Research Data Declines Rapidly with Article age
|
By HospiMedica International staff writers Posted on 30 Dec 2013 |
A new study reveals that the vast majority of raw data from old studies is missing, making the reproducibility of results, a cornerstone of science, unavailable.
Researchers at the University of British Columbia (Vancouver, Canada), Université Laval (Canada), and other institutions requested data sets from the authors of a relatively homogenous set of 516 articles published between 2 and 22 years ago, finding that the availability of the data was strongly affected by article age. For papers where the authors gave the status of their data, the odds of a data set being extant fell by 17% per year. As a result, more 90% of the oldest data were inaccessible, and even in papers published as recently as 2011, they were only able to track down the data for 23% of the studies.
In addition, the odds that the researchers could even locate a working e-mail address for the first, last, or corresponding author fell by 7% per year. Defunct addresses were listed on the paper itself, with web searches not turning up any current ones. For another 38% of studies, the researcher’s queries led to no response. And even when they received a reply, access to another7% of the data sets was inaccessible, or the data itself was lost. The study was published on December 19, 2013, in Current Biology.
“Everybody kind of knows that if you ask a researcher for data from old studies, they’ll hem and haw, because they don’t know where it is,” said lead author zoologist Timothy Vines, PhD, of the University of British Columbia. “Some of the time, for instance, it was saved on three-and-a-half inch floppy disks, so no one could access it, because they no longer had the proper drives.”
“Because the basic idea of keeping data is so that it can be used by others in future research, this sort of obsolescence essentially renders the data useless,” added Dr. Vines. “Our results reinforce the notion that, in the long term, research data cannot be reliably preserved by individual researchers, and further demonstrate the urgent need for policies mandating data sharing via public archives.”
Preserving raw data is important because it is impossible to predict in which directions research will move in the future. Dr. Vines, for instance, has been conducting research on a pair of toad species native to Eastern Europe that seem to be in the process of hybridizing. In the 1980s, a separate team of researchers was working on the same topic, and came across an old paper written in Polish that documented the distribution of the toads in the 1930s. Knowing that their distribution had changed relatively little over the intervening decades allowed the scientists to make calculations that would not have been possible otherwise.
Related Links:
University of British Columbia
Université Laval
Researchers at the University of British Columbia (Vancouver, Canada), Université Laval (Canada), and other institutions requested data sets from the authors of a relatively homogenous set of 516 articles published between 2 and 22 years ago, finding that the availability of the data was strongly affected by article age. For papers where the authors gave the status of their data, the odds of a data set being extant fell by 17% per year. As a result, more 90% of the oldest data were inaccessible, and even in papers published as recently as 2011, they were only able to track down the data for 23% of the studies.
In addition, the odds that the researchers could even locate a working e-mail address for the first, last, or corresponding author fell by 7% per year. Defunct addresses were listed on the paper itself, with web searches not turning up any current ones. For another 38% of studies, the researcher’s queries led to no response. And even when they received a reply, access to another7% of the data sets was inaccessible, or the data itself was lost. The study was published on December 19, 2013, in Current Biology.
“Everybody kind of knows that if you ask a researcher for data from old studies, they’ll hem and haw, because they don’t know where it is,” said lead author zoologist Timothy Vines, PhD, of the University of British Columbia. “Some of the time, for instance, it was saved on three-and-a-half inch floppy disks, so no one could access it, because they no longer had the proper drives.”
“Because the basic idea of keeping data is so that it can be used by others in future research, this sort of obsolescence essentially renders the data useless,” added Dr. Vines. “Our results reinforce the notion that, in the long term, research data cannot be reliably preserved by individual researchers, and further demonstrate the urgent need for policies mandating data sharing via public archives.”
Preserving raw data is important because it is impossible to predict in which directions research will move in the future. Dr. Vines, for instance, has been conducting research on a pair of toad species native to Eastern Europe that seem to be in the process of hybridizing. In the 1980s, a separate team of researchers was working on the same topic, and came across an old paper written in Polish that documented the distribution of the toads in the 1930s. Knowing that their distribution had changed relatively little over the intervening decades allowed the scientists to make calculations that would not have been possible otherwise.
Related Links:
University of British Columbia
Université Laval
Latest Health IT News
- Weekly Remote Symptom Monitoring Improves Symptom Control in Advanced Cancer
- Digital Heart Model Supports Targeted Ablation in Atrial Fibrillation
- AI Framework Helps Clinicians Create Trustworthy Risk Prediction Tools
- AI Tool Screens for Primary Aldosteronism Using Routine EHR Data
- AI-Enabled ECG Software Predicts One-Year Atrial Fibrillation Risk
- AI-Native EHR Achieves EU Medical Device Certification
- EHR-Integrated Screening Workflow Detects Cognitive Impairment at Admission
- AI System Detects and Quantifies Chronic Subdural Hematoma
- Continuous Monitoring Platform Detects Infection Risk Across Care Transitions
- Automated System Classifies and Tracks Cardiogenic Shock Across Hospital Settings
- Voice-Driven AI System Enables Structured GI Procedure Documentation
- EMR-Based Tool Predicts Graft Failure After Kidney Transplant
Channels
Artificial Intelligence
view channel
AI Tool Predicts Chronic Kidney Disease Risk in Diabetes
Chronic kidney disease is a common and serious complication of type 2 diabetes and often progresses without obvious early symptoms, increasing morbidity and straining health systems. Many risk models were... Read more
AI Trends Report Guides Responsible, Effective Healthcare Deployment
Hospitals are under growing pressure to adopt artificial intelligence tools that improve safety, efficiency, and continuity of care without compromising quality. At the same time, clinicians need clearer... Read moreCritical Care
view channel
Wearable Microneedle Patch Monitors Antibiotic Levels in Real Time
Therapeutic drug monitoring for agents with narrow therapeutic windows often relies on intermittent blood draws and laboratory analysis, providing only snapshots of exposure. Real-time, minimally invasive... Read more
AI Analysis of EMS Calls Aids Pediatric Trauma Decision-Making
Accurate trauma triage is difficult when decisions rely on brief, noisy reports from emergency medical services (EMS). Misclassification can delay lifesaving interventions or lead to overuse of critical... Read moreSurgical Techniques
view channel
AI-Designed Microneedle Patch Accelerates Diabetic Wound Healing
Chronic diabetic wounds are slow to heal and prone to infection, often leading to repeated procedures and prolonged care. Standard closure methods bring wound edges together but do not adapt to changing... Read more
Focused Ultrasound System Gains CE Mark for Liver Tumor Treatment
Liver tumors remain a major global health challenge, and many patients are not candidates for resection or conventional thermal ablation. Tumor location, underlying liver disease, and other clinical factors... Read morePatient Care
view channel
AI Avatar Doctor Improves Patient Understanding Before Radiotherapy
Radiation oncology consultations require patients to grasp complex concepts quickly, yet anxiety and information overload often undermine understanding and informed consent. Poor comprehension can also... Read more
Wearable Sleep Data Predict Adherence to Pulmonary Rehabilitation
Chronic obstructive pulmonary disease (COPD) is a long-term lung disorder that makes breathing difficult and often disturbs sleep, reducing energy for daily activities. Limited engagement in pulmonary... Read moreHealth IT
view channel
Weekly Remote Symptom Monitoring Improves Symptom Control in Advanced Cancer
Patients receiving treatment for advanced cancer often struggle with uncontrolled symptoms and fragmented communication with clinicians. These gaps can impair daily function, increase emergency department... Read more
Digital Heart Model Supports Targeted Ablation in Atrial Fibrillation
Atrial fibrillation is an erratic, quivering heartbeat and a leading cause of stroke. Catheter ablation is widely used to interrupt arrhythmogenic tissue, yet many patients—especially with persistent ... Read morePoint of Care
view channel
New Brain Ultrasound Platform Enables Bedside Postoperative Imaging
Transporting postoperative patients for CT or MRI can create operational burdens, delays, and disruptions in care. Bedside visualization may help reduce transport demands, lower radiation exposure, and... Read more
Handheld Ultrasound Expands Point-of-Care Imaging Access in Brazil
Rapid access to diagnostic imaging is essential across hospitals, emergency departments, clinics, and municipal health systems, but large markets still face uneven availability, particularly in rural regions.... Read moreBusiness
view channel







