Structuring Data and Content Since 1981
Data Conversion Laboratory (DCL) provides data and content transformation services and solutions.
Using the latest innovations in artificial intelligence, including machine learning and natural language processing, DCL helps businesses structure data and content for modern technologies and platforms.
With expertise across many industries, DCL uses advanced technology and US-based project management teams to solve complex conversion challenges and is a recognized leader in XML, DITA, SPL, and S1000D conversions.
OUR SERVICES
Data Conversion/
Transformation
Convert and transform information into structured formats: XML, S1000D, DITA, SPL, proprietary schemas, and others.
Enrichment
Enrich content with new or inferred metadata to improve the utility, discovery, and interoperability of content.
Entity Extraction
Extract free-form text from textual and form-based documents then generate target XML schema.
Data Harvesting
Website harvesting and AI transformations that deliver structured data to your systems.
QA Validation
Independent review of previously converted content. Provide third-party validation and peace of mind.
Content Reuse
Analyze large document collections to identify content reuse across multiple document sets and source formats.
Structured Content Delivery
Submit structured content to customer platforms such as PubMed, Silverchair, Highwire, and many more.
THE LATEST FROM DCL
PDF: Anatomy of a Document Format and the Paradox it Presents for AI
In 1990, Dr. John Warnock launched his idea for The Camelot Project . The idea was to create a universal way to share documents across computers, operating systems, or networks without losing formatting. The vision was that a document could be created once, then reliably viewed, printed, and exchanged anywhere with the exact appearance preserved. The PDF, Portable Document Format, was sheer elegance in its simplicity yet beneath that simplicity lay a deeply complex codebase engineered to...
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Structured Content Makes AI Work Better
Generative AI systems work best when the information they consume is organized, explicit, and precise. Structured content formats like XML and JSON provide exactly that – content that is machine‑readable, semantically rich, and consistently organized. Document processing is not simply one problem; rather, it comprises three components that must be considered.
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