Re: COVID19 RDF Dataset

Dear all,
I am delighted to see that we have academic literature covered.
I am working on a paper titled "A Smart City Framework for Disease Control utilizing Sensor, Tracing, Tracking, Wearable and Medical Technologies" with acase study on Travel and Tourism.
If you look at pandemic control as a specific case of disease control in a smart city setting, you will recognize that we are looking at "a set of systems of complex adaptive systems".
See:Thurner, Hanel, and Klimek write the book on complex systems

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Thurner, Hanel, and Klimek write the book on complex systems

Welcome to Santa Fe Institute.
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Their book synthesizes hundreds of disparate findings in complexity and articulates a single, underlying characteristic of complex systems: They work like co-evolving algorithms.In other words, the kaleidoscope of complex systems — ant colonies, economies, social networks, spin glasses —  are best described by the rules that govern their interactions, rather than just the properties of the individual components. 
To give an example anonymized patient data at points of care or points of testing, detailing demographics, underlying conditions, sensor provided data on environmental parameters of dispersion and survival rates, combined with the genomics of the virus all provide information on the functioning of the virus both in propagation, infection and replication and are useful for in vitro or computational development of antiviral, or secondary medication (for mitigation of symptoms for patients with underlying  diseases-comorbidity) and vaccines.

A myriad of systems of complex adaptive systems can be identified for a smart city framework focusing on travel and hospitality.
By using three key generalized processes, Prevention, Mitigation and Creation of viral loss-of-function, we can simplify a model for disease control, and allow the use of among others knowledge graphs, technologies consuming and processing linked data, and interfacing, while using AI and concepts from category theory to structure general system interactions.

Milton Ponson
GSM: +297 747 8280
PO Box 1154, Oranjestad
Aruba, Dutch Caribbean
Project Paradigm: Bringing the ICT tools for sustainable development to all stakeholders worldwide through collaborative research on applied mathematics, advanced modeling, software and standards development 

    On Wednesday, May 13, 2020, 5:41:59 AM ADT, Mohamed Sherif <mohamed.sherif@uni-paderborn.de> wrote:  
 
 
Dear all,


We (The DICE research group team) are  happy to introduce our novel RDF dataset COVID19-DS. Our RDF dataset is based on papers related to the COVID-19 and coronavirus-related research (CORD-19). In the current version of COVID19-DS we provide resources’ dereferencing via LodView  in addition to dump files download and SPARQL endpoint. We also preserve the provenance information about the source of each paper in our dataset. Moreover, we provide linking to other datasets (currently 1 dataset, more to come soon).

   
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SPARQL endpoint: https://covid-19ds.data.dice-research.org/sparql

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Example resource: https://covid-19ds.data.dice-research.org/lodview/resource/00acd3fd31ed0cde8df286697caefc5298e54df1

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GitHub: https://github.com/dice-group/COVID19DS

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Download: https://hobbitdata.informatik.uni-leipzig.de/COVID19DS


Stay tuned for future versions of the dataset.

Kind regards,


The COVID19-DS Development Team







PS: Example resource:

covid:PMC1616946 a swc:Paper,

        bibo:AcademicArticle,

        fabio:ResearchPaper,

        schema:ScholarlyArticle ;

    bibtex:hasAuthor covid:ChristineAnderson,

        covid:ClarkHenderson,

        covid:MichaelHoward ;

    prov:hadPrimarySource covid:nonCommercialUseDataset ;

    covid:hasBody covid:PMC1616946_Body ;

    covid:hasDiscussion covid:PMC1616946_Discussion ;

    covid:hasIntroduction covid:PMC1616946_Introduction .


covid:PMC1616946_Introduction covid:hasSection      covid:PMC1616946_Section1,

        covid:PMC1616946_Section2,

        covid:PMC1616946_Section3,

        covid:PMC1616946_Section4,

        covid:PMC1616946_Section5,

        covid:PMC1616946_Section6 .


covid:PMC1616946_Section1 a sdo:Section ;

    nif:isString "The standard triplet readout of the genetic code can be reprogrammed by signals in the mRNA to induce ribosomal frameshifting [reviewed in (1–3)]. Generally, the resulting trans-frame protein product is functional and may in some cases be expressed in equal amounts to the product of standard translation. This elaboration of the genetic code (4,5) demonstrates versatility in decoding." ;

    bibtex:hasTitle "INTRODUCTION" .


covid:PMC1616946_Section1_B1_1 a nif:Phrase ;

    nif:anchorOf "1" ;

    nif:beginIndex "140"^^xsd:nonNegativeInteger ;

    nif:endIndex "141"^^xsd:nonNegativeInteger ;

    nif:referenceContext covid:PMC1616946_Section1 ;

    its:taIdentRef covid:PMC1616946_B1_1 .


covid:PMC1616946_B1_1 a bibtex:Entry ;

    bibtex:Inbook "159-183" ;

    bibtex:hasAuthor covid:DMDunn,

        covid:JFAtkins,

        covid:RBWeiss,

        covid:RFGesteland ;

    bibtex:hasTitle "Ribosomal frameshifting from −2 to +50 nucleotides" ;

    bibtex:hasVolume "39" ;

    bibtex:hasYear 1990 ;

    schema:EventVenue "Prog. Nucleic Acid Res. Mol. Biol." .


covid:PMC1616946_Figure1A_1 a sdo:Figure ;

    bibtex:hasTitle "Figure 1: (A) Reporter construct design: cis- and trans-acting stimulators of frameshifting. Sequence of the shift site and downstream sequences for dual luciferase constructs containing cis-acting structures used in this paper. P2luc-AZ1wt contains the wild-type antizyme frameshift cassette, p2luc-AZ1-0sp has a 3 bp deletion of the spacer sequences separating the shift site from the pseudoknot and p2luc-AZ1hp contains a hairpin replacement of the pseudoknot structure. S1 and S2 refer to stem 1 and stem 2 of the RNA pseudoknot. L1 and L2 refer to loops 1 and 2 of the pseudoknot. Fluc and Rluc represent Firefly and Renilla luciferase genes, respectively. (B) Sequence of the shift site and downstream sequences for dual luciferase constructs and their complementary antisense oligonucleotide partners. Fluc and Rluc represent Firefly and Renilla luciferase genes, respectively." .


covid:nonCommercialUseDataset a prov:Entity ;

    prov:wasDerivedFrom 

<https://ai2-semanticscholar-cord-19.s3-us-west-2.amazonaws.com/2020-03-20/noncomm_use_subset.tar.gz> .

-- 
Dr. rer. nat. Mohamed Ahmed Sherif   
Data Science group
Department of Computer Science
University of Paderborn

Room TP6.3.306,
Technologiepark 6, 33100 Paderborn


Tel: +49 (0) 5251 60-1708

DICE Data Science Group https://dice-research.org
http://aksw.org/MohamedSherif