JARVIS - From Data Silos to Data Synergy
Platform Technology
Information
the last two decades, tools like electronic lab notebooks (ELNs) and laboratory information management systems (LIMS) have achieved what Gartner, Inc.
calls “the Plateau of Productivity.” These transactional systems have proven so popular that multiple instances of LIMS and ELNs, often from different vendors, have proliferated across and within research organizations. Organizations routinely capture experiments and data with good compliance, but their data now resides in isolated data silos that impede scientific decision-making.
Simultaneously, laboratory automation, the pace
and scale of research, and clinical data science have put in-silico augmented research tantalizingly out
of reach. Organizations possess the data that can
help them explore complex biological mechanisms
of action, accelerate the discovery of novel targets, rapidly discover and optimize therapeutics, and fuel artificial intelligence (AI) and machine learning (ML) algorithms. But that data resists interpretation because it isn’t findable, accessible, interoperable, and reusable (FAIR), and most of all, it lacks the scientific context that gives raw data meaning.
This white paper reviews the challenges labs face
in empowering scientists to capitalize on data to capitalize fully on data, R&D’s most precious resource. It also presents a solution to those challenges, a scientific data cloud called Sapio JarvisSM. Jarvis automates data collection, syncing, and parsing from instruments and contextualizes it with data housed in an organization’s scientific informatics systems. Jarvis is designed to increase research efficiency, provide
a centralized location for visualizing and analyzing scientific data, and generate accurate, contextualized FAIR data to drive informed, innovative decision- making and fuel the AI revolution. Above all, Jarvis gives scientists unified access to enterprise-wide data in a simple, familiar, and readily usable way.
