Tools for the Guidebook for evaluating fisheries co-management effectiveness

Task 3.3: Manage data and information collected

When data and information have been collected, there is a need to organize and store them. Data include information that is not fully processed to the point of being disseminated as an output, such as images and maps. This process is commonly referred to as “data management” and is a critical and often overlooked stage of the data collection and analysis process. Data security and confidentiality is critical for data management. Depending on the scope and extent of the evaluation, data management can be more or less complex. For instance, in some cases, recording data in a simple Excel file, or similar application, and keeping paper records may be sufficient. In other instances, a more elaborate data recording and management system may be required, with the appointment of a data manager and considering the following:

• Determine how collected data will be submitted to the data manager. Both the person submitting the data (data collector) and the person receiving the data (data manager) should have a clear and common understanding of the type of data that will be submitted and the form in which it will be received. This will greatly improve the accuracy and efficiency of the evaluation. Metadata recording (e.g. date, time, location, data collector's name and traceability information) is also critical to the value of the data for any further processing and interpretation.
• Code the data. Data coding is the process of translating each datum point to prepare for analysis. This translation requires a code sheet in which the meaning of data collected and their codes are available to the data manager. Identify a member of the evaluation team who will code the data.
• Develop a system for storing and entering the data. As each datum point is coded, it should also be entered. Data entry is the (often lengthy and tedious) process of moving coded data into a permanent storage location from which to export the data so that it can be analysed. This permanent storage location is known as a database.
• Collate and review the data set. Once data are entered into the database, the data manager is responsible for the collected data and for managing that data. The data manager collates and reviews the data set in order to check for completeness and errors (accuracy). This is known as "data cleaning". If errors or "gaps" (missing datum points) are found in the data set, the data manager should work with the data collector to correct or understand the problem. In some cases, an incomplete data set will reflect and inability to collect a aparticular datum point and cannot be filled in afterwards.
• Make the data available for analysis and sharing. The aim of data management is to make retrieving data simple and reliable. Coded and stored dta are only as good as the ease with which they can be used for analysis and communication. Develop a procedure so that someone is able to make contact with the data manager and request access to data, or receive stored information, from database. Identify who is allowed access and who is not and outline the responsibilities of the people who do have access to the data.
• If data collected are found to be in error, they should not be used. Identify and address any source of error before continuing the analysis. Common sources of error are human errors and sampling errors.

Toolbox navigation

• Step 1 - Planning
• Step 2 - Compilation of information
• Step 3 - Evaluation
  • Task 3.1
  • Task 3.2
  • Task 3.3
  • Task 3.4
  • Task 3.5
  • Task 3.6