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Using a Workflow Management Platform in Textual Data Management

Data Intelligence 2022年第2期4卷 398-408页

作者： Triet Ho Anh Doan Sven Bingert Ramin Yahyapour Gesellschaft fur wissenschafliche Datenverarbeitung mbH Gottingen 37077 GottingenGermany

The paper gives a brief introduction about the workflow management platform,Flowable,and how it is used for textual-data *** is relatively new with its first release on 13 October,*** the short time on the market,it seems to be quickly well-noticed with 4.6 thousand stars on GitHub at the *** focus of our project is to build a platform for text analysis on a large scale by including many different text ***,we have successfully connected to four different text resources and obtained more than one million *** resources are dynamic,which means that they might add more data or modify their current ***,it is necessary to keep data,both the metadata and the raw data,from our side up to date with the *** addition,to comply with FAIR principles,each work is assigned a persistent identifier(PID)and indexed for searching *** the last step,we perform some standard analyses on the data to enhance our search engine and to generate a knowledge ***-users can utilize our platform to search on our data or get access to the knowledge ***,they can submit their code for their analyses to the *** code will be executed on a High-Performance Cluster(HPC)and users can receive the results later *** this case,Flowable can take advantage of PIDs for digital objects identification and management to facilitate the communication with the HPC *** one may already notice,the whole process can be expressed as a workflow.A workflow,including error handling and notification,has been created and *** execution can be triggered manually or after predefined time *** to our evaluation,the Flowable platform proves to be powerful and *** usage of the platform is already planned or implemented for many of our projects.

关键词： Flowable workflow text analysis knowledge graph persistent identifier

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维普期刊数据库

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Improving Domain Repository Connectivity

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Data Intelligence 2023年第1期5卷 6-26页

作者： Ted Habermann Metadata Game Changers

Domain repositories,*** that store,manage,and persist data pertaining to a specific scientific domain,are common and growing in the research *** of these repositories develop close,long-term communities made up of individuals and organizations that collect,analyze,and publish results based on the data in the *** between these datasets,papers,people,and organizations are an important part of the knowledge infrastructure surrounding the *** these research objects,people,and organizations can now be identified using various unique and persistent identifiers(PIDs)and it is possible for domain repositories to build on their existing communities to facilitate and accelerate the identifier adoption *** community members contribute to multiple datasets and articles,identifiers for them,once found,can be used multiple *** explore this idea by defining a connectivity metric and applying it to datasets collected and papers published by members of the UNAVCO *** identifiers in DataCite and Crossref metadata and spreading those identifiers through the UNAVCO DataCite metadata can increase connectivity from less than 10%to close to 50%for people and organizations.

关键词： persistent identifier Domain Repository ORCID ROR Connectivity PID Graph

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维普期刊数据库

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