By Tisha Davis, Derek Ametam and Joe Wanzala
This is the fifth installment in our series on dtSearch. In the previous posts, we covered how to set up and configure an index. In this installment, we’ll begin exploring how to actually search your discovery data and make the most of dtSearch’s powerful search capabilities. You can find the previous installments here: Part 1, Part 2, Part 3 and Part 4.
dtSearch is built to help users rapidly and accurately find relevant information within massive datasets. It provides a versatile, layered set of search tools that can be used individually or combined for greater power and flexibility. Key components include Search requests, advanced Search features, Search within a Search (i.e. iterative or nested searching), Browse Words, and the User Thesaurus.
In this section, we focus on the core search methods available in the Search request area of the Search dialog box (see Figure 1). Through a practical case example, we’ll demonstrate how these methods can significantly improve search precision, uncover deeper insights, and streamline investigative or research workflows.
- Case Context: The Tucker Jones Matter
To demonstrate dtSearch’s capabilities, we will use an example dataset based on the Tucker Jones federal prison assault case. All names and locations have been anonymized. The government alleged that Jones assaulted two correctional officers, Ted Romanowski and Luke Brownson, when they attempted to discipline him for talking during ‘the count’, a required quiet period. The government’s claims were supported by guard testimony, injury reports, an FBI-302 from a cooperating inmate Frank Madison, and Bureau of Prisons policy documents. The defense view is that he was the victim of an assault by the weightlifter guard and draws on substantial impeachment and alternate narrative material – from the guards’ experience and disciplinary history to statements from other inmates, some with credibility issues.
Below we shall walk through an example workflow of how dtSearch can be utilized to identify facts and inconsistencies in the documents that might support the defense case.
Figure 1.
2. Example Workflow
a. Boolean and Advanced Search Operators
dtSearch supports a wide range of Boolean and proximity operators that let users construct precise and targeted search queries (Figure 1). The examples below are not exhaustive but illustrate several key capabilities.
As a first step in exploring evidence that may support the defense theory, it is useful to retrieve all documents referencing either Luke Brownson or Ted Romanowski. This broad search offers an overview of the materials involving both individuals but does not yet reveal how their names connect within the same context.
i. ‘Or’ Search: Brownson OR Romanowski
Returns all documents containing either term.(For example, the search may return 28 files with 247 total hits.)
After running this search, review the Search Results pane in dtSearch to explore document-level and hit-level details.
To get a better sense of where the two players’ stories overlap, we can search for documents that mention both Brownson and Romanowski by replacing OR with AND. This search retrieves only documents that include both names somewhere within the text.
ii. ‘And’ Search: Brownson AND Romanowski (For example, the search may return 18 files with 198 total hits.)
Now we know that each document in the result set has both entities—but we still don’t know how they are mentioned (e.g., whether they appear together or in unrelated sections). To isolate documents where the names appear in close proximity, we can use a proximity search.
iii. Proximity Search: Brownson w/5 Romanowski
Finds instances where “Brownson” appears within five words of “Romanowski.” (For example, the search may return 15 files with 66 total hits.)
This narrows the focus to passages suggesting a direct connection between the two individuals, such as conversations, joint actions, or co-occurrences in witness statements.
iv. Phrase Search
Search: “I want to talk to a Lieutenant”.
Retrieves documents containing the exact phrase as entered.
v. Wildcard Search
Example: Memo*
Finds word variants beginning with the same stem, such as “memory,” “memos,” or “memorandum.”
In the next installment, we will explore how to leverage dtSearch’s advanced Search features to further refine and expand your searches and allow you to handle common real-world challenges like misspellings, OCR errors, varied terminology, and conceptual relationships.
Cartoon provide by Dataedo