The equilibrium price for futures contracts. Also called the theoretical futures price, which equals the spot price continuously compounded at the cost of carry rate for some time interval. In the context of corporate goverance, Fair-Price

FAIR Data Principles in Brief • To be Findable: ๏ (meta)data are assigned a globally unique and persistent identiﬁer ๏ data are described with rich metadata ๏ metadata clearly and explicitly include the identiﬁer of the data it describes ๏ (meta)data are registered or indexed in a searchable resource

Responsible use of personal data. To meet concrete societal challenges such as human rights on the Internet, free flow of information, FAIR innebär att forskningsdata ska vara Findable (sökbara), Accessible (tillgängliga), Metadata är strukturerad och beskrivande information om data. För att ÖPPEN DATA I EUROPA OCH VÄRLDEN EOSC, som en infrastrukturutveckling där forskningsdata och metadata ska göras FAIR och maskinläsbara satte EU Aineistonhallinnan opas: Principer för Fair data rättvisa data under Den öppna forskningsprocessen och den goda hanteringen av data syftar Henrik Ekengren Oscarsson om kvantitativa data Principer och modeller. The FAIR Data Principles explained av DTL – Dutch Telecentre for Life Sciences. Välkommen att delta på en digitala frågestund om datahantering, FAIR data och öppen tillgång till forskningsdata med inriktning medicin och folkhälsa. Välkommen att delta på en digitala frågestund om datahantering, FAIR data och öppen tillgång till forskningsdata med inriktning språkforskning.

Fair data

Making practical FAIR data solutions. FAIR Data Collective has 6 repositories available. Follow their code on GitHub. A framework for establishing data collection criteria. Measurement scales for risk factors.

[Submitted on 10 Jun 2020]. Title:Fair Data Integration. Authors:Sainyam Galhotra, Karthikeyan Oct 10, 2018 This video illustrates how certified digital repositories contribute to making and keeping research data findable, accessible, interoperable and Aug 7, 2019 To achieve this, data should be findable, accessible, interoperable, and reusable (FAIR).

This output supersedes the FAIR Data Maturity Model: specification and guidelines DOI: 10.15497/rda00045 Context. Findability, Accessibility, Interoperability and Reusability – the FAIR principles – intend to define a minimal set of related but independent and separable guiding principles and practices that enable both machines and humans to find, access, interoperate and re-use data and

The principles have since received worldwide recognition as a useful framework for thinking about sharing data in a way that will enable maximum use and reuse. While the DSA focuses primarily on the responsibilities and conduct of data producers and repositories, FAIR focuses primarily on the data itself. The four collaborating international data organisations – CODATA, GO FAIR, RDA and WDS, collectively referred to as Data Together – commit to fostering cooperation among Open Science platforms and support CODATA’s Global Open Science Cloud (GOSC) and RDA’s Global Open Research Commons (GORC). Fair Data Society Mar 29, 2019 · 6 min read “Act in such a way that you always treat humanity, whether in your own person or in the person of any other, never simply as a means, but always at FAIR Data Principles bei FORCE11 Wilkinson et al.

What Fare's Fair? In London and New York, hailing a cab is putting a bigger dent in your wallet. Both cities face a similar problem—a shortage of drivers—and both have chosen the same solution: higher fares. Finding a black cab in London la

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FAIR research data shall be Findable, Accessible, Interoperable, and Reusable. There are a total of 15 FAIR principles that can be applied to research in all scientific disciplines. The FAIR principles are mainly focused on machine readability, but also target human understanding of research data, in order to enable the reuse of data. FAIR principles in practice. Data organised in accordance to the FAIR principles, so-called FAIR data, is structured, (re)usable, readable, interoperable between systems and possible to find as well as navigate within. The FAIR principles are structured around sub-categories, each containing guidelines regarding an aspect of FAIR. Data can be FAIR but not open.
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The ultimate goal of FAIR is to optimise the reuse of data. To achieve this, metadata and data should be well-described so that they can be replicated and/or combined in different settings. R1. (Meta)data are richly described with a plurality of accurate and relevant attributes. R1.1. (Meta)data are released with a clear and accessible data usage license DATA on The NET -- University of California, San Diego (Search or browse a listing of over 700 Internet sites of numeric social science statistical data, data catalogs, data libraries, social science gateways, addresses and more) DataPlace (maps and charts at geographic scales ranging from the neighborhood to the nation) The FAIR data principles were drafted by the Force11 group in 2015.

In the article we tell you what these two types of data are, what they look like and how they differ.
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The ultimate goal of FAIR is to optimise the reuse of data. To achieve this, metadata and data should be well-described so that they can be replicated and/or combined in different settings. R1. (Meta)data are richly described with a plurality of accurate and relevant attributes. R1.1. (Meta)data are released with a clear and accessible data usage license

öppen vetenskap utbildning | Research Data Management and Open Science Training in spring 2021. Det var en fair match sett till 90 minuter, säger han. Marcus Björling, pressansvarig i Djurgården, kommenterar Jeahzes ord om glåporden från Lendify är en digital bankutmanare som genom data och teknik vill effektivisera lånemarknaden Lendify is a bank challenger that is efficient, digital and fair.

Die "FAIR Data Principles" formulieren Grundsätze, die nachhaltig nachnutzbare Forschungsdaten erfüllen müssen und die Forschungsdateninfrastrukturen dementsprechend im Rahmen der von ihnen angebotenen Services implementieren sollten.

Open data may not be FAIR. For example, publically available data may lack sufficient documentation to meet the FAIR principles, such as licensing for clear reuse. In 2016, the ‘FAIR Guiding Principles for scientific data management and stewardship’ were published in Scientific Data.The authors intended to provide guidelines to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets.The principles emphasise machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data 2016-03-15 Open Data and FAIR Data are two very similar concepts, since they share a similar philosophy when it comes to sharing data and enhancing collaboration among users, but they are not exactly the same.

A FAIR Data Point (sometimes abbreviated to FDP) is the realisation of the vision of a group of authors of the original paper on FAIR on how (meta)data could be presented on the web using existing standards, and without the need of APIs. The FAIR principles, first published in 2016, contain guidelines for good data management practice that aim at making data FAIR: findable, accessible, interoperable, and reusable. "Data" refers in this context to all kinds of digital objects that are produced in research: research data in the strictest sense, code, software, presentations, etc. It will propose measures for increasing FAIR maturity to maximise data sharing and re-use. The EOSC-FAIR working group will define and implement a FAIR work plan. These will be based on the Action Plan proposed by the EC Expert Group on “Turning FAIR into reality”, as well as ongoing community initiatives and outputs from key projects like FAIRsFAIR , RDA and FREYA . A deep dive into FAIR data .