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From persistent identifiers to Digital Objects to Make Data Science More Efficient

Data Intelligence 2019年第1期1卷 6-21页

作者： Peter Wittenburg Max Planck Computing and Data Facility Gießenbachstraße 285748 GarchingGermany

Data-intensive science is reality in large scientific organizations such as the Max Planck Society,but due to the inefficiency of our data practices when it comes to integrating data from different sources,many projects cannot be carried out and many researchers are *** about 80%of the time in data-intensive projects is wasted according to surveys we need to conclude that we are not fit for the challenges that will come with the billions of smart devices producing continuous streams of data-our methods do not *** experts worldwide are looking for strategies and methods that have a potential for the *** first steps have been made since there is now a wide agreement from the Research Data Alliance to the FAIR principles that data should be associated with persistent identifiers(PID)and metadata(MD).In fact after 20 years of experience we can claim that there are trustworthy PID systems already in broad *** is argued,however,that assigning PIDs is just the first *** we agree to assign PIDs and also use the PID to store important relationships such as pointing to locations where the bit sequences or different metadata can be accessed,we are close to defining Digital Objects(DOs)which could indeed indicate a solution to solve some of the basic problems in data management and *** addition to standardizing the way we assign PIDs,metadata and other state information we could also define a Digital Object Access Protocol as a universal exchange protocol for DOs stored in repositories using different data models and data *** could also associate a type with each DO and a set of operations allowed working on its content which would facilitate the way to automatic processing which has been identified as the major step for scalability in data science and data industry.A globally connected group of experts is now working on establishing testbeds for a DO-based data infrastructure.

关键词： Big data Data management persistent identifiers Digital objects Data infrastructure Data intensive science

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维普期刊数据库

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Sustainable Connectivity in a Community Repository

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Data Intelligence 2024年第2期6卷 409-428页

作者： Ted Habermann Metadata Game Changers 452414th St.Unit 7H BoulderBoulderColorado 80304USA

persistent identifiers for research objects, researchers, organizations, and funders are the key to creating unambiguous and persistent connections across the global research infrastructure(GRI). Many repositories are implementing mechanisms to collect and integrate these identifiers into their submission and record curation processes. This bodes well for a well-connected future, but metadata for existing resources submitted in the past are missing these identifiers, thus missing the connections required for inclusion in the connected infrastructure. Re-curation of these metadata is required to make these connections. This paper introduces the global research infrastructure and demonstrates how repositories, and their user communities, can contribute to and benefit from connections to the global research infrastructure. The Dryad Data Repository has existed since 2008 and has successfully re-curated the repository metadata several times, adding identifiers for research organizations, funders, and researchers. Understanding and quantifying these successes depends on measuring repository and identifier connectivity. Metrics are described and applied to the entire repository here. identifiers(Digital Object identifiers, DOIs) for papers connected to datasets in Dryad have long been a critical part of the Dryad metadata creation and curation processes. Since 2019, the portion of datasets with connected papers has decreased from 100% to less than 40%. This decrease has significant ramifications for the re-curation efforts described above as connected papers have been an important source of metadata. In addition, missing connections to papers make understanding and re-using datasets more difficult. Connections between datasets and papers can be difficult to make because of time lags between submission and publication, lack of clear mechanisms for citing datasets and other research objects from papers, changing focus of researchers, and other obstacles. The Dryad community

关键词： Metadata curation Re-Curation Connectivity FAIR data persistent identifiers

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维普期刊数据库

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Open Science-A Question of Trust

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Data Intelligence 2021年第1期3卷 64-70页

作者： Jonathan Clark The DOI Foundation c/o EDItEURLondon N79DPUnited Kingdom

Collaboration and the sharing of knowledge is at the heart of Open Science(OS).However,we need to know that the knowledge we find and share is really what it purports to be;and we need to know that the authors we hope to collaborate with are really the people they claim to *** this paper,the author argues that a prerequisite for OS is trust and that persistent identifiers help to build that *** persistent identifier systems must themselves be trustworthy and they must be able to connect the user or their machine to the information they need now and into the *** is rather like plumbing:It goes unnoticed and unappreciated until it *** paper puts infrastructure for persistent identifiers in the spotlight as a core component of OS.

关键词： persistent identifiers Trust Open Science Metadata

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维普期刊数据库

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