SWAT4HCLS hackathon suggestions

Hackathon Chair: Andra Waagmeester
The SWAT4(HC)LS hackathon is a recurring hackathon. After an intense set of tutorial and 2 conference days, there is the time to relax and use the tranquility and informal space provided to play, experiment, create new collaborations, prepare a new project or simply work on your own work.

This document collect some idea's to use for inspiration. At the beginning of the hackathon there will be time allocated to pitch idea's after which the hacking starts. the final 30 minutes of the day will provide space to demonstrate of show of a developed app

Submit your pitch

New pitches are welcome, submit yours here

General

Bioschemas Markup and Support Tools

Driver
Alasdair Gray (A.J.G.Gray@hw.ac.uk)

Introduction
Bioschemas aims to make life sciences resources on the web more Findable.

Aim

• Generate markup for life sciences resources
• Enable validation of generated markup

Prerequisites
Markup: none, although an awareness of JSON-LD and schema.org is an advantage
Validation: ShEx and Javascript
Expected Results
Deployment of markup in web resources

WikiCite, Wikidata, and Scholia: Linking Publications to Topics

Driver
Egon Willighagen 0000-0001-7542-0286@orcid.org
Introduction
Keywords, MeSH terms are simple solutions to link topics to publications. However, our collective knowledge is not captured in single articles, they build on the effort explained in other articles. Citation networks are intrinsic to the provenance of our
knowledge. Wikidata, WikiCite, and Scholia provide a FAIR and Open
solution. Wikidata allows linking topics with articles about them.
WikiCite provides the citation graph, and Scholia visualizes it all.

Aim

• add BioSchemas annotation to Scholia pages
• Generate tools to automate linking articles with their 'main subjects'
• Develop SPARQL queries that find common topics in articles cited
  by some article
• Classify articles cited by some article, based on their 'main subjects'
• Develop SPARQL queries that find authors that specialize in some topic
• Write a new extension for Scholia for a type of topic (existing topics
  are proteins, genes, chemicals, etc)
• Write a Scholia extension that shows missing topic annotation of cited
  article
• Write code to generate main subject annotation coverage for the
  various Scholia topics (aspects)
• Develop a Scholia topic (aspect) for clinical trials

Agriculture

Schemas and Vocabularies for Agriculture and Plant Biology

Driver
Marco Brandizi (marco.brandizi@rothamsted.ac.uk)

Introduction
Schemas and Vocabularies are gaining momentum in the field of agriculture, plant research and food.

Aim
This hackathon activity aims at using simple and practical extensions of existing schemas/ontologies, like schema.org and bioschemas.org, to cover the typical entities used in the agriculture, plant biology and food field.

Prerequisites
Domain knowledge on agriculture, plant research and food.

Expected Results

• A collection of relevant entity types and their relations
• Ideas on how to leverage existing frameworks like schema.org and bioschemas
• Possibly some initial implementation examples.
• Deployment of a validation tool

Writing Shape Expressions for Lasagne

Drivers
Matthew Lange, Eric Prud'hommeaux, Tom Baker, Egon Willighagen, Andra Waagmeester

Introduction
Shape Expressions provide a powerful way to describe linked data sets. In this hackathon we will focus on food, specifically lasagna.

Aim
To create an initial collection of Shape Expressions to describe food phenotypes, the processes that produce and transform their ingredients, and the machines/people that engage in these processes.

Prerequisite:
Knowledge on food and agriculture data sets (recommended but not required). Having prepared, eaten or smelled lasagna.

Expected results:
Cooking up seed corpus of Shape Expressions by modeling lasagna. Providing some of the food linked data landscape, and serving as a nucleation site for further schema curation.

Healthcare

Metadata Interoperability - Mapping Metadata from Health Care, Clinical Research and EHR

Driver
Matthias Löbe (matthias.loebe@imise.uni-leipzig.de)

Time frame
Half day (12:30pm)

Introduction
Soon all university hospitals in Germany are required to provide access to their health data for research purposes. Making this happen brings major challenges for technical infrastructure, legal frameworks but certainly with respect to semantic interoperability.

Aim
The aim of the hackathon is to map exemplary data elements from clinical research and care data, into a common metamodel of ISO 21526 from TC 215.

Prerequisites

• Familiarity with ISO 11179-3 or ISO 21526 is required
• Knowledge on data modelling in health care
• Knowledge on common data modelling standards (CDA, CDISC, FHIR)

Expected results
To find and state weaknesses in the ISO 21526 draft and to develop best practices to translate mappings into a common metamodel.

Material
Google Drive Folder

Technical

Data2services, converting your data to a standard data model.

Driver
Vincent Emonet & Alexander Malic (Maastricht University)
Introduction
Today an increasingly amount of data is available on the Web, but this data usually comes in a myriad of formats (XML, CSV, RDB…) with no inherent semantic representation. Inspired by the FAIR data principles (Findable, Accessible, Interoperable, Reusable), we propose Data2services, a framework built with scalability in mind to convert any type of data to a standard data model that follows the Semantic Web standards.
This data is then accessible as RDF through a SPARQL endpoint. We are also working on automatically generating web services based on the data model for simplified access.

Aim

• Execute the data2services pipeline on your machine using Docker to convert your data to a generic RDF, where the data representation is based on the input data structure.
• Craft SPARQL queries to map the relevant data from the generated generic RDF to the target data model of your choice.
• Draft and start to develop web services that consume and expose the refined data model to simplify its access.

Prerequistes

• Docker already installed, or admin rights on your machine to install Docker
• Bring data you want to transform (relational database and/or XML-, CSV-, TSV-, PSV-files)
• Provide a target data model to convert your data to, or we can propose you one

Expected outcome

• Data2services running on your hardware using Docker
• Your data now complying to a standard data model, and accessible from a SPARQL endpoint and auto-generated API.
• A draft or a prototype of a web service that expose data2services RDF