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Tracking down Datasets Using PubMed and PMC

PubMed and PubMed Central (PMC) now offer filters to limit a search to only those articles or citations that include related data links, supplemental material, data citations, or a data availability or data accessibility statement.

The filters, detailed below, can be combined with any search by simply adding the Boolean operator “AND” and the specific filter into the search box (see the screenshots below for example syntax; the filters are highlighted in yellow).

PubMed

data[filter] in PubMed search box

Use data[filter] to find citations with related data links in either the Secondary Source ID field or the LinkOut – more resources field (both located below the abstract).

Introducing the Pitt Data Catalog for Dataset Sharing and Discovery

Pitt Data Catalog, a project by the Health Sciences Library SystemSharing research data can bring many benefits, including greater visibility for data creators, a more transparent research process, and opportunities to identify potential collaborators. But what about datasets that are stored on a lab server instead of in a data repository, or that should only be shared with vetted researchers? The Pitt Data Catalog is a new platform at HSLS designed to help Pitt health sciences researchers share and discover their otherwise hard-to-find datasets, while keeping ultimate control over the data in researchers’ hands.

Expand Your Data Analysis Universe with Galaxy

Galaxy logoThe life sciences are erupting with data. Thanks to advancements in DNA sequencing technologies and the speed and capacity of computational algorithms, the generation of vast quantities of genomic and proteomic data is now commonplace and expected. However, analysis of this data is not keeping pace with its acquisition (storage space is yet another issue…). One limiting factor is that many biomedical scientists do not yet know how to access, much less use, the available analytical resources. This article describes a platform for multi-omic data analysis that is accessible, reproducible, and transparent, and recommends resources on how to use it.

NEW Data Class Offerings

In our continuous effort to support your research needs, HSLS is offering four new classes this spring covering: (1) introduction to mapping, (2) Python through Jupyter, (3) beginning command line for bioinformatics, and (4) options for bioinformatics analysis. Class descriptions and registration links are listed below.

(1) Data 101: Introduction to Mapping 

Thursday, February 15, 2018, 11 a.m. – 1 p.m.; Registration required

Mapping is a great way to visualize and analyze information—and to tell stories. In this introductory workshop, you’ll learn the principles of mapmaking, understand how computers are used to plot addresses on a map, conduct basic spatial analysis, and update records in a database based on location. Along with a deeper appreciation for computers, this class will provide you with a solid foundation of mapping concepts and processes, and get you prepared to take your first computer-based mapping class. No computers will be used in this class.

Updated PubMed Central Policy Statement on Supplementary Data

PubMed Central logoPubMed Central (PMC) was established in 2000 as the National Library of Medicine’s full-text, journal article repository. Since 2005, PMC has also been the designated repository for papers submitted in accordance with the NIH Public Access Policy. Today, PMC serves as the full-text repository for papers across a variety of scientific disciplines that fall under a number of funding agencies’ public access policies.

Open Data in Research Trending Up

“Open Data” is defined by SPARC (Scholarly Publishing and Academic Resources Coalition) as “research data that

  1. is freely available on the Internet;
  2. permits any user to download, copy, analyze, re-process, pass to software, or use for any other purpose; and
  3. is without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself.”

The phrase “open data” first appeared in a PubMed article title in 2000, but it took another 13 years for an increase in publications. As we approach 2018, how do researchers now view open data? And most importantly, how does HSLS support health sciences researchers at Pitt?

NCBI Hackathon @ Pitt

As previously reported, HSLS hosted a National Center for Biotechnology Information (NCBI) Hackathon from September 25-27, 2017, in collaboration with numerous campus partners. The event took place in the Digital Scholarship Commons of the University Library System (ULS). HSLS, the Center for Research Computing (CRC), and the Department of Biomedical Informatics (DBMI) generously provided support for breakfasts. Computing Services and Systems Development (CSSD), the School of Computing and Information (SCI), and the CRC provided expert technical support.

search.DataJournals: a Tool to Discover Data Published within Data Journals

Data journals are a means to share datasets and communicate detailed information about the methods and instrumentation used to acquire the data.

NCBI Hackathon @ University of Pittsburgh

HSLS is pleased to announce that the National Center for Biotechnology Information (NCBI) Hackathon is coming to the University of Pittsburgh on September 25-27, 2017! HSLS is working with numerous groups across campus to organize this event, including the Center for Research Computing (CRC), Computing Services and Systems Development (CSSD), School of Computing and Information (SCI), and University Library System (ULS).

Keeping Up-To-Date with Data in NCBI Databases

Final Rule for Reporting Trial Results to ClinicalTrials.gov Effective January 18

The Final Rule of the FDA Amendments Act of 2007 has updated registration and reporting requirements, effective January 18, 2017, with compliance mandated by April 18, 2017. The purpose of the final rule is to clarify the statutory language, expand the minimum reporting data set, and add critical details throughout the ClinicalTrials.gov record to improve effectiveness and compliance overall.

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