A reminder that this is starting in about an hour! We hope you can join us!
Best, Emily On Wed, Feb 8, 2023 at 2:27 PM Emily Lescak <eles...@wikimedia.org> wrote: > Hello everyone, > > The next Research Showcase will be livestreamed next Wednesday, February > 15 at 9:30AM PT / 17:30 UTC. The theme is The Free Knowledge Ecosystem. > > YouTube stream: https://www.youtube.com/watch?v=8VJmR-3lTac > > We welcome you to join the conversation on IRC at #wikimedia-research. You > can also watch our past research showcases: > https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase > > This month's presentations: > > The evolution of humanitarian mapping in OpenStreetMap (OSM) and how it > affects map completeness and inequalities in OSMBy *Benjamin Herfort, > Heidelberg Institute for Geoinformation Technology*Mapping efforts of > communities in OpenStreetMap (OSM) over the previous decade have created a > unique global geographic database, which is accessible to all with no > licensing costs. The collaborative maps of OSM have been used to support > humanitarian efforts around the world as well as to fill important data > gaps for implementing major development frameworks such as the Sustainable > Development Goals (SDGs). Besides the well-examined Global North - Global > South bias in OSM, the OSM data as of 2023 shows a much more spatially > diverse spread pattern than previously considered, which was shaped by > regional, socio-economic and demographic factors across several scales. > Humanitarian mapping efforts of the previous decade have already made OSM > more inclusive, contributing to diversify and expand the spatial footprint > of the areas mapped. However, methods to quantify and account for the > remaining biases in OSM’s coverage are needed so that researchers and > practitioners will be able to draw the right conclusions, e .g. about > progress towards the SDGs in cities. > > > Dataset reuseː Toward translating principles to practiceBy *Laura > Koesten, University of Vienna*The web provides access to millions of > datasets. These data can have additional impact when used beyond the > context for which they were originally created. But using a dataset beyond > the context in which it originated remains challenging. Simply making data > available does not mean it will be or can be easily used by others. At the > same time, we have little empirical insight into what makes a dataset > reusable and which of the existing guidelines and frameworks have an > impact.In this talk, I will discuss our research on what makes data > reusable in practice. This is informed by a synthesis of literature on the > topic, our studies on how people evaluate and make sense of data, and a > case study on datasets on GitHub. In the case study, we describe a corpus > of more than 1.4 million data files from over 65,000 repositories. Building > on reuse features from the literature, we use GitHub’s engagement metrics > as proxies for dataset reuse and devise an initial model, using deep neural > networks, to predict a dataset’s reusability. This demonstrates the > practical gap between principles and actionable insights that might allow > data publishers and tool designers to implement functionalities that > facilitate reuse. > We hope you can join us! > > Warm regards, > Emily > > > -- > Emily Lescak (she / her) > Senior Research Community Officer > The Wikimedia Foundation > _______________________________________________ Wiki-research-l mailing list -- wiki-research-l@lists.wikimedia.org To unsubscribe send an email to wiki-research-l-le...@lists.wikimedia.org