Databases in peril

Merali, Zeeya; Giles, Jim

doi:10.1038/4351010a

Cited by 55 publications

(32 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Much of this data is deposited into disciplinary repositories and data banks that are funded by the U.S. government (Baker, 2012;Merali & Giles, 2005). Unfortunately, the government has prioritized funding of new services over maintenance of existing services, which jeopardizes the future of disciplinary data repositories (Merali & Giles, 2005).…”

Section: Research Data At Riskmentioning

confidence: 99%

“…Data quality presents an opportunity to offer new rationales to University administration for additional funding. The long-term stewardship risks associated with governmentsupported disciplinary data repositories (Baker, 2012;Merali & Giles, 2005) may help make the case that centrally-funded data services protect the University's investments in new research, increasing return on investment by ensuring for its long-term stewardship. As research data is typically owned by the institution itself in the United States (Clinical Tools, Inc. 2006;Erickson & Muskavitch, 2009), and not individual researchers, it is in the best interest of the institution to take a proactive role in safeguarding the data.…”

Section: Our Challengementioning

confidence: 99%

See 1 more Smart Citation

Academic Libraries as Data Quality Hubs

Giarlo

2013

Journal of Librarianship and Scholarly Communication

View full text Add to dashboard Cite

Academic libraries have a critical role to play as data quality hubs on campus. There is an increased need to ensure data quality within ‘e-science’. Given academic libraries’ curation and preservation expertise, libraries are well suited to support the data quality process. Data quality measurements are discussed, including the fundamental elements of trust, authenticity, understandability, usability and integrity, and are applied to the Digital Curation Lifecycle model to demonstrate how these measures can be used to understand and evaluate data quality within the curatorial process. Opportunities for improvement and challenges are identified as areas that are fruitful for future research and exploration

show abstract

Section: Research Data At Riskmentioning

confidence: 99%

Section: Our Challengementioning

confidence: 99%

Academic Libraries as Data Quality Hubs

Giarlo

2013

Journal of Librarianship and Scholarly Communication

View full text Add to dashboard Cite

show abstract

“…As journals are steadily overtaken by databases as the preferred means for getting data into the public domain, BRIF, or something like it, will be needed to demonstrate researchers' productivity and the importance of their work. It will also help in making it evident to funding bodies that database creation efforts are worthy of support -a message that presently needs some re-enforcement 44 …”

Section: Future Challenges and Opportunitiesmentioning

confidence: 99%

Genotype–phenotype databases: challenges and solutions for the post-genomic era

2009

View full text Add to dashboard Cite

“…A recent study of 138 LSDBs found that 40 had not been updated since 2000, and another 44 that had not been updated between 2001[Soussi et al, 2006. Financial issues are a major factor in database maintenance and several such as the Asthma and Allergy gene database were closed due to lack of funding [Merali and Giles, 2005]. To handle the large number of mutations to be identified for this database, we have explored an automatic text processing method that identifies mutations in both abstracts and full-length articles within the literature database PubMed (www.ncbi.nlm.nih.gov/entrez/query.fcgi?db 5 pubmed).…”

Section: Introductionmentioning

confidence: 99%

CoagMDB: a database analysis of missense mutations within four conserved domains in five vitamin K-dependent coagulation serine proteases using a text-mining tool

Saunders

Perkins

2008

Hum. Mutat.

View full text Add to dashboard Cite

Communicated by John McVeyCentral repositories of mutations that combine structural, sequence, and phenotypic information in related proteins will facilitate the diagnosis and molecular understanding of diseases associated with them. Coagulation involves the sequential activation of serine proteases and regulators in order to yield stable blood clots while maintaining hemostasis. Five coagulation serine proteases-factor VII (F7), factor IX (F9), factor X (F10), protein C (PROC), and thrombin (F2)-exhibit high sequence similarities and all require vitamin K. All five of these were incorporated into an interactive database of mutations named CoagMDB (http://www.coagMDB.org; last accessed: 9 August 2007). The large number of mutations involved (especially for factor IX) and the increasing problem of out-of-date databases required the development of new database management tools. A text mining tool automatically scans full-length references to identify and extract mutations. High recall rates between 96 and 99% and precision rates of 87 to 93% were achieved. Text mining significantly reduces the time and expertise required to maintain the databases and offers a solution to the problem of locus-specific database management and upkeep. A total of 875 mutations were extracted from 1,279 literature sources. Of these, 116 correspond to Gla domains, 86 to the N-terminal EGF domain, 73 to the C-terminal EGF domain, and 477 to the serine protease domain. The combination of text mining and consensus domain structures enables mutations to be correlated with experimentally-measurable phenotypes based on either low protein levels (Type I) or reduced functional activities (Type II), respectively. A tendency for the conservation of phenotype with structural location was identified. Hum Mutat 29(3), [333][334][335][336][337][338][339][340][341][342][343][344] 2008.

show abstract

Databases in peril

Cited by 55 publications

References 3 publications

Academic Libraries as Data Quality Hubs

Academic Libraries as Data Quality Hubs

Genotype–phenotype databases: challenges and solutions for the post-genomic era

CoagMDB: a database analysis of missense mutations within four conserved domains in five vitamin K-dependent coagulation serine proteases using a text-mining tool

Contact Info

Product

Resources

About