Leveraging Big Data in Scholarly Communication Space

Greg TananbaumStrategic Partnerships

Leveraging Big Data in the Scholarly Communication Space

800 K

1 M

600 K

400 K

200 K

1900 1950

Power

2010

Science has scaled up

400xsince 1950 26,560,336

papers since 1811

4,000+new every day

Graph: ReLX Group

These papers represent a global conversation that is happening among researchers across science.

It’s a paper-by-paper conversation that charts the progress of ideas and discoveries across every major field of knowledge.

But given the volume of papers and their complexity, deep engagement increasingly requires new classes of products and services.

AI-enabled systems that are able to read and understand scientific literature at scale.

This is no easy task, considering we’re dealing with the the densest and most information-rich documents on Earth.

When the term “big data” is applied to scientific literature, big doesn’t just mean volume – it also means complexity.

That is what Meta was created to accomplish. To read, understand, and create structured connections across all of scientific knowledge.

Our Mission – Unlock the world’s scientific and technical insights using artificial intelligence.

Founded in 2010 • Team of 25+ • Venture Backed

Toronto (HQ) • San Francisco

Our model is built on content that we’ve obtained from a variety of sources. We have direct indexing partnerships with 40 of the world’s leading publishers, with more being added all the time.

We use the information within papers to generate the world’s largest scientific knowledge graph. We identify, map, and rank the connections between more than 37 million different scientific entities, mapping the entirety of science today and how we got here.

3.5Brecommendations

1Bpaper-concept

matches

422Mcitations

26Mpapers

16Mgenetic elements

20Mconcepts

17Mresearchers

2Mantibodies

407Kdrugs

427Kinstitutes

234Kbacteria

96Kdiseases

85Kproducts

36Kjournals

4.6BKnowledge Graph

connections

The World’s Largest Scientific Knowledge Graph

The Knowledge Graph is the base data set that powers our big data applications – including Meta Science, Bibliometric Intelligence, and Horizon Scanning.

Literature Discovery

Meta ScienceLiterature Discovery

Meta Science

Meta Science is a free AI-enabled literature discovery engine for researchers to stay apprised of the latest developments in their areas of research, explore the evolution of certain topics, and follow high-impact journals and authors.


Meta Science

• 44 million pages representing virtually every person and entity in biomedicine

• Used by researchers at over 1,200 institutions

• Industries include academia, publishing, pharma, life science tools, government

• Benefit to the scientific ecosystem: article discovery


Meta Science

Bibliometric IntelligencePredictive Insights

Bibliometric Intelligence helps journal editors manage the flow of manuscripts they are tasked with evaluating by helping them pinpoint subject-appropriate and high impact manuscripts at the moment of first submission.


It is a quantitative set of tools that complement the qualitative expertise that editors bring to the task of evaluating manuscripts.


• Pre-ranks incoming manuscripts based on deep predictive profiling

• Intelligently cascades rejected manuscripts to more appropriate sister journals within a portfolio

• Currently integrated into Aries Systems’ Editorial Manager, with more integrations to be announced

Horizon ScanningPredictive Insights

Horizon Scanning is a predictive intelligence engine for making sense of emerging topics, disciplinary intersections, and the next "what's hot" areas in science, years in advance.


The system scans scientific and patent literature to identify every entity mentioned in the texts. Those concepts are then analyzed based on a number of semantic patterns within the article sets.


Based on those patterns, the system measures their current global prominence and predicts their future prominence, three years from now.

Our understanding of research developments is like a visible light spectrum. There is so much

going on that are unable to discern.

What big data tools can do is extend our field of vision. Meta is providing tools to process

these signals.

Thank YouFor more information visit meta.comGreg Tananbaum · [email protected]