Zobrazeno 1 - 10
of 1 315
pro vyhledávání: '"Data discovery"'
Autor:
Ambery Leahey, Grant Gibson, Julie Shi, Kelly Stathis, Kevin B. Read, Lynn Peterson, Sarah Rutley, Victoria Smith
Publikováno v:
Journal of eScience Librarianship, Vol 13, Iss 2 (2024)
Background: While open datasets are adopting FAIR principles to improve their discovery and use, restricted data—those only accessible via request or application—have fallen behind. Metadata is not an inherent characteristic of restricted data, w
Externí odkaz:
https://doaj.org/article/5a6377d7f1d749fb99f87df1ce9c9b6d
Autor:
Kevin B. Read, Grant Gibson, Amber Leahey, Lynn Peterson, Sarah Rutley, Julie Shi, Victoria Smith, Kelly Stathis
Publikováno v:
FACETS, Vol 9, Iss , Pp 1-9 (2024)
Data that are restricted are historically challenging for researchers to find and even more difficult to access. While efforts to support open data have expanded in Canada, the same cannot be said for restricted data. To better understand the landsca
Externí odkaz:
https://doaj.org/article/e68cc73a4f854346b3f4d7fb704f0735
Publikováno v:
IEEE Access, Vol 12, Pp 32164-32180 (2024)
Privacy is a fundamental human right according to the Universal Declaration of Human Rights of the United Nations. Adoption of the General Data Protection Regulation (GDPR) in European Union in 2018 was turning point in management of personal data, s
Externí odkaz:
https://doaj.org/article/03294ce517584d6fba1d52c433320233
Autor:
Luke Marsden, Olaf Schneider
Publikováno v:
Data Science Journal, Vol 23, Pp 38-38 (2024)
The scientific community is growing increasingly aware of the importance of the FAIR data management principles for publishing scientific data. For data providers, this includes creating machine-understandable file structures such as CF-NetCDF files
Externí odkaz:
https://doaj.org/article/094eb0f5e60a4d4291b34b71c9d8e4d6
Publikováno v:
Journal of Documentation, 2023, Vol. 79, Issue 5, pp. 1236-1264.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JD-06-2022-0129
Autor:
Björn Backeberg, Zdeněk Šustr, Enol Fernández, Gennadii Donchyts, Arjen Haag, J. B. Raymond Oonk, Gerben Venekamp, Benjamin Schumacher, Stefan Reimond, Charis Chatzikyriakou
Publikováno v:
Big Earth Data, Vol 7, Iss 3, Pp 812-830 (2023)
ABSTRACTAn adequate compute and storage infrastructure supporting the full exploitation of Copernicus and Earth Observation datasets is currently not available in Europe. This paper presents the cross-disciplinary open-source technologies being lever
Externí odkaz:
https://doaj.org/article/2b30cb4115f44e7e948b8099b6e9ba34
Autor:
Elia Ferrari, Friedrich Striewski, Fiona Tiefenbacher, Pia Bereuter, David Oesch, Pasquale Di Donato
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 13, Iss 4, p 128 (2024)
The improvement of search engines for geospatial data on the World Wide Web has been a subject of research, particularly concerning the challenges in discovering and utilizing geospatial web services. Despite the establishment of standards by the Ope
Externí odkaz:
https://doaj.org/article/d9f6d8ac7a7a40cb8643bff67353fe3c
Autor:
Vinh V. Vu, Mi T. H. Lam, Thuy T. M. Duong, Ly T. Manh, Thuy T. T. Nguyen, Le V. Nguyen, Unil Yun, Vaclav Snasel, Bay Vo
Publikováno v:
IEEE Access, Vol 11, Pp 104789-104805 (2023)
High-utility itemset mining (HUIM) is an important task in the field of knowledge data discovery. The large search space and huge number of HUIs are the consequences of applying HUIM algorithms with an inappropriate user-defined minimum utility thres
Externí odkaz:
https://doaj.org/article/f347f1ea7fa945cfa3f63c337ded437c
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 4529-4548 (2023)
With the booming of high-resolution Earth observation and open-data efforts, petabyte-scale Earth observation data have been available for free access. Due to the unprecedented availability of big data deluge, regional to global spatio-temporal analy
Externí odkaz:
https://doaj.org/article/464bbd6796f24980b3f504ea4690616d
Publikováno v:
Data Science Journal, Vol 23, Pp 2-2 (2024)
The National Science Foundation’s Arctic Data Center is the primary data repository for NSF-funded research conducted in the Arctic. There are major challenges in discovering and interpreting resources in a repository containing data as heterogeneo
Externí odkaz:
https://doaj.org/article/c80aed5e23544a3492f73c40668b598d