 I'm going to introduce the concept of open synthesis and how it relates to maximizing efficiency, rigor, transparency, impact, and legacy of evidence synthesis and metronalsies. I wanted to start off just by talking about open science, it's obviously very important to the topic. There have been a number of different taxonomies and definitions set out to explain the key elements of open science, but in principle they all relate to the idea that it should be making science as accessible to the public as possible. There are various different advantages and disadvantages that have been reported in relation to open science. Some of the advantages include things like more rigorous pay review, the fact that publicly funded research is publicly available which perhaps is a mandate, the increased level of reproducibility and transparency of research and related to that a greater impact in open science research and that open collaborations can support high complexity analysis. Some of the disadvantages relate to the fear of possible misuse of data and research, the risk that the public may misunderstand that research, there could be an exacerbation in the volume of poor quality research and any existing power imbalances may be made worse by the push towards open science. Before I move on to evidence synthesis, I wanted to think about closed evidence synthesis. Perhaps in many ways the status quo of evidence synthesis, if not now then recently. Some of the common issues with closed evidence synthesis are that they could suffer from selective or incomplete reporting and that's where the data or results that we're seeing may not be representative of the full analysis conducted. It could be that there's a lack of methodological detail making it difficult to verify or replicate the methods used. Some research is pay walled and can't be accessed. The research that has analyses involving code may not provide that code in a format that's reproducible. Where data is provided it may be unclear or unusable. There may be a waste in resources caused by closed synthesis, particularly where there's a lack of collaboration or networking. Where people aren't honest about their potential interests in a topic and those conflicts of interests could be a problem, it's difficult to verify whether we can have trust in the analyses that have been done. Closed evidence synthesis may also mislead decision makers if they're not reliable. Where a review is attempted to be updated it's very difficult to do so if the original review is closed and everything has to be done from scratch. The open synthesis working group is a group of people interested in the application of open science to evidence synthesis and over the last 12 months or so they've been discussing a draft framework for open synthesis and I wanted to share this, what is a draft framework for the key elements of how open science might relate to evidence synthesis. First of all there's a concept of open collaboration and that's non-selective opportunities for collaboration in evidence synthesis and meta-analyses. Open discovery, which is the use of bibliographic databases that are free to use and free to export data from. Open methods which relates to detailed methodology which is freely accessible describing the planned or eventual methods involved in a synthesis or a review. Open data which we're probably all familiar with which is freely accessible data. Open source which relates to freely accessible software code for any programs that are developed within a review. Open code which relates to freely accessible analytic code within a synthesis or meta-analysis. Open access which again we're probably all familiar with and relates to freely accessible manuscripts and full texts. Open peer review which relates to freely accessible peer review reports. Open education which relates to freely accessible training materials and open interests relating to the open declaration of financial and non-financial interests for all review authors. And the open synthesis working group will discuss what each of these might mean, whether they're all integral parts of open synthesis and any potential disadvantages or things that need to be looked out for when trying to provide practical advice on being more open in evidence synthesis and meta-analyses. Open synthesis is important for a number of reasons. Firstly evidence synthesis itself relies on the openness of the primary research that we are synthesizing. So we're often having to deal with hurdles around the openness of primary research and as a result we should be more aware and more open to being open ourselves. In addition evidence synthesis is already built on many open science principles. So for example we already use open methods in systematic reviews where an a priori protocol is published in advance that outlines the methodology we plan to use. There are also reporting standards that help to ensure that the methods we're reporting are highly detailed and reproducible and as reproducible as possible like Prisma and Roses. The linkages between open science and evidence synthesis so far haven't been explicit and that means that the potential benefits of open science haven't been fully appreciated in evidence synthesis. We've also seen already as we've seen in this presentation evidence synthesis are often insufficiently open and so the concept of open synthesis aims to explicitly define how openness should be applied in evidence synthesis and what the potential benefits might be. And those benefits are that it helps to facilitate full transparency and in particular digital transparency. It helps to verify the results and conclusions of reviews and therefore increase the level of reliability that we might have and the trust that we might have in synthesis and metralizes. It can also help to increase and improve the access to resources in lower middle income countries or participation by low and middle income countries because of removing that financial barrier. It can also help to facilitate data reuse for example where we want to understand the methods used across the topic area. Some people call this meta research and it can help to increase the efficiency of review conduct by sharing work across people. It can also reduce the need for requests for information from corresponding authors many of which we've experienced which are often not particularly successful or may have a low efficiency or a big time lag. And it can help to raise awareness of and capacity building for the conduct of rigorous evidence synthesis and finally increase the impact of evidence synthesis by ensuring that the evidence synthesis are more reliable, they're more rigorous and they're easier to find and use and integrate into further research.