AI-Ready Scientific Data

Organizations are finding it increasingly hard to compete without making some use of Artificial Intelligence and Machine Learning to support their everyday decisions, guide research or automate next steps. There is an incredible amount to be learned from scientific data gathered from previous work – whether that be early warnings of instruments or processes heading out of control, selecting the best chemical or drug candidate, or investigating trends in results. Historical data analysis can really shift the needle to help expedite decisions and reveal insights that otherwise would not have been possible.

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What Is AI-Ready Scientific Data?

In order for data to be useful to power AI/ML, organizations must have supreme confidence of data accuracy and integrity. By standardizing formats and metadata, organizations can improve accessibility, interoperability, and reusability, providing richer understanding for future use. Collating complete data including metadata is also crucial, as this provides additional context and clarity, which may be important when considering use for AI/ML. It’s also important to collate data from all relevant and reliable sources, in order to achieve more complete data sets which provide greater insights and intelligence.

How Can Organizations Achieve AI-Ready Data?

There are several important considerations for organizations to achieve AI-ready data:

  • Adopt solutions such as LIMS and ELN to support data integrity by providing centralized, automated and secure systems to manage data
  • Ensure data integrity and traceability throughout its entire lifecycle through robust and reliable transfers between lab software and instruments and equipment
  • Apply robust data governance, with clear guidelines around management, compliance, privacy and security
  • Standardize all data and associated metadata in a future-proof format, ensuring it remains Findable, Accessible, Interoperable and Reusable (FAIR)

How Does Splashlake Support AI-Ready Scientific Data?

By providing robust and reliable integrations between systems such as LIMS, ELN, SAP-QM and lab instruments, and managing and storing that data according to FAIR principles, Splashlake gives organizations unquestionable confidence in their scientific data to power AI and ML.

Splashlake AI Companion supports organizations seeking to realize additional value from data by applying Large Language Models.

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