View points on data points: A shared vocabulary for cross-domain conversations on data and metadata

Sharing data across scientific domains is often impeded by differences in the language used to describe data and metadata. We argue that disagreements over the boundary between data and metadata are a common source of confusion. Information appearing as data in one domain may be considered metadat...
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Gespeichert in:

Autor*in:	George Alter [verfasserIn] Flavio Rizzolo [verfasserIn] Kathi Schleidt [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	metadata data sharing data interoperability

Übergeordnetes Werk:	In: IASSIST Quarterly - International Association for Social Science Information Service and Technology, 2022, 47(2023), 1
Übergeordnetes Werk:	volume:47 ; year:2023 ; number:1

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.29173/iq1051

Katalog-ID:	DOAJ094663173

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author	George Alter
spellingShingle	George Alter misc metadata misc data sharing misc data interoperability misc Social Sciences misc H View points on data points: A shared vocabulary for cross-domain conversations on data and metadata
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title	View points on data points: A shared vocabulary for cross-domain conversations on data and metadata
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title_full	View points on data points: A shared vocabulary for cross-domain conversations on data and metadata
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title_sort	view points on data points: a shared vocabulary for cross-domain conversations on data and metadata
title_auth	View points on data points: A shared vocabulary for cross-domain conversations on data and metadata
abstract	Sharing data across scientific domains is often impeded by differences in the language used to describe data and metadata. We argue that disagreements over the boundary between data and metadata are a common source of confusion. Information appearing as data in one domain may be considered metadata in another domain, a process that we call “semantic transposition.” To promote greater understanding, we develop new terminology for describing how data and metadata are structured, and we show how it can be applied to a variety of widely used data formats. Our approach builds upon previous work, such as the Observations and Measurements (ISO 19156) data model. We rely on tools from the Data Documentation Initiative’s Cross Domain Integration (DDI-CDI) to illustrate how the same data can be represented in different ways, and how information considered data in one format can become metadata in another format.
abstractGer	Sharing data across scientific domains is often impeded by differences in the language used to describe data and metadata. We argue that disagreements over the boundary between data and metadata are a common source of confusion. Information appearing as data in one domain may be considered metadata in another domain, a process that we call “semantic transposition.” To promote greater understanding, we develop new terminology for describing how data and metadata are structured, and we show how it can be applied to a variety of widely used data formats. Our approach builds upon previous work, such as the Observations and Measurements (ISO 19156) data model. We rely on tools from the Data Documentation Initiative’s Cross Domain Integration (DDI-CDI) to illustrate how the same data can be represented in different ways, and how information considered data in one format can become metadata in another format.
abstract_unstemmed	Sharing data across scientific domains is often impeded by differences in the language used to describe data and metadata. We argue that disagreements over the boundary between data and metadata are a common source of confusion. Information appearing as data in one domain may be considered metadata in another domain, a process that we call “semantic transposition.” To promote greater understanding, we develop new terminology for describing how data and metadata are structured, and we show how it can be applied to a variety of widely used data formats. Our approach builds upon previous work, such as the Observations and Measurements (ISO 19156) data model. We rely on tools from the Data Documentation Initiative’s Cross Domain Integration (DDI-CDI) to illustrate how the same data can be represented in different ways, and how information considered data in one format can become metadata in another format.
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title_short	View points on data points: A shared vocabulary for cross-domain conversations on data and metadata
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