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Press the refresh button: using research integrity and open science for researcher assessment
Introducing the Hong Kong Principles and the Transparency and Openness Promotion (TOP) guidance for academic institutions Please note this workshop is no longer accepting registrations. This workshop is an introduction to researcher assessment. A presentation examining the current metrics used to assess researchers will be followed by an introduction to the Hong Kong Principles (HKPs). The principles were developed as part of the 6th World Conference on Research Integrity (2019) with a specific focus on the need to drive research…
Find out more »Open Research Transparency workshop
New tools and practices to promote open and efficient science Please note this workshop is no longer accepting registrations. Currently, innovative ideas are abundant in science, yet we are still short of practical tools to implement these ideas in everyday practice. A tool is practical if it can achieve its aim without requiring too much or no extra effort from the user. The consideration of user experience, efficiency, and user-friendliness is still weak in the development of scientific tools. In this workshop,…
Find out more »IsoArcH: Open Science in Archaeology
Please note this workshop is no longer accepting registrations. This event provides archaeologists with an overview of the latest Open Science developments in the field. The event features presentations about open access to publications and databases, open review of papers, as well as open sharing of data/codes/methods. Talks will be given by Prof. Ben Marwick (Univ. of Washington), Prof. Trudy Turner (Univ. of Wisconsin-Milwaukee; American Journal of Physical Anthropology) and Prof. Connie Mulligan (Univ. of Florida; American Journal of Physical…
Find out more »Introduction to causal inference and directed acyclic graphs
Registration for this event is open Register Estimating causal effects in non-experimental data is a key aim of applied health and social science research. Unfortunately, it is also notoriously difficult. Contemporary causal inference methods, including directed acyclic graphs, promise to revolutionise the analysis and interpretation of non-experimental data, not least by making our ambitions and assumptions far more explicit. This interactive session offers a friendly and non-technical introduction to the theory, practice, and benefits of contemporary…
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