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Digital Science to Support SciGraph Hack Day London: Linked Open Data in Action
Digital Science is sponsoring the Springer Nature SciGraph Hack Day “Linked Open Data in Action” in London on June 23rd 2017.
Get ready to build cool things with other researchers, developers and the Springer Nature staff. Meet and collaborate with data lovers from around the globe, using Springer Nature SciGraph Linked Open Data (LOD) set to develop interesting solutions to a variety of different challenges. Participation is free of charge, but the experience you gain will be priceless!
Some suggestions of what do to with Springer Nature LOD:
Image Credit: Springer Nature
- Data Visualization
- Information Retrieval
- Linked Data Browsing
- Predictive Analytics
The registration deadline is June 20th.
What can you expect from the Hack Day?
- Engage with the Linked Data Researcher Community
- Meet and connect with Springer Nature staff who also love hacking as much as you do
- Provide us with first-hand feedback from potential users of our data
- Explore Springer Nature’s SciGraph data sets and develop cool new tools in small groups
- Bring together developers from different countries and with different backgrounds
Date: Friday, June 23rd 2017 from 9 am – 6 pm
Venue: The Stables Auditorium, 2 Trematon Walk, London N1 9FN, UK
Lunch, drinks and a free wifi will be provided. Feel free to email your ideas for themes and challenges you think would work well at the event at scigraph@springernature.com.
What is Springer Nature SciGraph?
Springer Nature SciGraph collates information from across the research landscape, such as funders, research projects and grants, conferences, affiliations, and publications. Currently the knowledge graph contains 155 million facts (triples) about objects of interest to the scholarly domain. Additional data, such as citations, patents, clinical trials, and usage numbers will follow in stages, so that by the end of 2017 Springer Nature SciGraph will grow to more than one billion triples. The vast majority of these datasets will be freely accessible and provided in a way to enable experts to analyze downloaded datasets using their own machines, or via exploration tools on the Springer Nature SciGraph website which is being continuously enhanced.