esh_logo Developing collaborations and technology for evidence synthesis

whiteboard Evidence synthesis (ES) is the process of converting scientific outputs - such as articles, reports and data - into reliable and digestible evidence that can inform management or policy.

ES is critical to evidence-informed decision-making in a range of fields from environmental conservation to medicine; but ES projects can be particularly time-consuming and resource-intensive.

We believe that ES can be made more resource-efficient, timely, transparent, rigorous and accessible by developing and improving the ecosystem of available Open Science tools for effective synthesis.

We created the Evidence Synthesis Hackathon (ESH) series to bring together interested researchers, practitioners and coders to discuss and develop new Open Source technologies for ES applications.


Key Projects

metaverse
metaverse

Evidence synthesis workflows for R

Grey Literature
Grey Literature Reporter

Chrome plugin for grey literature searching

metaverse
eviatlas

An R tool for exploring systematic map databases



ESHcon 2020

Our next event will be a virtual conference on R tools for evidence synthesis. If you work on software tools for meta-analysis, systematic review or related fields, then this is for you!

Details are still TBC, but you can see our event page here


Core Contributors

Adam
Adam Dunn
  
Matt
Matt Grainger
  
Eliza
Eliza Grames
  
Charles
Charles Gray
  
Neal
Neal Haddaway
  
W.
W. Kyle Hamilton
  
Emily
Emily Hennessy
  
Luke
Luke McGuinness
  
Shinichi
Shinichi Nakagawa
  
Daniel
Daniel Noble
  
Matthew
Matthew Page
  
Christopher
Christopher Penkin
  
Daniel
Daniel Perez
  
Alfredo
Alfredo Sánchez-Tójar
  
Ezgi
Ezgi Tanriver-Ayder
  
Juan
Juan Vásquez
  
Wolfgang
Wolfgang Viechtbauer
  
Vivian
Vivian Welch
  
Martin
Martin Westgate
  

News

    / Choosing databases for Systematic Reviews
    An Interview with Michael Gusenbauer
    Michael Gusenbauer is an assistant professor at the Institute of Innovation Management (ifi) at Johannes Kepler University (JKU) Linz. Here Michael talks about his recent article with Neal Haddaway on selecting academic search systems for systematic reviews.



    / Technology paves the way for African evidence synthesis
    Planning for ESH Johannesburg 2020

    This is a version of our article ‘The Evidence Synthesis Hackathon: A global community building technology for more rigorous, efficient, and just evidence synthesis’, published by The Conversation, 1 July 2019.


    / Introducing EviAtlas
    In discussion with the EviAtlas team
    EviAtlas is a brand new tool for visualising evidence bases produced within systematic reviews and systematic maps, helping researchers to create interactive graphics and identify patterns, gaps and clusters in the evidence. EviAtlas was produced by a team of volunteers working across three Evidence Synthesis Hackathon events (ESH2018, miniESH2018 and ESH2019). Here, we speak to the team about their new tool and their experiences with ESH.



    / Reflections on ESH Canberra 2019
    An interview with Martin Westgate
    Martin is a co-founder of the evidence synthesis hackathon series and part of the organising team for ESH 2019, which was held at the University of New South Wales' Canberra campus in April. Here he reflects on that event and where the ESH series is headed next.



    / Building metafor
    An interview with Wolfgang Viechtbauer
    Wolfgang is associate professor of statistics at Maastricht University. In addition to a successful career in meta-research, Wolfgang's hugely-influential software package 'metafor' is the default method for meta-analysis in R. Here Wolfgang answers some of our questions about his work and the importance of open science.



    / What is the Evidence Synthesis Hackathon?
    An interview with Neal Haddaway
    In the first of our blog series, Neal Haddaway, a Research Fellow from the Stockholm Environmental Institute, answers our questions about what exactly the Evidence Synthesis Hackathon is and how Evidence Synthesis Technology can support rigorous evidence-informed decision-making.