Digital PDF vs. machine-readable JSON format
Automatically process (un)structured data from documents
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In today’s digital world, we face the daily challenge of efficiently processing and managing large volumes of information. Two of the most commonly used formats for representing and storing this information are PDF (Portable Document Format) and JSON (JavaScript Object Notation). While both formats are widely used, they serve different purposes and play crucial roles in intelligent document processing (IDP).
PDF – The Universal Format for the Visual Representation of (Un)structured Data
PDFs have long been the standard for displaying documents that need to look consistent across different devices and platforms. They are ideal for sharing formatted content like reports, forms, and presentations. However, PDFs are mainly intended for the visual representation of information, which means the data contained within is often not directly accessible or editable. Manual extraction or specialized OCR (Optical Character Recognition) software might be required to access the data inside.
JSON – The Machine-readable Format for Structured Data
On the other hand, there is JSON, a lightweight data interchange format known for its simplicity and readability. JSON is especially popular in software development and data exchange between web applications because it can be easily processed by machines. It represents data in a clear, structured format that is directly accessible without additional conversion.
The Role of PDF and JSON in Intelligent Document Processing (IDP)
IDP is an emerging field aimed at revolutionizing the way companies process and manage documents. It incorporates technologies like Machine Learning (ML), Natural Language Processing (NLP), and Computer Vision to efficiently extract and process information from various document types.
In this context, both PDFs and JSON play important roles:
Document Capture and Classification: IDP solutions often begin with capturing PDFs, as these are the most commonly used format for incoming documents. Classifying the document type – be it an invoice, a contract, or a form – is the first step. Technologies like OCR can already help convert visually presented information into machine-readable data.
Data Extraction and Structuring: Once PDFs are identified and digitized, JSON comes into play. The extracted data is often stored in a structured, machine-readable format like JSON. This allows for easy analysis, further processing, or integration into other systems, such as DMS or ERP software.
Workflow Automation: The JSON format plays a crucial role in automating business processes, as it is straightforward to create APIs (Application Programming Interfaces) that send and receive data in JSON format. This enables companies to automate workflows, organize documents, and utilize relevant information more efficiently.
Analytics and decision-making: Since JSON data is well-structured, it is excellent for analytical purposes. Companies can use IDP tools and methods to gain deeper insights into their data and make data-driven decisions more quickly and effectively.
PDF: The Dual Role in the IDP Process
An exciting aspect of intelligent document processing (IDP) is the dual role that the PDF format plays. PDFs serve not only as a common input format but also as a useful output format. Incoming PDFs are processed, classified, and the contained information is extracted into a structured format like JSON using technologies. This JSON dataset contains all necessary information for document classification and content extraction. Once the data is analyzed and further processed, it can be compiled into a newly generated PDF. This PDF can then be automatically sorted into an existing document management system (DMS), enriched with additional metadata, significantly simplifying and optimizing workflows.
IDP as a Catalyst for Existing DMS, ECM, and ERP Software
IDP acts as a catalyst that drives and enhances existing DMS, ECM, and other software rather than replacing them. By integrating IDP technologies, these systems become more powerful as they access, analyze, and utilize information more efficiently in corresponding business processes. This enables companies to fully leverage their existing systems and expand their capacities to keep up with the ever-accelerating pace of business. IDP offers the opportunity to modernize existing structures and adapt to modern needs by bridging the gap between traditional document formats and digital data processing.
Conclusion
Although PDF and JSON seem like opposing approaches to document processing at first glance, they complement each other optimally in practice. PDFs facilitate access to extensive document-based information, while JSON enables the efficient processing of this information by machines. In intelligent document processing, they jointly offer businesses the ability to work not only more efficiently but also make smarter business decisions.
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