As the scale of mining and mineral business and research organizations expand, very quantities of heterogeneous data are generated incrementally from many different sources. The requirement for extracting useful information from the huge data pool in the disparate information systems is becoming increasingly sophisticated. Managing both real-time and historical business and research data is becoming a particularly challenging problem.
Heterogeneity and integration are the fundamental issues. A literature review demonstrates that there is a trend towards open system standards in many industries. While many area-specific data standards (e.g., IREDES and XMML) already exist, there is no single standard or open system which has been accepted as having the extensibility and capability to be a mineral industry wide “standard”, although some have been more popular than others. This exposes a scale problem with no satisfactory solution at present.
The literature review further indicates that Metadata combined with XML technology and using the component based modelling approach offers a promising solution. The Information Resource Planning/Information Engineering approach suggests a feasible approach for our modelling development process. A five-point model is proposed for analysing the Metadata and planning for model development. These solutions combined point to a tactical and strategic approach to research into an extensible mineral information model. The approach is implemented in the case studies.
Two cases with different scopes are discussed and developed. They are:
1. A framework of a working MineML (Mineral Markup Language). MineML is developed as the pilot study for a GML (Geography Markup Language) compliant standard and primarily consists of case specific feature-types which can be used in the mineral industry. The MineML specification is validated by a proof-of-concept Web Service demonstration where mineralogical liberation data is efficiently integrated, transferred and presented in a distributed environment.
2. P9IMP (P9 Information Management Package). A real application of P9IMP based on P9IMM (P9 Information Management Model) framework is developed and successfully implemented. P9IMP allows the viewing or interpreting of data mining output within different contexts. The InfoParser/Thesaurus/Coder services provide a mechanism to tailor the information entity, properties, relationships and operations. This working system provides a powerful platform to evaluate the mechanism, and demonstrate how a well-managed information model framework can help the organization to take advantage of existing knowledgebase.
The case studies are manageable in scope, feasible for development, expose the challenges and illustrate the strengths and weaknesses of our information modelling approach. All presented techniques, methods and models are implemented in real-world scenarios. In developing these cases, the goals have been to implement and validate a common methodology while addressing the general needs for mineral information sharing with the extensible feature on all data entities, without bias to a specific field. This framework is fundamentally extensible in the sense that it can be sustained, interoperates with other existing standards, models and databases, and is flexible to grow in scale, and thus can be applied across different areas.
This thesis addresses the emerging issue of mineral information standardization by proposing a methodology for developing an extensible mineral information model based on the above approaches. This information model is a formal abstract representation of entities of mineral information, including their properties, relationships and the applications that can be performed on them.
It is concluded that the growing power of Metadata with XML technology using a component based modelling approach affords the mineral community great opportunity to leverage the information systems to tremendous advantage, such as: lowering the cost of maintaining and exchanging information, easier exploiting and utilizing the information, thus greatly improving the efficiency of doing business and research.