Springer Nature SciGraph

A Linked Open Data platform for the scholarly domain

Hack Day "Linked Open Data in Action"

Dear Linked Data Evangelists,
Pioneer with us and get ready to build cool things with other researchers, developers and the Springer Nature staff. 

What can you expect? 

Meet and collaborate with data lovers from around the globe, using our new 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 worth a lot. 

More information about SciGraph

Agenda

Friday, 23 June 2017

9 am
Reception with coffee
9.30 – 9.35 am
Welcome by Henning Schönenberger
9.35 – 9.50 am
SciGraph product vision & work so far by Markus Kaindl
9.50 – 10.20 am
“Getting you ready to hack” by SN SciGraph development team
10.20 – 11 am
Brainstorm ideas and use cases to work on - create working groups
11 am to 5 pm
6 hours hack sprint (food and drinks served throughout the event)
5 - 5.45 pm
Result presentation – including small prize ceremony
5.45 - 6 pm
Wrap up by Markus Kaindl
6 pm-open end
Social event: let’s grab a drink @ the Parcel Yard pub

Good to know

  • Lunch, drinks and a stable internet connection will be provided. 
  • Book some extra time on Friday evening after the official end of the event: We will definitely grab a beer in one of the nearby pubs.
  • Venue: Springer Nature campus, The Stables Auditorium, 2 Trematon Walk, London N1 9FN, UK (View in Google Maps)


Aims and Scope

  • 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

​​​​​​​Neuer Inhalt​​​​​​​Some suggestions of what to do with our Linked Open Data offering:

  • Data Visualization: Develop insightful dashboards on top of our data, e.g. visually appealing journal or institutional pages
  • Information Retrieval: Text data mine our abstracts and grants description texts to better understand what the content is really about by extracting contained facts
  • Linked Data Browsing: develop an intuitive and innovative approach to simply browse our linked data offering, making it easy and fun to explore -rather than to search- on top of linked data (see image on the right: Visual Graph | © Ontotext)
  • Predictive Analytics: train a model using SciGraph data, e.g. funding patterns, to be able to predict the future for an institute or a journal based on their past - the data is there!

Data provided:

Connect to the LOD cloud and take advantage of the full power of Linked Open Data: Pull in other useful data (like DBpedia, DBLP or GeoNames) to achieve your goals.

In this useful blog entry our lead architect Michele Pasin explains how to explore SciGraph data using JSON-LD, Elasticsearch and Kibana - definitely worth a read in preparation for the event!

About 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.