LEADING Application

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**Application deadline for 2021 is closed. **

**LEADING is a virtual fellowship program. Fellows located near their selected site may have more on-site interaction.**

LEADING Fellows will complete the following: 

  1. Online preparatory curriculum (Approximately 15 hours, May 2021)
  2. Intensive 4-day data science boot camp at Drexel University with other LEADING fellows, June 2021
    *Accommodations and COVID-19 adjustments possible
  3. Development of communication plan to connect with mentors on a regular basis
  4. Six-month virtual data science internship coordinated with one of our LEADING Mentors. See member node project descriptions below.
  5. Development of research output: in the form of papers, posters, and presentations

For inquiries about this unique educative program, please contact the Metadata Research Center (mrc.metadata@drexel.edu), or Jane Greenberg directly.

Fellowship Support

  • Fellowship stipend: up to $6,000 (~10-15 hours per week, July-December 2021; (work is virtual and asynchronous; you will have several ZOOM check-ins with your mentor/s and project faculty/PIs)
  • Barring any Covid-19 restrictions, additional financial support will be provided for conference travel during the 2021/2022 academic year to share project outcomes

Fellowship Requirements

  • Applicants should either be early-to-mid career library professionals, or doctoral students enrolled in iSchool or ALA-accredited LIS programs.
  • Applicants must complete the application form and upload the requested application materials
  • Applicants must rank their top three choices for their data science fellowship placement
  • IMLS support is restricted to persons currently based in the U.S. (including non-U.S. citizens)

Criteria for Selection

  • Clear interest in data science applications in the LIS domain
  • Relevant connection to the selected fellowship sites
  • Strong letter of support from advisor, mentor, or current/past supervisor

Commitment to Diversity, Equity, and Inclusivity (DE&I)

The LEADING program is committed to attracting and recruiting a diverse cohort of fellows. The LEADING team will strive to provide learning environments that are welcoming, inclusive, and equitable. The College demonstrates its commitment and support through the CCI Diversity, Equity & Inclusion Council with representation of current students (undergraduate and graduate), faculty and professional staff. The Council works to support CCI and University-led DE&I initiatives. 

Important Dates

  • LEADING Application Deadline: March 15th, 2021, 11:59pm EST
  • Notification of Acceptance: by April 23rd, 2021
  • May: Online pre-curriculum and bootcamp
  • June-December: Fellowship period

Application Materials Requested

  • One-page statement sharing your interest in the LEADING program and the selected fellowship site. Your one-page statement must address why you seek to learn about the intersection of library science and data science, and your career goals related to becoming an educator and researcher, or furthering your library career
  • Brief statement about your training and expertise with at least one of the following statistical packages: Excel, SPSS, R, MATLAB, or SAS (or other package)
  • Brief statement about your training and programming skill/experience with any of the following: HTML, XML, JSON, JavaScript, Python, R, Java, or Scala (The LEADING program anticipates applicants with a range of skills)
  • 1-2-page CV, resume, or biosketch (any format is acceptable; for NSF template, see link. Note: For early-to-mid career professionals who may or may not have publications to list, you can share volunteer and other related experience under products
  • For doctoral students: A letter of reference from your advisor or mentor
  • For early-to mid-career professionals: A letter of reference from a current or previous supervisor
  • Submit all materials through the application form link below

LEADS Fellowship Projects at Member Node Sites

Project SiteProject Title (Link to full project description)Project GoalsData
Academy of Natural Sciences (ANS)From Natural History Literature to Linked Open Data Biodiversity Knowledge GraphAutomate the identification and disambiguation of specimen descriptions in the historical full-text of the Proceedings of the Academy of Natural Sciences of PhiladelphiaSource: Link
Type: Plain text (OCR), GBIF datasets
AI-Collaboratory, University of Maryland iSchool (AIC–MD)Revisiting the WWII Japanese American Incarceration Camp Experience:
Spatial and Temporal Representations from the “Inside Out”
Analysis of Densho data records to identify people who were in camps, how they lived, and how they connected in order to resist and endure these circumstancesType: CSV, shapefile, graph database, text
Size: 50K files, less than 1TB
California Digital Library, University of California, Office of the President (CDL)Moving a Metadata Meritocracy into ProductionWork with the yamz.net database of terms and the yamz source code to refine workflows for gaining acceptance of proposed metadata terms in a stable production environmentSource: Link
Type: Postgres RDB, 10k rows
Digital Scholarship, Tish Library, Tufts University (DTTu)Data & Decision-Making for Consortial Ebook AcquisitionsAnalyze and visualize consortium-wide ebook usage data to examine use patterns across the individual institutionsType: Tabular title lists and usage reports
Kislak Center for Special Collections, Univ. of Pennsylvania Libraries (UPenn)Authority Creation and Exploitation in the Schoenberg Database of ManuscriptsIntegrate or link UPenn authority records for manuscript name and place metadata into VIAF or Wikidata knowledge bases. Visualize authority-related data for publication, and experiment with the datasetDocumentation: Link
Type: Structured metadata, MySQL Relational database
Loretta C. Duckworth Scholars Studio, Temple University Libraries (LCDSS)Enhancing and Visualizing Philadelphia Black Artist Records in WikidataDevelop SPARQL queries for Wikimedia records about black artists in Philadelphia to identify gaps and disparities in the records that can be enhanced with library catalogs, analyzed, and visualizedType: Wikidata database RDFs
Montana State University Library#ROIStats: Connecting Subscription Library Resources to the Research EnterpriseDevelop a workflow for extracting and visualizing specific data types from grant award data files to demonstrate how subscription library services are used to secure research dollarsSource: Link
Type: .xlsx, CSV, XML, JSON, PDF (OCR) files
Movement Alliance Project (MAP)People’s Media Record: Activist Media MetadataDevelopment of workflows for enhancement, analysis, or generation of quality descriptive metadata records for audio/video media files and associated production materialsSample: Link
Source: Link
Type: PBCore XML files
OCLC—Research and Development (OCLC-R): Project 1Metadata Record Similarity: Identification and Clustering
Use string similarity and match-scoring approaches to develop an algorithm and implementation that can identify match candidates or small fuzzy clusters for MARC recordsSample: Link
Type: MARC records
OCLC—Research and Development (OCLC-R): Project 2Detect Missing Marks (diacritics) in TextExamine instances of missing diacritic marks among title fields in WorldCat MARC records and analyze the associated bibliographic records to identify predictive patterns for this occurrenceSample: Link
Type: MARC records
Smithsonian Libraries (SL)Enhancing the museum data ecosystem through linking research publications to museum systemsExtract textual entities from Smithsonian publication PDF files and identify patterns among specimens, taxonomic names, localities, and other entities that can enable linking to museum systemsType: PDF research publications, Wikidata
UC San Diego Library: Project 1Transformation and enhancement of the Farmworker movement collection
Develop text analysis and data mining techniques for extracting quality metadata to augment digital objects in the Farmworker Movement Documentation Project collection
Source: Link
UC San Diego Library: Project 2Creating a Community of Expertise among FellowsAnalysis of existing data science collaborative groups to identify models to support a learning communityTBD
University of New Mexico (UNM) w/ Montana State University LibraryThe Scholarly Elite: Characterizing Uneven Distributions in Access to Institutional Repository (IR) ContentAnalyze a subset of aggregated institutional repository data to identify trends and disparities across access and useDocumentation: Link
Source: Link
Type: JSON, tabular data, 100+ GB
University of North Texas (UNT)Developing a Framework for Identifying Gaps in Large Newspaper CollectionsAnalyze the UNT digitized newspaper collection to identify collection underrepresentation of specific regions, time periods, languages, and ethnic groupsType: XML, CSV, tabular, MARC, JSON, markdown
University of Rochester (ROC)Using Data to make Impactful Collection DecisionsBibliographic and network analysis for ROC publications in Web of Science and Scopus to understand journal usage and impactType: CSV, .xlsx
**Partners for year 2 include Northeastern University Libraries and Charles Widger School of Law Library, Villanova University*Confirmed, additional partners for project year 2 include:
1) Northeastern University Libraries
2) Charles Widger School of Law Library, Villanova University.

Please reach out to mrc.metadata@drexel.edu if interested in  learning more about joining the LEADING network.