Meta-data model

The following considerations apply to the verification documents at the lowest level of the document hierarchy shown in Section 8.2. The main objective of the verification documentation is that for all GxP-relevant processes traceable information is generated, accessible for the legally prescribed retention period. The purpose of the following meta-data model is to enable the complete traceability of the information and data, using the meta-data. From this information, no results can be derived, but they are an indispensable part of the raw data. 

In study-based quality management systems, such as good laboratory practice (GLP) and good clinical practice (GCP), the study number is considered as the main index variable and any other information along the meta-data model can be derived from it. With the help of the meta-data model (see Box Meta-Data Model), it can be checked easily if the information of the documented GxP-relevant process is complete. 

Each machine printout or manually generated entry should be checked by the meta-data model to ensure traceability. Only when all six questions can be fully answered, the data are traceable in the sense of authority requirements. 

Objectives of Documentation 311 Table 8.3 Meta-data model of data traceability in an HPLC laboratory. 

Siltanen, P., Syrjanen T., Kuusisto M., 1999, XML-based meta-data modelling for product data management. In Proceedings of PDT Europe 99. Stavanger, Norway. 

Besides the scientific questions related to the coupling of models, the interaction of the numerical models is a big technical challenge. The transformation of data at different temporal and spatial resolutions as well as computational efficiency, memory consumption, data storage capacity, meta-data communication and code management are issues which have to be addressed. 

The model developer who wants to couple the models (1) has to include coupler-specific interfaces in the models, and (2) has to provide the model and coupling meta-data according to standards of the coupling software. Both tasks can be time consuming, and the gain of interoperability has to be balanced against the costs of the implementation. 

Concerning the implementation aspects of FireS, we will concentrate on modeling the dynamic behavior. The graph schema shown in Fig. 5.67 defines the abstract syntax for the collaboration diagrams used in phase 4. It is an extension of the formerly introduced graph schema of Fig. 5.60, which serves as meta model for defining the static data model in phase 3. 

Bernstein PA (2003) Applying model management to classical meta-data problems. In Conference on innovative data systems research (CIDR), Asilomar, CA, pp 209-220... 

However, the historical meta-data does have a certain degree of influence on the new treatment through under the random effects model, but not under the fixed effects model. Under both types of meta log-linear regression models, when analyzing the current data, the historical data can be borrowed only through the common parameters, namely, (yq, or Yq. For this reason, Ibrahim et al. (2012) called the power priors given in (2.18) and (2.19) partial borrowing power priors. 

From Table 2.3, we see that the posterior means of Yo based on the historical meta-data were -3.799 imder the random effects model and -4.241 under the fixed effects model. Thus, the posterior mean of Yo based on the historical... 

As discussed earlier, the historical meta-survival data can be partially borrowed through the two common parameters Yq and under the random effects model but through only one common parameter Yo under the fixed effects model. This implies that under the same value of ag, that is, the same amount of incorporation of the historical meta-survival data, the power is higher under the random effects model than under the fixed effects model. On the other hand, the design value of Yo in the current metatrial is more comparable to the value of Yo in the historical meta-data under the fixed effects model than under the random effects model, which explains why more historical meta-survival data can be allowed to be borrowed under the fixed effects model than the random effects model. From Figure 2.1, it is interesting to see that (1) both the power and type I error... 

A real prerequisite for SE is the alignment of methods and models of the disciplines involved in product development. Investigations that are performed by an arbitrary discipline do not need only a data set of another discipline as input, instead additional meta-data such as the maturity level are necessary. 

A 3D PDF document containing 3D geometry models as well as additional meta data is shown in Fig. 11.16. 

Equation (6.12) comprises all possible relationships that may exist in system instance w. To keep the model simple, we will refer to the problem model Eq. (6.3) as the object model and to the set of relationships as R. A problem model is an abstract representation of a problem domain—a meta-model. Ontological commitments are for developing a data model out of this meta-model. These commitments are interfaces between abstract problem representation and real world data storage. Rearranging the standard definition, we can define a model M as a stmcture (S, /), where S = (T, R) is a global stmcture (standard system definition) and 7 is an interpretation function assigning elements of T to constant symbols (variables) of V. 

HLA has an object-oriented world-view, which is not to be confused with OOP (object-oriented programming) because it doesn t specify the methods of objects, since in the common case this is not info to be transferred between federates. This view does only define how a federate must communicate with other federates, while it doesn t consider the internal representation of each federate. So, a simulation object model (SOM) is built, which defines what kind of data federates have to exchange with each other. Furthermore, a meta-object model, the federation object model (FOM), collects all the classes defined by each participant to the federation in order to give a description of all shared information [56]. 

As last step, vehicle tracks and velocity as well as the distance estimate are merged with the current environment model M. This meta-data is attached to each frame and fed into the subsequent rendering pipeline (see Sect. 4). This combined data does not only provide the spatial and temporal reconstruction of the rear-ward traffic scene but with the time-to-impact the risk potential of a collision for each trailing vehicle is given as well. 

The ontology-based representation also improved the model management process. For instance, it was straightforward to search for components in a model library that have a certain type of connectors by using a simple query. The design models can also be enriched with other types of semantic relationships that improve the documentation of the model. Different types of meta-data can be attached to components in the ontologies, such as, provenance, version, release status, etc., that plan an important role in the development process. 

The 3DIS data modeling constructs support (1) information objects of various levels of abstraction and modalities, (2) dynamic descriptive and structural information (meta-data), and (3) user design, manipulation, and evolution of databases. Data and meta-data are handled uniformly. 

DIS databases contain collections of interrelated objects which represent any identifiable information fact For example, a part screwlO, a parts attribute Weight, a string of characters SC342P, a part s type (meta-data) SCREW, and a procedure Add-To-Inventory, are all modeled uniformly as objects. What distinguishes different kinds of objects is the set of structural (meta-data) and non-structural (data) relationships defined on them. 

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