Google unveils search engine for open data

@article{Castelvecchi2018GoogleUS,
  title={Google unveils search engine for open data},
  author={Davide Castelvecchi},
  journal={Nature},
  year={2018},
  volume={561},
  pages={161-162}
}
The tool, called Google Dataset Search, should help researchers to find the data they need more easily.The new feature, called Google Dataset Search, locates open data repositories, and should help researchers to find the data they need more easily. 
Improved Ontology-Based Semantic Search for Open Data
TLDR
This thesis presented a prototype for ontology-based semantic search called DataOntoSearch, which matches the user’s query with concepts in an ontology, which are then matched with datasets based on either an automatic or a manual association between datasets and concepts.
Google dataset search and DOI for data in the ESA space science archives
TLDR
The on-going activities at the European Space Agency (ESA) to mint DOIs for datasets served across the space science archives are described, and how a subset of these DOIs are already discoverable by GDS.
SEforRA: A Bibliometrics-ready Academic Digital Library Search Engine Alternative
TLDR
SEforRA extracts and processes data from CrossRef, publishers, and other sources to provide an integrated platform for researchers to search and retrieve publication metadata, which is ready to use further in their research.
Talk of the Town: Discovering Open Public Data via Voice Assistants (Short Paper)
TLDR
This work envisioning using core concepts of spatial information to organize the geospatial themes of data exposed through voice assistant applications to curate them for improved discovery, ultimately supporting more meaningful user questions and their translation into spatial computations.
Editorial for the 8th Bibliometric-enhanced Information Retrieval Workshop at ECIR 2019
TLDR
This editorial presents the 8th iteration of the oneday BIR workshop held at ECIR 2019 in Cologne, Germany.
Report on the 8th International Workshop on Bibliometric-Enhanced Information Retrieval (BIR 2019)
The Bibliometric-enhanced Information Retrieval workshop series (BIR) at ECIR tackled issues related to academic search, at the crossroads between Information Retrieval and Bibliometrics. BIR is a
Boosting geoscience data sharing in China
  • Xin Li, Guodong Cheng, +9 authors Guofeng Zhao
  • Nature Geoscience
  • 2021
Enabling public sharing of scientific data in China not only needs top-down mandates but also incentive mechanisms that boost confidence and willingness to engage in data-sharing practices among
Bibliometric-Enhanced Information Retrieval: 3rd International BIR Workshop
TLDR
This paper introduces the BIR workshop series and discusses some selected papers presented at previous BIR workshops, and features original approaches to search, browse, and discover value-added knowledge from scientific documents and related information networks.
A Realistic Guide to Making Data Available Alongside Code to Improve Reproducibility
TLDR
Practical, actionable advice on how to actually share data alongside research is provided, and the key message is sharing data falls on a continuum, and entering it should come with minimal barriers.
Common-sense approaches to sharing tabular data alongside publication
TLDR
This paper argues that a lack of incentives and infrastructure for making data useful is the biggest barrier to creating a culture of widespread data sharing, and focuses on common-sense ideas for sharing tabular data for a target audience of academics working in data science adjacent fields who are about to submit for publication.
...
1
2
3
...