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Quantitative Science Studies\n2022-01-24; doi: https://doi.org/10.1162/qss_a_00169", "type": { "id": "notes", "title": { "de": "Anmerkungen", "en": "Notes" } } } ], "creators": [ { "affiliations": [ { "name": "Athena Research Center" } ], "person_or_org": { "family_name": "Thanasis Vergoulis", "identifiers": [ { "identifier": "0000-0003-0555-4128", "scheme": "orcid" } ], "name": "Thanasis Vergoulis", "type": "personal" } }, { "affiliations": [ { "name": "Athena Research Center" } ], "person_or_org": { "family_name": "Ilias Kanellos", "identifiers": [ { "identifier": "0000-0003-2146-3795", "scheme": "orcid" } ], "name": "Ilias Kanellos", "type": "personal" } }, { "affiliations": [ { "name": "Athena Research Center" } ], "person_or_org": { "family_name": "Serafeim Chatzopoulos", "identifiers": [ { "identifier": "0000-0003-1714-5225", "scheme": "orcid" } ], "name": "Serafeim Chatzopoulos", "type": "personal" } }, { "affiliations": [ { "name": "Athena Research Center" } ], "person_or_org": { "family_name": "Danae Pla Karidi", "identifiers": [ { "identifier": "0000-0002-3154-6212", "scheme": "orcid" } ], "name": "Danae Pla Karidi", "type": "personal" } }, { "affiliations": [ { "name": "Athena Research Center" } ], "person_or_org": { "family_name": "Theodore Dalamagas", "identifiers": [ { "identifier": "0000-0002-5002-7901", "scheme": "orcid" } ], "name": "Theodore Dalamagas", "type": "personal" } } ], "description": "
This dataset contains impact metrics and indicators for a set of publications that are related to the COVID-19 infectious disease and the coronavirus that causes it. It is based on:
\n\nThese data have been cleaned and integrated with data from COVID-19-TweetIDs and from other sources (e.g., PMC). The result was dataset of 628,506 unique articles along with relevant metadata (e.g., the underlying citation network). We utilized this dataset to produce, for each article, the values of the following impact measures:
\n\nWe provide five CSV files, all containing the same information, however each having its entries ordered by a different impact measure. All CSV files are tab separated and have the same columns (PubMed_id, PMC_id, DOI, influence_score, popularity_alt_score, popularity score, influence_alt score, tweets count).
\n\nThe work is based on the following publications:
\n\n\n\n\n\n\t
\n- COVID-19 Open Research Dataset (CORD-19). 2020. Version 2023-01-10 Retrieved from https://pages.semanticscholar.org/coronavirus-research. Accessed 2023-01-10. doi:10.5281/zenodo.3715506
\n\t- Chen Q, Allot A, & Lu Z. (2020) Keep up with the latest coronavirus research, Nature 579:193 (version 2023-01-10)
\n\t- R. Motwani L. Page, S. Brin and T. Winograd. 1999. The PageRank Citation Ranking: Bringing Order to the Web. Technical Report. Stanford InfoLab.
\n\t- I. Kanellos, T. Vergoulis, D. Sacharidis, T. Dalamagas, Y. Vassiliou: Impact-Based Ranking of Scientific Publications: A Survey and Experimental Evaluation. TKDE 2019
\n\t- I. Kanellos, T. Vergoulis, D. Sacharidis, T. Dalamagas, Y. Vassiliou: Ranking Papers by their Short-Term Scientific Impact. CoRR abs/2006.00951 (2020)
\n\t- Rumi Ghosh, Tsung-Ting Kuo, Chun-Nan Hsu, Shou-De Lin, and Kristina Lerman. 2011. Time-Aware Ranking in Dynamic Citation Networks. In Data Mining Workshops (ICDMW). 373–380
\n
A Web user interface that uses these data to facilitate the COVID-19 literature exploration, can be found here. More details in our peer-reviewed publication here (also here there is an outdated preprint version).
\n
\nFunding: We acknowledge support of this work by the project "Moving from Big Data Management to Data Science" (MIS 5002437/3) which is implemented under the Action "Reinforcement of the Research and Innovation Infrastructure", funded by the Operational Programme "Competitiveness, Entrepreneurship and Innovation" (NSRF 2014-2020) and co-financed by Greece and the European Union (European Regional Development Fund).
Terms of use: These data are provided "as is", without any warranties of any kind. The data are provided under the Creative Commons Attribution 4.0 International license.
", "publication_date": "2023-01-23", "publisher": "Zenodo", "references": [ { "reference": "COVID-19 Open Research Dataset (CORD-19). 2020. Version 2023-01-10. Retrieved from https://pages.semanticscholar.org/coronavirus-research. Accessed 2023-01-10" }, { "reference": "I. Kanellos, T. Vergoulis, D. Sacharidis, T. Dalamagas, Y. Vassiliou: Impact-Based Ranking of Scientific Publications: A Survey and Experimental Evaluation. TKDE 2019" }, { "reference": "I. Kanellos, T. Vergoulis, D. Sacharidis, T. Dalamagas, Y. Vassiliou: Ranking Papers by their Short-Term Scientific Impact. CoRR abs/2006.00951 (2020)" }, { "reference": "Rumi Ghosh, Tsung-Ting Kuo, Chun-Nan Hsu, Shou-De Lin, and Kristina Lerman. 2011. Time-Aware Ranking in Dynamic Citation Networks. In Data Mining Workshops (ICDMW). 373\u2013380" }, { "reference": "R. Motwani L. Page, S. Brin and T. Winograd. 1999. The PageRank Citation Ranking: Bringing Order to the Web. Technical Report. Stanford InfoLab." }, { "reference": "Chen Q, Allot A, & Lu Z. (2020) Keep up with the latest coronavirus research, Nature 579:193 (version 2023-01-10)" } ], "related_identifiers": [ { "identifier": "https://pages.semanticscholar.org/coronavirus-research", "relation_type": { "id": "cites", "title": { "de": "Zitiert", "en": "Cites" } }, "resource_type": { "id": "dataset", "title": { "de": "Datensatz", "en": "Dataset" } }, "scheme": "url" }, { "identifier": "www.biorxiv.org/content/10.1101/2020.04.11.037093v2", "relation_type": { "id": "issupplementto", "title": { "de": "Erg\u00e4nzt", "en": "Is supplement to" } }, "resource_type": { "id": "publication-preprint", "title": { "de": "Preprint", "en": "Preprint" } }, "scheme": "handle" }, { "identifier": "https://github.com/diwis/PaperRanking", "relation_type": { "id": "cites", "title": { "de": "Zitiert", "en": "Cites" } }, "resource_type": { "id": "software", "title": { "de": "Software", "en": "Software" } }, "scheme": "url" } ], "resource_type": { "id": "dataset", "title": { "de": "Datensatz", "en": "Dataset" } }, "rights": [ { "description": { "en": "The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited." }, "icon": "cc-by-icon", "id": "cc-by-4.0", "props": { "scheme": "spdx", "url": "https://creativecommons.org/licenses/by/4.0/legalcode" }, "title": { "en": "Creative Commons Attribution 4.0 International" } } ], "subjects": [ { "subject": "COVID-19" }, { "subject": "coronavirus" }, { "subject": "scientometrics" }, { "subject": "bibliometrics" } ], "title": "BIP4COVID19: Impact metrics and indicators for coronavirus related publications", "version": "110" }, "parent": { "access": { "owned_by": { "user": 42037 } }, "communities": { "default": "10f33f78-3f29-41b6-bb10-f757a8f03cb8", "entries": [ { "access": { "member_policy": "open", "members_visibility": "public", "record_policy": "open", "review_policy": "open", "visibility": "public" }, "children": { "allow": false }, "created": "2020-03-16T11:40:44.487619+00:00", "custom_fields": {}, "deletion_status": { "is_deleted": false, "status": "P" }, "id": "10f33f78-3f29-41b6-bb10-f757a8f03cb8", "links": {}, "metadata": { "curation_policy": "The Coronavirus Disease Research Community - COVID-19 is curated by a selected team of experts nominated by OpenAIRE* (see list below). Each time a Zenodo user wants to add a record into the community, an email is sent to the curators that will decide whether to include the record or not.
\r\n\r\nOnly records that may be relevant to the Corona Virus Disease (COVID-19) or the SARS-CoV-2 should be included in this community. The Community curators are not able to edit records, therefore they may ask the corresponding authors to modify the record metadata when necessary, to provide the readers/users with more detailed information according to the FAIR principle of Open Science.
\r\n\r\nIf after its acceptance, a record is subsequently found not to be compliant, we reserve the right to remove it from the community.
\r\n\r\nThe curation team is reachable through the following email address for further clarification or information: covid19@openaire.eu.
\r\n\r\nCurator List:
\r\n\r\n* OpenAIRE: open access and open science training and support since 2009. OpenAIRE is the largest aggregator of European Commission funded research outputs and beyond, also delivering on-demand services for research communities.
\r\n", "page": "This community collects research outputs that may be relevant to the Coronavirus Disease (COVID-19) or the SARS-CoV-2. Scientists are encouraged to upload their outcome in this collection to facilitate sharing and discovery of information. Although Open Access articles and datasets are recommended, also closed and restricted access material are accepted. All types of research outputs can be included in this Community (Publication, Poster, Presentation, Dataset, Image, Video/Audio, Software, Lesson, Other).
\r\n\r\nThe recent Corona Virus Disease (COVID-19) outbreak is requiring unseen efforts of collaboration of the scientific community that need to act fast and to share results in an unpredictable manner. In order to facilitate the Scientist efforts, this community was created to collect all research results that could be relevant for the scientific community working on the Corona Virus Disease (COVID-19) and SARS-CoV-2.
\r\n\r\nAlthough Open Access articles and datasets are recommended, also closed and restricted access material are accepted. All types of research outputs can be included in this Community (Publication, Poster, Presentation, Dataset, Image, Video/Audio, Software, Lesson, Other).
\r\n\r\nWhen depositing a resource that is linked to other resources (not limited to the records deposited in Zenodo but also in other repositories), please make sure that your record is linked to all the other related elements already available, in order to adhere to the FAIR principles of Open Science to maximise the reusability of research results.
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