The aim of the course is that researchers firstly become aware of the potential benefits of Linked Open data – using (science and innovation studies) field specific examples, secondly to provide knowledge and skills to formulate the relevant questions related to data integration, and thirdly to introduce methods and tools for data linking, and for exploring, analyzing and visualizing linked data, as embedded in the Semantically Mapping Science (SMS) platform.
This course, organized as a mixture of lectures, hands-on and discussion sessions, is about understanding Linked (Open) Data and how it can be used in science and innovation studies.
Over the last couple of years, many governmental institutions, research communities and individuals have figured out that data is better off being shared and integrated with other data rather than staying behind locked doors. This change of mindset triggered a movement to publish Linked Data on the Web, in different formats. This movement has still quite some momentum, and the amount of relevant open data increases fastly. Linked Data brings the promise of incorporating a new dimension to the Web where the availability of Web-scale data can determine a paradigmatic transformation of the Web and its applications. But it may also support social science researchers who may start to deploy these linked open data.
In this course we will first discuss the motivations behind publishing Linked (Open) Data compared to the traditional centralized data silos. Then, we will discuss the basic principles and building blocks of the Linked Data.
The second part of the tutorial will address the knowledge and tools required to generate, store, query, analyze, and visualize Linked Data. Throughout the lectures, we will provide hands-on sessions for people to practice and interact with Linked Data in the domain of science and innovation studies. We will demonstrate how the data available within RISIS can be linked to, and in that way enriched by, open data. Various services embedded in the Semantically Mapping Science (SMS) platform will be used for this.
To make the course as effective as possible, we ask you to prepare by watching some material, by reflecting on it and by preparing for the first session.
Location: main building of Vrije Universiteit Amsterdam, Room HG 9A.16
9:30 – 10:00 Coffee
10:00 – 10:30 Introduction
10:30 – 11:45 Linked Data Principles
What is Linked Data, why do we need it, what does it look like and how does it work?
Goal: by the end of this session you will understand the difference between URIs and URLs and can read Turtle files.
11:45 – 12:30 Linked Data Hands-on
Build your own Linked Data, explore it, and link it to the Web of Data.
Goal: By the end of this session you can write your own Turtle file, and use someone else’s URIs to build Linked Data.
12:30 – 13:30 Lunch
13:30 – 14:30 The Linked Data Lifecycle
What are the different phases in the lifecycle of Linked Data, what are the important considerations that need to be taken into account.
Goal: by the end of this session you will understand the Linked Data lifecycle, and can apply it to your own research project.
14:30 – 14:45 Coffee
14:45 – 16:00 Research Data Conversion Hands-on
Together with a fellow participant, select and (re)formulate a research question, decide on a plan for converting a relevant dataset to Linked Data, and perform the conversion.
Goal: by the end of this session you will know what to take into account when converting tabular data to RDF, and are able to use OpenRefine to convert a dataset to RDF.
16:00 – 17:00 Marketplace
This is where you showcase the end result of the conversion, and reflect on how you converted Linked Data. What are common pitfalls, what are best practices?
Reflection and preparation for day 2
17:00 – Drinks
To keep you busy over dinner, we ask you to prepare for the next day by watching some material, by reflecting on it and by doing some preparation.
Location: main building of Vrije Universiteit Amsterdam, Room HG 11A.22
9:00 – 9:15 Coffee
9:15 – 9:45 Introduction & Reflection
10:30 – 11:30 SPARQL Query Language
How can we query Linked Data, what is the syntax of SPARQL and how can I use it.
Goal: by the end of this session you will know the syntax of SPARQL and understand how you can query Linked Data on the Web.
11:30 – 11:45 Coffee
11:45 – 12:30 SPARQL Hands-on
Query external datasets, query your own Linked Data, use queries to link it to the Web of Data.
Goal: By the end of this session you can write your own SPARQL queries, you can explain how a query produces results, and use someone else’s SPARQL endpoint to answer questions.
12:30 – 13:30 Lunch
13:30 – 14:30 Linked Data Publishing
What are triple stores, and how do they work. How can we use a triple store to publish Linked Data on the web. How can we use mapping files to expose relational data on the web. How can we use (faceted) linked data browsers to explore our data.
Goal: by the end of this session you will understand how triple stores work, and can explain how Linked Data is published on the web.
14:30 – 14:45 Coffee
14:45 – 16:00 Data Publication Hands-on
Together with your fellow participant, revise your research research question, make final adjustments to your Linked Data, and publish the Linked Data on the web..
Goal: by the end of this session you can install a triple store, and publish your own Linked Data.
16:00 – 17:00 Actual Research
Now that we have datasets as Linked Data, can we formulate queries across our data that answer our research questions?
Goal: at the end of this session, you will give a short presentation of the design decisions of your data publication effort, and present “the” answer to your research question.
Researchers (graduate and undergraduate) interested in data integration in science and innovation studies, from within the RISIS consortium and from outside. Participants can either be active researchers in the field, or data/information/computer scientists working together with STI studies researchers
As this is an introductory course, no previous knowledge on Linked Open Data is required. Previous experience with programming and database technology will be helpful, but is not strictly required. Participants are expected to bring their own laptops for the hands-on sessions.
registration is closed now.