Showing posts with label Cost. Show all posts
Showing posts with label Cost. Show all posts

Saturday, May 30, 2009

Collaboration in Engineering using Semantic Web techniques

Abstract
This article describes how software developers could enable domain experts such as engineers to collaborate on problem solving. The means for this is development using Semantic Web and Web 2.0 techniques to enable end-user programming. This could enable domain experts such as engineers to be involved in the modelling of a problem such as product design, and so understand, assess, and develop possible solutions.

Introduction
Visualisation is necessary to provide traceability for decision making, as an audit trail for information, to justify a decision and/or cost, or to understand a process, or a product data structure. It is necessary to navigate a database in order to validate it, the structure of the visual interface needs to show the structure of the data, and the model. The best way to do this is to relate them all so that any change to the database, changes the structure of the model and this changes the structure of the visualisation, or vice versa . Semantic search allows someone to see results or individual items but enables going straight to this, that doesn’t show the context and the model is still a ‘black box’, unless the Semantic search actually returns the relevant portion of the structure so that the context of the returned information is displayed.

Methodology
The example below illustrates how it is possible to enable refining a search by visualising all the items present in sub-categories of the main category found in the search. McGuinness (2003) explains how ontologies support this functionality and calls this ‘generalization/specialization’ of information. Uschold and Gruninger (2004) describe ‘ontology-based search’ as “Ontology used for concept-based structuring of information in a repository”; and describe the benefit of this as “better information access” This aids the research objectives of ease of use and sharing of information. The use of open standards for representing information makes it possible to enable searches that understand the semantics of the information and so can track all of the relationships between items. This example illustrates the interface for making a search. In this example the user wants to retrieve all the information related to a spar (aircraft wing component).





Semantic Search interface


The result is shown as a series of trees for each item that contains the word spar. Each keyword match is the root of a tree. Each tree shows the item found and all its children and attributes. The example below shows an image of the top part of the results, this is part of the branch for the first item returned.



Results from semantic search

The information is held in linked and related taxonomies/sub ontologies so it is not HTML that is being searched but the taxonomy itself. Because the information is held in a structured way, it is much more likely that searchers will find what they are looking for, because the search can follow the relationships represented in the taxonomy. One of the key objectives of Semantic Web research and Web 2.0 is to make this kind of search possible over the web as a whole. The Semantic Web is a longer-term vision for managing information over the web and Web 2.0 is the shorter-term practical implementation of techniques, which can ease current information search and management problems. A web interface has been developed for Protégé An example of the use of this is the illustration below where a search is made for information on the cure cycle for composites manufacturing. This search is possible as WebProtege[1] has succeeded in providing a web based interface for displaying and searching ontologies, so providing an additional way to enable web access to the test ontologies created for this research.



Web Protégé Interface


The next stage of this problem is to enable interaction and modelling with the returned information. A project was created called Bitriple by Leaver (2008), to enable end-user functionality for this kind of web-based ontology construction and search. The application provides a facility to edit an ontology/ies and instances, and provides tree-based visualisation of the ontology (as shown in the example below). This example illustrates creation of an online aircraft wing ontology. Wing component sub/ontologies created using Protégé can be translated for the Bitriple application to be represented as RDF/XML. An application could be built as an extension to Bitriple to perform calculations and modelling using the information stored. This could assist in allowing domain expert end-user programmers/modellers to create models. Such web applications provide an alternative to spreadsheets, and to single computer based programs; and if installed on a network server, such applications can provide a collaborative model development environment. This would fit in well with both Semantic Web, and Web 2.0 approaches to knowledge creation, allowing structured representation and navigation of information, and end-user interaction, collaboration, customisation and programming via the web. Collaboration can aid people to agree on terminology, and standardisation of calculations used such as for cost rates and currencies. RDF information can be searched with SPARQL[2] (SPARQL Protocol And RDF Query Language), which is used to search the Bitriple application.

A screenshot from the Bitriple application, of ontology creation for an aircraft wing, is shown below :-



Bitriple Ontology Creation Screenshot


Conclusion

If domain experts are not involved in creation of the model, there is no proper way for the knowledge they are encoding to emerge, or for proper collaboration so each expert is best encapsulating the part of the model that they are most expert in. People need to be involved in model creation if they are to understand the model, decision, and how the decision was made. So there is a need for end-user modelling/programming to enable this. Full automation hinders user involvement and traceability, so semi-automated systems that interact with end-users and assist with all stages of the model decision are better. If a person goes straight to the answer how can it be expected that they fully understood the question?

Breaking complex mathematics into modularised traceable steps eases management of it, and visualisation, and allows modelling of different scenarios, and these scenarios demonstrate the emergent properties of the model, enabling decision support. BiDirectional Traceability is needed, traceability between nodes/submodels, and between models, and between suppliers and buyers.

Existing ontologies can be extended for modelling of software systems and engineering systems e.g. PSL, STEPML, UML, SysML can be extended.This research can enable collaborative modelling and interaction, via applying end-user programming techniques to enable domain experts such as engineers and business people to create and interact with the knowledge representation themselves, and co-operate to ensure the representations are useful for addressing their problems, with less software creation barriers. Software developers need to enable such systems to make this all possible.

[1] SPARQL is the query language and protocol for RDF being recommended to the World Wide Web Consortium - (2008) [online]. Available from: http://www.w3.org/TR/rdf-schema/ [Accessed 27 June 2008]. A tutorial has been developed by Dodds - [online]. Available from: http://www.xml.com/lpt/a/2005/11/16/introducing-sparql-querying-semantic-web-tutorial.html
[Accessed 27 June 2008].

[2] WebProtege (2008) Wiki Page [online]. Available from: http://protege.cim3.net/cgi-bin/wiki.pl?WebProtege [Accessed 27 June 2008].
References
Leaver, N. (2008) Using RDF as an Enabling Technology. MSc. Dissertation, University of the West of England, Bristol.

McGuinness, D. L., 2003. Ontologies Come of Age. In: Dieter Fensel, Jim Hendler, Henry Lieberman, and Wolfgang Wahlster, ed. Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential. MIT Press, 2003.

Uschold, M., Gruninger, M., 2004. Ontologies and Semantics for Seamless Connectivity. In: Association for Computer Machinery - Special Interest Group on Management of Data - SIGMOD Record December, 33(4).

Thursday, July 05, 2007

User Driven Modelling - Detailed Explanation - Part 1 - Research Aim

This research arises out of projects to create systems to facilitate management of design and cost related knowledge within aerospace organisations, with the aim of using this knowledge to reduce the costs of designing and manufacturing products. This paper identifies ways that problems arising from the model development process can be addressed, by a new way of providing for the creation of software. We have gained experience from projects, which have used a combination of proprietary software solutions and bespoke software. It is possible to identify the approach of User Driven Programming (UDP) as an effective software development technique. This research unites approaches of Object Orientation, the Semantic Web, and Relational Databases and Event Driven programming. The approach encourages much greater user involvement in software development. The advantages of increasing user involvement in software development are explained by Olsson [1]. The intention of this research is to allow users to create the whole model/program they develop without typing code.

User Driven Programming (UDP) and User Driven Modelling (UDM) are techniques of End-User Programming, http://www.cs.cmu.edu/~bam/papers/EUPchi2006overviewColor.pdf explains End User Programming. A diagram from this presentation illustrates how small a proportion of development is carried out by professional developers.

Categories of User
It is important to distinguish between the two different types of users for the system, as they would work on different parts of the overall system. However a person may be represented in either or both categories.

Model Builders
Model builders create or edit the semantic representation of the model in an ontology editor in order to create models. Model builders do not need knowledge of a programming language, but do need training in how to use the ontology interface to create a model, and some knowledge of the domain to which it is to be applied.

Model Users
Model users make decisions based on their domain knowledge. This type of user manipulates the tree representation to obtain a result based on the input values they know, or otherwise based on default values. They will want to be able to use a model to evaluate a problem in order to help in decision making.

Expertise of Users
Within this paper the terms user, and domain expert are used interchangeably. The user is a domain expert who wants a problem represented and modelled using software. The domain is engineering but our research could be applied to other domains. The users/domain experts may well be computer literate and able to model certain problems using a software tool such as a spreadsheet. For reasons that will be explained later, this is only sufficient for simpler problems. The reasons that spreadsheets should not be used to represent complex models are connected with difficulties in maintaining, extending, and reusing spreadsheet models. This might not be such a problem in future if research such as that of Oregon State and Houston Universities can succeed in automatically generating correct spreadsheets, and solving errors of meaning (semantic errors) [2].

For now, to be able to model a complex problem, the users/domain experts currently must specify their requirements to other software experts, who may or may not have domain knowledge themselves. It is difficult to find and afford those who have sufficient expertise in both the software and the domain. Someone without the domain knowledge may not understand the requirements. Putting the right team together is a difficult balancing act, and sometimes may be difficult or impossible.

Software development is time consuming and error prone because of the need to learn computer languages. If people could instruct a computer without this requirement they could concentrate all their effort on the problem to be solved. This is termed User Driven Programming (UDP) within this paper, and for the examples demonstrated the term User Driven Modelling (UDM) is used to explain the application of User Driven Programming to model development. This research aims to create software that enables people to program using visual metaphors. Users enter information in a diagram, which for these examples is tree based. Tree based visualisation is often a good way of representing information structures and/or program code structures. The software developed as part of this research translates this human readable representation into computer languages. The tree also shows the flow of information. This technique is a kind of End User Programming, research in this area is undertaken by the EUSES (End Users Shaping Effective Software) research collaboration [3].
Our research is explained with examples at www.cems.uwe.ac.uk/~phale/.

References
1 Olsson, E. (2004). What active users and designers contribute in the design process, Interacting with Computers, 16: 377-401.
2 Stanford University. (2006). Stanford University - Welcome to protégé, protege.stanford.edu/.
3 EUSES. (2006). End Users Shaping Effective