Managing Data from Remeasured 

 Plots: An Evaluation of Existing 

 Systems 



John C. Byrne 

 Michael D. Sweet 



INTRODUCTION 



Remeasured (or permanent) forest growth plots are 

 used for a variety of purposes. By a remeasured plot 

 we mean a plot where tagged trees are measured at 

 successive time intervals for monitoring growth and 

 development. Many activities that are integral parts 

 of forest management rely on data from such plots, 

 including the development and validation of forest 

 growth and yield models, the documentation of changes 

 in forest inventory, and the monitoring of forest health. 

 A system for properly managing the data from these 

 plots is essential to their eventual use. 



Remeasured plots are typically expensive to install 

 and maintain. Therefore, in recent years, organizations 

 have been formed for sharing existing remeasured plot 

 data or for combining resources to install new plots. 

 One such organization, the Inland Northwest Growth 

 and Yield (INGY) Cooperative, consists of a group of 

 universities, Federal and State forestry agencies, and 

 forest industries in the Northern Rocky Mountains. 

 A major thrust of INGY in recent years has been the 

 consolidation of existing plot data from member orga- 

 nizations into a common data base for use in growth 

 and yield model validation. Utilizing data from these 

 diverse sources has been cumbersome, time consum- 

 ing, inconsistent, and very costly, because of two ma- 

 jor factors: (1) the use of different formats and codes 

 by organizations to store information and (2) the lack 

 of capabilities within organizations to adequately 

 manage the data. We addressed the first factor by 

 designing a data structure that provides a standard- 

 ized format for the exchange of remeasured plot data 

 (Sweet and Byrne 1990). The second factor, the man- 

 agement of data, is the focus of this report. This pa- 

 per reports on the results of a 1988 survey of organi- 

 zations that manage data from remeasured plots. In 

 order to evaluate these data base management sys- 

 tems (DBMS), we defined a set of desirable system 

 features. 



DESIRABLE SYSTEM FEATURES 



We defined 12 major features that a DBMS for 

 remeasured plot data should have, based on our 



experiences in managing data from remeasured plots 

 within our own organizations and with cooperators. 

 These features are briefly described below. 



1. Import/export large amounts of data. The sys- 

 tem must allow the input of plot data from existing 

 files (that is, import). For exchange of data, the sys- 

 tem must allow the exporting of data to a common 

 format that is acceptable to other computer systems. 



2. Edit data already in the data base. Data may 

 not be complete or correct when entered into the data 

 base, so the changing of existing data or the addition 

 of more data must be easily done. 



3. Error-check data. The quality of data is im- 

 proved if, before it is entered, it is checked for proper 

 coding, reasonableness of values, proper data types, 

 and the uniqueness of variables used as keys. 



4. Store large amounts of data. Data accumulate 

 rapidly after several measurements of a set of plots, 

 and the system should be capable of handling it. 



5. Store remeasurement data. All measurements 

 taken on a plot over time should be stored such that 

 successive measurements can be compared. 



6. Safeguard the data and their integrity. Data 

 are safeguarded by providing for safe, long-term 

 backup, the control of individuals allowed to change 

 data, and the documenting of changes made to the 

 data base. 



7. Provide for recording commonly measured plot 

 and tree characteristics. Data fields should be pro- 

 vided for recording both common plot-level measure- 

 ments (for example, sampling design, location, site 

 characteristics, etc.) as well as tree-level measure- 

 ments (for example, tree number, species, diameter, 

 height, etc.) for more than one measurement. 



8. Ability to add new data fields. Data require- 

 ments change over time, so the data base should have 

 the flexibility to allow new data fields without major 

 reprogramming of the software. 



9. Selective retrieval of data from the data base. 

 The ability to query the data base permits the user 

 to retrieve data to address a specific question. 



10. Accessibility of the data base software at a 

 reasonable cost. The data base software should be 

 nonproprietary and reasonably priced and thus en- 

 hance availability and use. 



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