# Translation and Clinical Implementation of a Test of Language and Short-term Memory (STM) in Aphasia: The CORE-APHASIA Collaboratory: Advancing Robust Data Science & Sharing (CARDS)

> **NIH NIH R01** · TEMPLE UNIV OF THE COMMONWEALTH · 2021 · $237,750

## Abstract

PROJECT SUMMARY
Aphasia is an impairment of language, affecting the production or comprehension of speech and the ability to
read or write resulting from damage to the left hemisphere from stroke, head trauma or other neurological
conditions. Aphasia affects any aspect of spoken and/or written language processing (e.g., comprehension, word
retrieval) and can range from mild to severe. Language impairments in aphasia often have profound adverse
effects on the individual's quality of life. Existing research efforts in aphasia have led to a wide range of measures,
interventions and resultant datasets that yield more precise diagnoses and finely targeted treatment plans. A
consequence of this much needed gain in diagnostic precision and treatment specificity has been a
preponderance of underpowered single case and case series studies with little consistency of measurements or
treatment content across groups, and multiple datasets that lack standardization and interoperability with limited
mechanisms for open access and long-term sustainability. Thus, there is a critical need, for a technological
infrastructure to support data standardization and aggregation, and collaboration amongst aphasia researchers.
We have developed CORE-APHASIA, a biomedical database, knowledge repository, and “collaboratory” using
an open-science platform with an award from the NIH Office of Data Science Strategy (ODSS). CORE-APHASIA
relies on cloud-based open science resource and is timely and complementary to the goals of the parent grant
that supports development of a clinical diagnostic tool for aphasia, the Temple Assessment of Language and
Short-term memory in Aphasia (TALSA). This proposed project is aligned with NIH's strategic plan for data
science, and aims to further advance the data ecosystem for aphasia researchers with a focus on ensuring FAIR-
ness (Findable, Accessible, Interoperable, and Reusable) and TRUST-worthiness (Transparency,
Responsibility, User Focus, Sustainability, and Technology) of CORE-APHASIA. For this proposed project, our
primary research objective is to incorporate the FAIR and TRUST principles and processes within our exiting
CORE-APHASIA biomedical data repository and “Collaboratory”. As part of this effort, we will assess and
increase the alignment of our CORE-APHASIA data resource to optimize it's impact on the aphasia research
community. Our specific aims are 1) achievement of desirable characteristics for data repositories including
standardized data vocabularies; 2) establish FAIR-ness of the CORE-TALSA data repository using the 3 prong
FAIR-ify standard approach and tools; and 3) establish TRUST-worthiness. Our final deliverable will be an
improved more mature data repository that has a system of metrics and processes in place to enhance data
sharing, access, and interoperability; increase usage, utility, sustainability and impact of the data resource, and
to improve the ability to capture, curate, validate, store, and analyze clinic...

## Key facts

- **NIH application ID:** 10407779
- **Project number:** 3R01DC016094-04S1
- **Recipient organization:** TEMPLE UNIV OF THE COMMONWEALTH
- **Principal Investigator:** Nadine Martin
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $237,750
- **Award type:** 3
- **Project period:** 2017-12-15 → 2022-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10407779

## Citation

> US National Institutes of Health, RePORTER application 10407779, Translation and Clinical Implementation of a Test of Language and Short-term Memory (STM) in Aphasia: The CORE-APHASIA Collaboratory: Advancing Robust Data Science & Sharing (CARDS) (3R01DC016094-04S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10407779. Licensed CC0.

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