hole Oceanographic Institution). They will be diving in the Galapagos hot vent area and want to: • see an organized list of links to related publications, Oceanus articles, data library holdings, video snapshot sequences, and any other datasets available in the various repositories. • get a list of researchers who have published journal articles about this particular area.

20. DSRP Resources • Bibliography of all journal articles that mention one of the deep submergence vehicles by name • Text of some of the articles from the bibliography • A CSV file containing a list of Oceanus magazine articles and keywords associated with these articles • An inventory of video and still imagery held by the data library • The Alvin Vehicle Framegrabber website (with video snapshots available) • The Jason Virtual Control Van website (with video snapshots available)

21. More resources • NDSF bibliography link -- http://dlaweb.whoi.edu/DIG_RES/NDSF_bib.html • Holdings spreadsheet • Jason control van website -- http://4dgeo.whoi.edu/jason/alvin • Framegrabber -- http://4dgeo.whoi.edu/alvin

22. Domain experts • Andy Maffei, Lisa Raymond (WHOI)

23. Assignment 3 • Team use case implementation • On the wiki • Write up and presentation • Due November 22 • Team 1: Environmental Cleanup • Chris, Xiang, Jim, Shankar • Team 2: Deep Sea Research Preparation • Eric, Yongmei, Selcuk, Tim

24. Next week • This weeks reading assignment: • reading: IAAI VSTO, Semantic eScience Web Services and C&G paper • Next class (week 8 – October 25): • Foundations V: Infrastructure and Architecture, Middleware • Questions?