APPENDIX C. LOGICAL MODEL ENTITY RELATIONSHIP DIAGRAM

This diagram expands on the conceptual model to demonstrate the structures within a relational database. There is an ERD for segment, intersection, intersection leg, interchange and curves and grades.

List of Figures

Figure 1. Role of Improved Data Collection Efforts in Safety Outcomes

Figure 2. MIRE MIS Data Flow Diagram.

Figure 3. Model MIRE MIS Entity Relationship Diagram

APPENDIX B. CRASH DATA OVERVIEW ENTITY RELATIONSHIP DIAGRAM

Notes: The primary key in this case is the unique location identifier. The foreign key(s) may indicate another linkage key such as a bridge identifier or a crash identifier.

Source: Model Electronic Crash Data Collection System (11).

APPENDIX A. KEY TO DATA FLOW DIAGRAMS

A Data Flow Diagram (DFD) is a graphical means of describing the flow of data through a system that produces, changes, or stores data. The DFD is a visual depiction of an automated or manual system from the perspective of the data. A DFD differs from a flowchart in its perspective: a flowchart describes a system of programs or manual processes that manipulate the data, while a DFD describes a system from the perspective of the flow of information. A DFD is drawn from most general to most specific in a series of levels of detail.

REFERENCES

1. Lefler, Nancy; Forrest Council; David Harkey; Daniel Carter; Hugh McGee; and Michael Daul. Model Inventory of Roadway Elements—MIRE, Version 1.0. FHWA-HRT-10-048, Federal Highway Administration, Washington, DC, October 2010.

CONCLUSION

The MIRE MIS concept offers many potential benefits to agencies safety programs. The MIS brings together data from many sources. Each of these sources pertain to safety issues and can provide valuable information in determining where safety can be improved and what measures may be most effective.

DATA QUALITY

One of the key findings of this report was the importance of data quality. The research team organized the management of the system development process into three parts to ensure data quality for the MIRE MIS:

DEVELOPMENT OF THE CONCEPTUAL STRUCTURE OF THE MIRE MIS

The first objective of this project was to develop a conceptual model of a MIRE MIS. This section provides a broad overview of the conceptual model including the potential business functions and methodologies an agency would need to undertake in order to implement a MIRE MIS. The research team predominantly based the design of the MIRE MIS on the MIRE data inventory published in 2010 (1). Ideally, agencies will integrate MIRE MIS with other roadway- related and supplemental databases that a State needs for safety analyses.

INTRODUCTION

The need for improved and more robust safety data is increasing due to the development of a new generation of safety analysis tools and methods.

EXECUTIVE SUMMARY

Safety data are the key to making sound decisions on the design and operation of roadways. The need for improved and more robust safety data is increasing due to the development of a new generation of safety data analysis tools and methods. The ability to link roadway and traffic data with other safety data sources allows States to better identify where the problems are, what those problems are, how best to treat them, and how to evaluate the treatments.