Data Intelligence, an MIT Press Direct open access journal, seeks contributions for a special issue on Metadata as Data Intelligence.
Read the full call for papers below.
Beta Phi Mu has announced the 2021 award winners for the Eugene Garfield Doctoral Dissertation Fellowship. Among the six recipients is Drexel CCI doctoral candidate Elizabeth Campbell, as well as three 2019 LEADS-4-NDP fellows: Jessica (Yi-Yun) Cheng, University of Illinois at Urbana-Champaign; Julaine Clunis, Kent State University; and Rongqian Ma, University of Pittsburgh. The Metadata Research Center wishes a hearty congratulations to all of the recipients!
The Metadata Research Center participated in NASKO 2021 (North American Society for Knowledge Organization) from July 9-11, 2021.
Congratulations to Sam Grabus for her appointment as ISKO-C/US Program Officer. Congratulations also to Brian Dobreski and Vanessa Schlais for their appointments as President and Treasurer.
Drexel’s MRC had a good showing at NASKO, with two papers: “Modeling Ephraim Chambers’ Knowledge Structure from a Naïve Standpoint,” by Scott McClellan, Mat Kelly, and Jane Greenberg [Slides]; and “A Framework for Facilitating the Development of Data sharing and Use Agreements,” by Micaela Greene, Sam Grabus, and Jane Greenberg [Slides]. The papers will be published open access in the Proceedings from North American Symposium on Knowledge Organization.
Additionally, a shout out to all of the past and present LEADS and LEADING participants who attended NASKO: former LEADS Fellows Jessica Cheng, Laura Ridenour, and Chris Holstrom, current LEADING fellow L.P. Coladangelo, and LEADS/LEADING Project Manager Sam Grabus.
On May 13th, CCI PhD student Joel Pepper presented at the Great Lakes Bio Conference 2021 with co-authors Dr. David Breen and Dr. Jane Greenberg.
Presentation Title: “Automated Metadata Generation for Biological Specimen Image Collections”
Presentation Slides: [LINK]
On Tuesday, March 9th, MRC doctoral student Sam Grabus presented about her dissertation research as invited guest speaker for the graduate chapter of the Rutgers University Library and Information Science Student Association.
Presentation title: “Historical Subject Representation: Identifying Temporal Concept Drift for Temporally-Aligned Access Points.”
View the full presentation on the Rutgers LISSA Youtube Channel: LINK
The Metadata Research Center is proud to present a lecture from Dr. Marcia Zeng (Professor in the School of Information at Kent State University) as part of the 2021 Distinguished Speaker Series and LOVE Data Week.
Presenter: Dr. Marcia Zeng, Kent State University
Time: 11am- 12pm EST
Location: Zoom
Zoom Registration: LINK
Title: Ensuring the FAIRness of Metadata in the Open Data Mainstream— Requirements and opportunities
Abstract:
The FAIR principles have been widely implemented in the open data environment during the past several years to ensure that published digital resources are Findable, Accessible, Interoperable, and Reusable (FAIR). The principles refer to three types of entities, including data (or any digital object), metadata (information about that digital object), and infrastructure. In this presentation, the focus will be on metadata. After an introduction of the FAIR principles and W3C’s DCAT (Data Catalog Vocabulary) ontology, the presentation will report the new efforts of the AGRIS (The International System for Agricultural Science and Technology), a global public service provided by the Food and Agriculture Organization (FAO) of the United Nations (UN). Using the U.S. Department of Agriculture (USDA) research data’s metadata in the pilot study, and enabled by the interoperability of the metadata structures, AGRIS effectively extended the metadata spectrum. Now, it not only continually covers bibliographic metadata of publications worldwide, but also includes research data resources. The presentation will share the research findings on ensuring the FAIRness of metadata in the Open Data and Open Science movement.
On Thursday, January 21st, Drexel Engineering Librarian Jay Bhatt presented at the virtual International Conference on Statistical Tools & Techniques and Research Data Analysis (ICSTTRDA 2021) at Central University of Gujarat, India. The presentation abstract and slide-deck are available below.
Citation:
Bhatt, Jay. (January 2021). Information Awareness of Research Data in Science and Engineering. Virtual International Conference on Statistical Tools and Techniques for Research Data Analysis (ICSTTRDA 2021), the School of Library and Information Science, Central University of Gujarat, Gandhinagar, India (ICSTTRDA 2021), Central University of Gujarat, India.
On Thursday, January 21st, CCI professors Jane Greenberg and David Breen, along with PhD student Joel Pepper, presented at the virtual International Conference on Statistical Tools & Techniques and Research Data Analysis (ICSTTRDA 2021) at Central University of Gujarat, India. The presentation abstract and slide-deck are available below.
Citation:
Breen, D., Pepper, J., & Greenberg, J. (2021, January 21-22). Approaches for Computing Specimen Image Research Data. International Conference on Statistical Tools & Techniques and Research Data Analysis (ICSTTRDA 2021), Central University of Gujarat, India. [Abstract]
On Friday, December 11th, doctoral student Christopher Rauch will present a paper for the Computational Archival Science workshop at the IEEE International Conference on Big Data (IEEE Big Data 2020). The paper, titled “A Computational Approach to Historical Ontologies,” is co-authored with CCI’s Mat Kelly, Jane Greenberg, Sam Grabus, and Joan Boone, as well as California Digital Library’s John Kunze, and Temple University’s Peter Logan.
Citation:
Kelly, M., Greenberg, J., Rauch, C. B., Grabus, S., & Boone, J. P. (In Press, December 10-13, 2020). A Computational Approach to Historical Ontologies 2020 IEEE International Conference on Big Data (IEEE BigData 2020), Atlanta, Georgia, US. [PDF]
On December 4th, 2020, doctoral candidate Jeremy Leipzig and Dr. Jane Greenberg were awarded the “Best Research Paper Award” at the 14th International Conference on Metadata and Semantics Research (MTSR 2020). The paper, titled “Biodiversity Image Quality Metadata Augments Convolutional Neural Network Classification of Fish Species,” was co-authored by J. Leipzig, Y. Bakis, X. Wang, M. Elhamod, K. Diamond, M. Maga, W. Dahdul, A. Karpatne, P. Mabee, H. L. Bart Jr. and J. Greenberg.
Research supported by NSF OAC Office of Advanced Cyberinfrastructure (OAC) #1940233and #1940322.
