<human> EXTRA wdt:P31 { wdt:P22 @<father> *; } <father> EXTRA wdt:P31 { wdt:P735 [<human>/P734/P31/PQ642] * ; # given name wdt:P734 [<human>/P734] * ; # family name } El ejemplo con ShEx de verdad sería:

Background hackmd-github-sync-badge In this report, we describe the activities that we have been carrying on during the Biohackathon 2023, held in Shodoshima, Japan. The main goal of the project has been to identify approaches and issues that can be used to integrate large RDF datasets by creating subsets described by Shape Expressions [@EricSemantics2014]. We have recently submitted a publication on creating subsets from Wikidata [@SeyedWikidataSubsetting23]. Wikidata is a knowledge graph which is constantly in flux and getting to a size which makes it hard to locally replicate. By creating topical subsets we are able to dissect a managable subset that can be loaded in local RDF stores for further processing. However, this subsetting app approach relies on Wikidata daily dumps, which are available in JSON format. For this hackathon we specifically choose to extend the subsetting mechanisms to work on RDF dumps or SPARQL endpoints.

Enhancement and Reusage of Biomedical Knowledge Graph Subsets Abstract Knowledge Graphs (KGs) such as Wikidata act as a hub of information from multiple domains and disciplines, and is crowdsourced by multiple stakeholders. The vast amount of available information makes it difficult for researchers to manage the entire KG, which is also continually being edited and changing its content. It is necessary to develop tools that extract snapshots and subsets for some specific domains of interest. These subsets help researchers by reducing costs and ease accessbility to data of interest. In the last two biohackathons, we have identified this issue and created prototypes to extract subsets easily applicable to Wikidata, as well as to define a map of the different approaches used to tackle this problem. Building on those outcomes, we aim to enhance subsetting in both definitions using Entity schemas based on Shape Expressions and extraction algorithms, with a special focus on the biomedical domain captured by entity schemas like the one defined in the GeneWiki project. Our first aim is to develop complex subsetting patterns to cover subsetting based on qualifiers and references for enhancing credibility of datasets. Our second aim is to establish a faster subsetting extraction platform applying new algorithms based on Apache Spark and new tools like a document-oriented DBMS platform. During this biohackathon, we aim to explore reuse workflows of Wikidata subsets specifically with respect to drug repurposing. The biohackathon will assist in an evaluation of existing nodes and edges on drug-target interactions categories within Wikidata, and if these are in need of updates as well as deeper annotation. We would also aim to deliver machine readable schemas of drug-target interactions in Wikidata for future data reuse. Report about project 11 at Biohackathon-Europe 2022 Links HackMD notes notes from 2021 (Barcelona)

Abstract Introduction (what is serverless, microservicios) introduction what is serverless and microservicios wether the initial state is a monolith maybe Background and motivations (advantages and adoption of serverless -> migrate legacy software trouble -> serverless) 3.1 Advantages and adoption of serverless (it does not fit for all use cases) 3.2 Migrate legacy software trouble 3.3 Cloud provider options, why AWS and consecuences of choose one or other...

Links The contents of this repo are created also on HackMD Github repo: https://github.com/kg-subsetting/biohackathon2021 Notes of 8th Nov 2021 TODOs List existing subsetting tools & methods Create Gene Wiki subset from the eLife paper

Attendees Labra Dani F Pablo Guillermo Jorge Discussions

--- title: 'Data validation and schema interoperability' tags: - schema - data validation - interoperability - FAIR authors: - name: Leyla Garcia orcid: 0000-0003-3986-0510 affiliation: 1 - name: Jerven Bolleman orcid: 0000-0002-7449-1266 affiliation: 2 - name: Michel Dumontier orcid: 0000-0003-4727-9435 affiliation: 3 - name: Simon Jupp orcid: 0000-0002-0643-3144 affiliation: 4 - name: Jose Emilio Labra Gayo orcid: 0000-0001-8907-5348