Table of Contents
Data collection is a major step in the intelligence cycle, as it involves gathering the information to be used in other stages of the process and delivering the intelligence product to the relevant decision makers.
Reliable and trustworthy data can be obtained from a wide variety of sources: OSINT (open-source intelligence), WEBINT (Web intelligence), IMINT (imagery intelligence), HUMINT (human intelligence), VIRTUAL HUMINT (virtual intelligence), and SOCMINT (social media intelligence), among other sources.
One of the main problems faced by intelligence professionals when collecting data is related to the vast amount of information that can be found, which can lead to chaos and disorganization. That is why professionals need to set certain limits to collection activities in order to render these tasks actionable (for instance, by clearly defining the quantity of information that can be assessed). Data obtained can be redundant, come from a number of sources and present different formats, making it difficult to process them efficiently.
To avoid these difficulties, professionals can implement a collection plan at the beginning of the collection step, which will allow them to focus on particular targets.
Data Collection Plan
A collection plan is a document that guides professionals through the acquisition of information. It includes a comprehensive list of the sources and resources to be used for searching and retrieving information in an effective way.
This plan needs to be as detailed as possible, beginning with a general overview of the types of collection systems that will be applied. When resorting to OSINT searches, it is important to specify all the sources to be consulted, together with their corresponding description. Similarly, for VIRTUAL HUMINT searches, the plan has to include the resources to be used and how tasks should be performed.
Steps in the Collection Plan
To begin with, collection plans need to list all the questions and information requirements that must be addressed, together with a general classification of the domains to be exploited.
Those questions are to be agreed with the appropriate decision maker and intelligence team managers, and have to focus on the specific needs of the intended research. Questions have to do with where the information is, how it is going to be obtained and how it is going to be accessed.
Once initial characteristics are defined, collection plans have to integrate the tactical requirements of the search.
This tactical approach should guarantee that search orientation is correct and use all the tools, sources and resources at reach, depending on the type of data collection to be performed.
During this process, professionals can resort to web resources, for instance by using dorks in search engines, as well as to technical tools in order to obtain further details, verify existing data or gather additional information. Search objectives need to be clearly defined and kept in mind at all times, which will allow them to allocate all available resources to find relevant information.
However, additional resources and tools might be needed sometimes to trace certain data, and these should be specified in the Resources and Logistics section. This chapter provides a description of the requirements for data searching and collecting, and the use of virtual machines, virtual private networks (VPNs) or information management systems are to be detailed accordingly. In short, this section serves as a provision of the required items to ensure the successful execution of the project.
intelligence collection plan – Conclusions
Once the collection plan is implemented, the next stage can be started, consisting on gathering raw information following the requirements already defined. This will allow professionals to obtain detailed and classified information while reducing difficulties associated with disorganization in data collection and the generation of massive amounts of information.
When using a well-designed data collection plan, moving to next stages in the intelligence cycle will be easier and smoother, helping intelligence analysts to process the information collected. This will eventually contribute to the efficiency improvement of the whole intelligence process.