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Document Search

Document Central offers a comprehensive Document Search page, designed to help users in effortlessly locating documents stored within the Database, Azure Blob Storage, or SharePoint, which processed through Document Central. This intuitive Document Search page contains many customizable configurations, allowing users to finely tailor their searches. These advanced filtering options are instrumental in streamlining the quest for specific data, ensuring a smooth and efficient user experience.

To open the Document Search page, follow these steps:

  1. Navigate through the DMS by Simova - User role center.
  2. Click on Documents in the ribbon bar and execute the action Document Search.
  3. The Document Search page is opened.

Working with Filters

Starting a search on the Document Search page is simple. First, decide what type of information you need. The filter section offers several options: you can search by record number, date, filename, content type, or group ID. To initiate a search, enter a value in the desired filter or search field and then press Enter on your keyboard.

Using filters to search documents provides several key advantages:

  • Targeted Results: Filters allow users to narrow down search results based on specific criteria, such as record number, date, filename, content type, or group ID. This ensures that users can quickly locate the exact document they need without wading through irrelevant results.
  • Efficiency: The use of filters significantly speeds up the search process, as users can quickly focus on a subset of documents that match their criteria.
  • Ease of Use: Filters offer a straightforward, user-friendly way to initiate searches, making them accessible even for users who may not be familiar with the specific content of the documents.

Metadata search allows users to locate documents based on specific metadata attributes associated with the documents. This type of search is particularly useful when the exact content of the document is unknown, but other identifying details are available.

To perform a metadata search, enter a search term in the Metadata Search field. The search term can be a single word or a phrase and can be combined with other search filters. Press Enter on your keyboard to start the search.

Metadata search can be combined with other filters, such as full-text search or specific content type, to narrow down the results. For instance, you can search for documents authored by "Jane Smith" that were created in the last month and contain the keyword "budget."

Metadata search offers several distinct benefits:

  • Precision in Document Retrieval: By searching based on metadata attributes such as title, author, creation date, tags, and document type, users can find documents with a high degree of accuracy, especially when the content is not specifically known.
  • Enhanced Organization: Metadata search encourages the use of consistent and detailed metadata, improving the overall organization and management of documents within the system.
  • Combinatory Power: The ability to combine metadata search with other filters, such as full-text search or specific content types, allows for highly refined searches, enabling users to drill down to very specific subsets of documents.

Working with Full Text Search

The Full Text Search function is available for SharePoint and Azure Blob Storage repositories. This powerful feature allows you to search within the content of documents, beyond just filenames or metadata. It scans the actual content, providing a comprehensive and accurate search experience.

SharePoint

The Full Text Search is available for the SharePoint repository with a SharePoint Online.

Azure Blob Storage

The Full Text Search is available for the Azure Blob Storage repository with Azure Cognitive Search enabled.

To use Full Text Search, enter a search term in the Full Text Search field. The search term can be a single word or a phrase and can be combined with other search filters. Press Enter on your keyboard to start the search.

Full Text Search supports logical operators such as AND, OR, and NOT, allowing for precise and complex search queries. This feature also supports various data formats, including DOCX, XLSX, PPTX, and PDF.

Operator Description and Examples
AND Finds documents containing all specified words. Example: apples AND oranges finds documents with both terms, though they may not be adjacent.
OR Finds documents containing any of the specified words. Example: apples OR oranges finds documents with either term.
NOT Excludes documents containing certain words. Example: invoice AND NOT January finds documents with "invoice" but excludes those mentioning "January."

Warning

  • Logical operators must be written in capital letters to be recognized correctly.
  • Not all data formats are supported, such as JPG, PNG, and PDF/A-3.

Full Text Search offers powerful capabilities for in-depth document searches:

  • Comprehensive Content Search: Unlike metadata or filter-based searches, full-text search delves into the actual content of documents, making it possible to find specific phrases or keywords within the body of the documents. This is invaluable for retrieving documents based on detailed content.
  • Advanced Query Customization: With support for logical operators (AND, OR, NOT), users can construct complex search queries to fine-tune their search results. This precision is particularly useful when looking for documents that meet multiple criteria.
  • Broad Format Support: Full Text Search supports various data formats, such as DOCX, XLSX, PPTX, and PDF, ensuring that users can search through a wide range of document types.

The search can also be used to search for related documents, If the search is used, and the Document No. field is filled, a query will pop up if no document is found. If you click on yes, a new page for the related documents will open. On this page, the related document source is displayed. If you click on the entry count, the related documents from this source will be displayed.

Searching for related documents provides additional contextual insights:

  • Contextual Understanding: This feature allows users to view documents that are connected through a common process or related to a specific document. It helps users understand the broader context and history of a particular document or series of documents.
  • Process Continuity: By accessing related documents, users can maintain continuity and ensure they have all relevant information, which is crucial for projects that span multiple documents or stages.
  • Efficient Data Retrieval: This search method makes it easy to locate documents that might not be directly searchable by content or metadata but are linked through relational data, enhancing the overall efficiency of document retrieval.