Data Management Standards Research Articles

Design and implementation of a national public health surveillance system in Jordan

Understanding and improving the health status of communities depend on effective public health surveillance. Adoption of new technologies, standardised case definitions and clinical guidelines for accurate diagnosis, and access to timely and reliable data, remains a challenge for public health surveillance systems however and existing public health surveillance systems are often fragmented, disease specific, inconsistent and of poor quality. We describe the application of an enterprise architecture approach to the design, planning and implementation of a national public health surveillance system in Jordan. This enabled a well planned and collaboratively supported system to be built and implemented using consistent standards for data collection, management, reporting and use. The system is case-based and integrated and employs mobile information technology to aid collection of real-time, standardised data to inform and improve decision-making at different levels of the health system.

Trends and challenges of ecosystem observations in the age of big data

With the development of observation technology, the scale of ecological research is increasing. Ecological observations have turned from small-scale, short-time individual observations into broad-scale, long-term, interdisciplinary, multi-factor group observations. Innovation in sensor techniques has led to a profound evolution in time and space precision of ecological observations, while the volume, type, and gen- erating speed of these observational data are increasing, which indicates that traditional ecological data ac- quisition, storage and management methods cannot afford the demands of modern ecological research. With the assistance of new big data storage, management and processing techniques, integrated with the Internet of Ecology, a citizen science observational network and standardized data management network, we can build an ecological observation system to resolve these issues. The concept to provide a one-station ecological ob- servation service to researchers represents the general trend of the development of ecological observations in the age of big data.

Maximising value by using good data to drive good decisions

The industry-wide move towards big data and the digital oilfield is underpinned by good data. This paper outlines a suite of data management standards, systems and processes, and provides examples of how these have led to improved decision making. The approach involved the development of standards and streamlined business processes followed by the implementation of systems focusing on production data accessibility, quality and integration. Accessibility was addressed by making real-time data readily available from multiple devices so users spend more time using data instead of locating it. Quality was improved through the implementation of processes such as operational data validation (ODV) and production allocation (PA). Integration was facilitated so that users could view data from various systems in a single location. The implementation of data management standards, systems and processes led to improved decision making in the areas of external reporting, operating cost, safety, environment, commercial, reservoir management, well surveillance, and situational awareness. In particular, implementation of the ODV process ensured the completeness, accuracy and timeliness of data from reservoir to sales. Furthermore, improved accessibility and integration increased situational awareness, reduced troubleshooting time, and improved problem analysis. While the concept of data management and quality control is not new, the novelty is in the approach of developing robust standards, implementation of systems based on these standards, and creating the supporting business process and culture aligned to what drives value in the organisation. This is easily transferable and adaptable across all facets of the petroleum industry.

Sustainability in Biobanking: Model of Biobank Graz.

Research infrastructures remain the key for state-of-the-art and successful research. In the last few decades, biobanks have become increasingly important in this field through standardization of biospecimen processing, sample storage, and standardized data management. Research infrastructure in cohort studies and other sample collection activities are currently experiencing a lack of long-term funding. In this article, the Biobank Graz discusses these aspects of sustainability including the definition of sustainability and necessity of a business plan, as well as cost calculation model in the field of biobanking. The economic state, critical success factors, and important operational issues are reviewed and described by the authors, using the example of the Biobank Graz. Sustainability in the field of biobanking is a globally important matter of necessity, starting from policy making and ending with security and documentation on each operational level.

The distribution of clinical phenotypes of preterm birth syndrome: implications for prevention.

Preterm birth has been difficult to study and prevent because of its complex syndromic nature. To identify phenotypes of preterm delivery syndrome in the Newborn Cross-Sectional Study of the INTERGROWTH-21st Project. A population-based, multiethnic, cross-sectional study conducted at 8 geographically demarcated sites in Brazil, China, India, Italy, Kenya, Oman, the United Kingdom, and the United States. A total of 60,058 births over a 12-month fixed period between April 27, 2009, and March 2, 2014. Of these, 53,871 had an ultrasonography estimate of gestational age, among which 5828 were preterm births (10.8%). Pregnancies were prospectively studied using a standardized data collection and online data management system. Newborns had anthropometric and clinical examinations using standardized methods and identical equipment and were followed up until hospital discharge. The main study outcomes were clusters of preterm phenotypes and for each cluster, we analyzed signs of presentation at hospital admission, admission rates for neonatal intensive care for 7 days or more, and neonatal mortality rates. Twelve preterm birth clusters were identified using our conceptual framework. Eleven consisted of combinations of conditions known to be associated with preterm birth, 10 of which were dominated by a single condition. However, the most common single cluster (30.0% of the total preterm cases; n = 1747) was not associated with any severe maternal, fetal, or placental condition that was clinically detectable based on the information available; within this cluster, many cases were caregiver initiated. Only 22% (n = 1284) of all the preterm births occurred spontaneously without any of these severe conditions. Maternal presentation on hospital admission, newborn anthropometry, and risk for death before hospital discharge or admission for 7 or more days to a neonatal intensive care unit, none of which were used to construct the clusters, also differed according to the identified phenotypes. The prevalence of preterm birth ranged from 8.2% in Muscat, Oman, and Oxford, England, to 16.6% in Seattle, Washington. We identified 12 preterm birth phenotypes associated with different patterns of neonatal outcomes. In 22% of all preterm births, parturition started spontaneously and was not associated with any of the phenotypic conditions considered. We believe these results contribute to an improved understanding of this complex syndrome and provide an empirical basis to focus research on a more homogenous set of phenotypes.

COLOMBIAN FROZEN BIODIVERSITY: 16 YEARS OF THE TISSUE COLLECTION OF THE HUMBOLDT INSTITUTE

Collections of tissue samples stand as keystone sources of molecular information to construct biodiversity knowledge, and are particularly useful in megadiverse countries. In 1998 the Humboldt Institute (<em>Instituto de Investigación de Recursos Biológicos Alexander von Humboldt</em>) began a tissue collection of Colombian biodiversity (IAvH-CT) and the aim of this work is to present a diagnostic and an historical narrative for that collection, constructed by compiling information and experiences on its management as well as by organizing and curating the information of each catalogued sample. After 16 years the IAvH-CT harbors 16469 samples, which represent around 2530 species from 1289 genera, and 323 families of the Colombian biodiversity. Samples are biased toward plants and birds (84 %), but also include other animal taxa. Geographically, IAvH-CT includes samples from all Colombian departments, but there is a broad variation in their coverage. When compared with other international collections IAvH-CT fulfills several standards of sample storage and data management, but have a major weakness that is that several tissues seem to lack a vouchered specimen. Tissues housed at IAvH-CT have been included in at least 48 studies published in several scientific journals. IAvH-CT is implementing strategies to improve curatorial standards, fill-up taxonomic gaps, and to explore the potential of its samples to understand the outstanding Colombian biota in a cooperative research frame among institutions.

Contemplation on the application of big data in clinical medicine

Medicine is another area where big data is being used. The link between clinical treatment and outcome is the key step when applying big data in medicine. In the era of big data, it is critical to collect complete outcome data. Patient follow-up, comprehensive integration of data resources, quality control and standardized data management are the predominant approaches to avoid missing data and data island. Therefore, establishment of systemic patients follow-up protocol and prospective data management strategy are the important aspects of big data in medicine.

The clinical liver safety assessment best practices workshop: rationale, goals, accomplishments and the future.

The workshop was successful in bringing international experts from industry, academia, and regulatory agencies together to address the need for industry-wide standardization of liver safety data collection, causality assessment, and liver safety data management. It should be noted that the consensus statements contained in the manuscripts are simply that. They are not regulatory policy, but hopefully will stimulate progress toward the lengthy process of updating and revising the 2009 guidance document. There was near unanimous agreement that future guidelines and policies should be based as much as possible on data that should be available through precompetitive collaboration. Importantly, the workshop established a core international group of concerned experts from academia, industry and regulatory bodies to improve and standardize the approaches to assessing liver safety in clinical trials. An important goal to consider in this effort would be the establishment of a Liver Safety Research Consortium.

Organization of marine phenology data in support of planning and conservation in ocean and coastal ecosystems

Among the many effects of climate change is its influence on the phenology of biota. In marine and coastal ecosystems, phenological shifts have been documented for multiple life forms; however, biological data related to marine species' phenology remain difficult to access and is under-used. We conducted an assessment of potential sources of biological data for marine species and their availability for use in phenological analyses and assessments. Our evaluations showed that data potentially related to understanding marine species' phenology are available through online resources of governmental, academic, and non-governmental organizations, but appropriate datasets are often difficult to discover and access, presenting opportunities for scientific infrastructure improvement. The developing Federal Marine Data Architecture when fully implemented will improve data flow and standardization for marine data within major federal repositories and provide an archival repository for collaborating academic and public data contributors. Another opportunity, largely untapped, is the engagement of citizen scientists in standardized collection of marine phenology data and contribution of these data to established data flows. Use of metadata with marine phenology related keywords could improve discovery and access to appropriate datasets. When data originators choose to self-publish, publication of research datasets with a digital object identifier, linked to metadata, will also improve subsequent discovery and access. Phenological changes in the marine environment will affect human economics, food systems, and recreation. No one source of data will be sufficient to understand these changes. The collective attention of marine data collectors is needed—whether with an agency, an educational institution, or a citizen scientist group—toward adopting the data management processes and standards needed to ensure availability of sufficient and useable marine data to understand marine phenology.

Shoreline Oiling Data Management for the Deepwater Horizon oil spill, Gulf of Mexico, USA: Implications for Data Management Standards for Future Spills of Significance

The Shoreline Cleanup Assessment Technique (SCAT) data management program for the Deepwater Horizon oil spill is, to our knowledge, the largest shoreline spill data management effort in history, still currently providing continuous data management of over 35,000 separate surveys covering over 22,000 survey-miles of shoreline and tens of millions of individual pieces of data. The program flexibly expanded the scope of coverage to support the changing requirements of survey and cleanup over the response, from surface and subsurface oiling survey data to treatment and administrative status, while maintaining backward compatibility and constant availability for planning and analysis. While we hope many of the tools and products developed will be of value in near-term future spill responses, we are less clear on the specific recommendations we can make to data managers during the next nationally significant spill in 10 or 20 years. The differing needs of each spill, varying levels of agency and industry personnel participation, and the inevitable and increasingly rapid change in software and information technology environments, all point to the need for a different way forward. We feel the most important contribution we can make is the recommendation of an open data standard for shoreline oiling and related data management, allowing interested parties in future responses to be assured of data interoperability, transparency, and data quality, while permitting required flexibility. We propose such a standard here. The proposed data standard does not compete with or supplant any existing vendor or solution, and is completely agnostic about physical spill environment, data collection methods, algorithms, software and computing environment. The standard requires only the most basic structured data so as to preserve the maximum flexibility for spill specific conditions and the unanticipated needs of future data collection. The core components are spatial geometry, temporal relationship, and database attribute and relationship requirements for storing and querying oiling, response, and administrative status via standard geometries over multiple time periods. We present generic entity-relationship diagrams and example core and expansion data structures that outline the proposed standard. In the same way that SCAT methodology protocols and terminology have been adopted across the spill response community by agency and industry, we suggest a core standard for storage and analysis of shoreline oiling and response data. This standard reflects, we hope, a root-level understanding of the purpose and scope of SCAT and related data, and imposes only the minimum uniformity required to be of use.

Reflections on a Vision for Integrated Research and Monitoring After 15 Years

In May of 1998, Owen Bricker and his co-author Michael Ruggiero introduced a conceptual design for integrating the Nation’s environmental research and monitoring programs. The Framework for Integrated Monitoring and Related Research was an organizing strategy for relating data collected by various programs, at multiple spatial and temporal scales, and by multiple science disciplines to solve complex ecological issues that individual research or monitoring programs were not designed to address. The concept nested existing intensive monitoring and research stations within national and regional surveys, remotely sensed data, and inventories to produce a collaborative program for multi-scale, multi-network integrated environmental monitoring and research. Analyses of gaps in data needed for specific issues would drive decisions on network improvements or enhancements. Data contributions to the Framework from existing networks would help indicate critical research and monitoring programs to protect during budget reductions. Significant progress has been made since 1998 on refining the Framework strategy. Methods and models for projecting scientific information across spatial and temporal scales have been improved, and a few regional pilots of multi-scale data-integration concepts have been attempted. The links between science and decision-making are also slowly improving and being incorporated into science practice. Experiments with the Framework strategy since 1998 have revealed the foundational elements essential to its successful implementation, such as defining core measurements, establishing standards of data collection and management, integrating research and long-term monitoring, and describing baseline ecological conditions. They have also shown us the remaining challenges to establishing the Framework concept: protecting and enhancing critical long-term monitoring, filling gaps in measurement methods, improving science for decision support, and integrating the disparate integrated science efforts now underway. In the 15 years since the Bricker and Ruggiero (Ecol Appl 8(2):326–329, 1998) paper challenged us with a new paradigm for bringing sound and comprehensive science to environmental decisions, the scientific community can take pride in the progress that has been made, while also taking stock of the challenges ahead for completing the Framework vision.

Teenagers and texting: use of a youth ecological momentary assessment system in trajectory health research with latina adolescents.

BackgroundAdolescent females send and receive more text messages than any others, with an average of 4050 texts a month. Despite this technological inroad among adolescents, few researchers are utilizing text messaging technology to collect real time, contextualized data. Temporal variables (ie, mood) collected regularly over a period of time could yield useful insights, particularly for evaluating health intervention outcomes. Use of text messaging technology has multiple benefits, including capacity of researchers to immediately act in response to texted information.ObjectiveThe objective of our study was to custom build a short messaging service (SMS) or text messaging assessment delivery system for use with adolescents. The Youth Ecological Momentary Assessment System (YEMAS) was developed to collect automated texted reports of daily activities, behaviors, and attitudes among adolescents, and to examine the feasibility of YEMAS. This system was created to collect and transfer real time data about individual- and social-level factors that influence physical, mental, emotional, and social well-being.MethodsYEMAS is a custom designed system that interfaces with a cloud-based communication system to automate scheduled delivery of survey questions via text messaging; we designed this university-based system to meet data security and management standards. This was a two-phase study that included development of YEMAS and a feasibility pilot with Latino adolescent females. Relative homogeneity of participants was desired for the feasibility pilot study; adolescent Latina youth were sought because they represent the largest and fastest growing ethnic minority group in the United States. Females were targeted because they demonstrate the highest rate of text messaging and were expected to be interested in participating. Phase I involved development of YEMAS and Phase II involved piloting of the system with Latina adolescents. Girls were eligible to participate if they were attending one of the participating high schools and self-identified as Latina. We contacted 96 adolescents; of these, 24 returned written parental consent forms, completed assent processes, and enrolled in the study.ResultsYEMAS was collaboratively developed and implemented. Feasibility was established with Latina adolescents (N=24), who responded to four surveys daily for two two-week periods (four weeks total). Each survey had between 12 and 17 questions, with responses including yes/no, Likert scale, and open-ended options. Retention and compliance rates were high, with nearly 18,000 texts provided by the girls over the course of the pilot period.ConclusionsPilot results support the feasibility and value of YEMAS, an automated SMS-based text messaging data collection system positioned within a secure university environment. This approach capitalizes on immediate data transfer protocols and enables the documentation of participants’ thoughts, feelings, and behaviors in real time. Data are collected using mobile devices that are familiar to participants and nearly ubiquitous in developed countries.

Standards in molecular diagnostics for the discovery and validation of clinically useful cancer biomarkers

Recent discoveries in cancer biology have greatly increased the understanding of cancer at the molecular level, but translating this knowledge into clinically useful diagnostic tests has proved challenging. More efficient transfer of new molecular tests into patient care requires better standardization of laboratory practices, measurement methods and data management. The workshop assembled experts from National Cancer Institute, US FDA, National Institute of Standards and Technology, academia and industry, to address the most efficient approaches to biomarker standardization and validation. The workshop participants described the current state of research in molecular diagnostics standardization and addressed three questions: what has worked? What has not?And what needs improving?

走査型プローブ顕微鏡データマネジメントの標準化

走査型プローブ顕微鏡データマネジメントの標準化

In Silico Analysis of Nanomaterials Hazard and Risk

Because a variety of human-related activities, engineer-ed nanoparticles (ENMs) may be released to various environmental media and may cross environmental boundaries, and thus will be found in most media. Therefore, the potential environmental impacts of ENMs must be assessed from a multimedia perspective and with an integrated risk management approach that considers rapid developments and increasing use of new nanomaterials. Accordingly, this Account presents a rational process for the integration of in silico ENM toxicity and fate and transport analyses for environmental impact assessment. This approach requires knowledge of ENM toxicity and environmental exposure concentrations. Considering the large number of current different types of ENMs and that those numbers are likely to increase, there is an urgent need to accelerate the evaluation of their toxicity and the assessment of their potential distribution in the environment. Developments in high throughput screening (HTS) are now enabling the rapid generation of large data sets for ENM toxicity assessment. However, these analyses require the establishment of reliable toxicity metrics, especially when HTS includes data from multiple assays, cell lines, or organisms. Establishing toxicity metrics with HTS data requires advanced data processing techniques in order to clearly identify significant biological effects associated with exposure to ENMs. HTS data can form the basis for developing and validating in silico toxicity models (e.g., quantitative structure-activity relationships) and for generating data-driven hypotheses to aid in establishing and/or validating possible toxicity mechanisms. To correlate the toxicity of ENMs with their physicochemical properties, researchers will need to develop quantitative structure-activity relationships for nanomaterials (i.e., nano-SARs). However, as nano-SARs are applied in regulatory applications, researchers must consider their applicability and the acceptance level of false positive relative to false negative predictions and the reliability of toxicity data. To establish the environmental impact of ENMs identified as toxic, researchers will need to estimate the potential level of environmental exposure concentration of ENMs in the various media such as air, water, soil, and vegetation. When environmental monitoring data are not available, models of ENMs fate and transport (at various levels of complexity) serve as alternative approaches for estimating exposure concentrations. Risk management decisions regarding the manufacturing, use, and environmental regulations of ENMs would clearly benefit from both the assessment of potential ENMs exposure concentrations and suitable toxicity metrics. The decision process should consider the totality of available information: quantitative and qualitative data and the analysis of nanomaterials toxicity, and fate and transport behavior in the environment. Effective decision-making to address the potential impacts of nanomaterials will require considerations of the relevant environmental, ecological, technological, economic, and sociopolitical factors affecting the complete lifecycle of nanomaterials, while accounting for data and modeling uncertainties. Accordingly, researchers will need to establish standardized data management and analysis tools through nanoinformatics as a basis for the development of rational decision tools.

Temperature dataloggers as stove use monitors (SUMs): Field methods and signal analysis

We report the field methodology of a 32-month monitoring study with temperature dataloggers as Stove Use Monitors (SUMs) to quantify usage of biomass cookstoves in 80 households of rural Guatemala. The SUMs were deployed in two stoves types: a well-operating chimney cookstove and the traditional open-cookfire. We recorded a total of 31,112 days from all chimney cookstoves, with a 10% data loss rate. To count meals and determine daily use of the stoves we implemented a peak selection algorithm based on the instantaneous derivatives and the statistical long-term behavior of the stove and ambient temperature signals. Positive peaks with onset and decay slopes exceeding predefined thresholds were identified as “fueling events”, the minimum unit of stove use. Adjacent fueling events detected within a fixed-time window were clustered in single “cooking events” or “meals”. The observed means of the population usage were: 89.4% days in use from all cookstoves and days monitored, 2.44 meals per day and 2.98 fueling events. We found that at this study site a single temperature threshold from the annual distribution of daily ambient temperatures was sufficient to differentiate days of use with 0.97 sensitivity and 0.95 specificity compared to the peak selection algorithm. With adequate placement, standardized data collection protocols and careful data management the SUMs can provide objective stove-use data with resolution, accuracy and level of detail not possible before. The SUMs enable unobtrusive monitoring of stove-use behavior and its systematic evaluation with stove performance parameters of air pollution, fuel consumption and climate-altering emissions.

Electronic Data Collection and Management System for Global Adult Tobacco Survey

Introduction:Portable handheld computers and electronic data management systems have been used for national surveys in many high-income countries, however their use in developing countries has been challenging due to varying geographical, economic, climatic, political and cultural environments. In order to monitor and measure global adult tobacco use, the World Health Organization and the US Centers for Disease Control and Prevention initiated the Global Adult Tobacco Survey, a nationally representative household survey of adults, 15 years of age or older, using a standard core questionnaire, sample design, and data collection and management procedures. The Survey has been conducted in 14 low- and middle-income countries, using an electronic data collection and management system. This paper describes implementation of the electronic data collection system and associated findings.Methods:The Survey was based on a comprehensive data management protocol, to enable standardized, globally comparable high quality data collection and management. It included adaptation to specific country needs, selection of appropriate handheld hardware devices, use of open source software, and building country capacity and provide technical support.Results:In its first phase, the Global Adult Tobacco Survey was successfully conducted between 2008 and 2010, using an electronic data collection and management system for interviews in 302,800 households in 14 countries. More than 2,644 handheld computers were fielded and over 2,634 fieldworkers, supervisors and monitors were trained to use them. Questionnaires were developed and programmed in 38 languages and scripts. The global hardware failure rate was < 1% and data loss was almost 0%.Conclusion:Electronic data collection and management systems can be used effectively for conducting nationally representative surveys, particularly in low- and middle-income countries, irrespective of geographical, climatic, political and cultural environments, and capacity-building at the country level is an important vehicle for Health System Strengthening.

The need for data: natural disasters and the challenges of database management

Hundreds of natural catastrophes occur worldwide every year—there were 780 loss events per year on average over the last 10 years. Since 1980, these disasters have claimed over two million lives and caused losses worth US$ 3,000 billion. The deadliest disasters were caused by earthquakes: the tsunami following the Sumatra quake (2004) and the Haiti earthquake (2010) claimed more than 220,000 lives each. The Great East Japan Earthquake of 11 March 2011 was the costliest natural disaster of all times, with total losses of US$ 210 billion. Hurricane Katrina, in 2005, was the second costliest disaster, with total losses of US$ 140 billion (in 2010 values). To ensure that high-quality natural disaster analyses can be performed, the data have to be collected, checked and managed with a high degree of expertise and professionality. Scientists, governmental and non-governmental organisations and the finance industry make use of global databases that contain losses attributable to natural catastrophes. At present, there are three global and multi-peril loss databases: NatCatSERVICE (Munich Re), Sigma (Swiss Re) and EM-Dat (Centre for Research on the Epidemiology of Disasters). They are supplemented by numerous databases focusing on national or regional issues, certain hazards and specific sectors. This paper outlines the criteria and definitions relating to how global and multi-peril databases are operated, and the efforts being made to ensure consistent and internationally recognised standards of data management. In addition, it presents the concept and methodology underlying the NatCatSERVICE database, and points out the many challenges associated with data acquisition and data management.

PP081. Study group obstetrics – A platform for efficient collaboration and networking in obstetrical science

Modern medical science has to meet a series of challenges including the integration of new technologies and strategies to daily scientific routine. Biobanking is defined as 'a collection of biological material and the associated data and information stored in an organized system for a population or a large subset of a population' and plays a key role in these efforts. The study group obstetrics aims to establish a platform for efficient collaboration and networking in obstetrical science. Based on existing resources, technologies and expertise, autonomous data and sample collection in local biobanks shall be processed with uniformed SOPs to guarantee quality and compatibility. The study group obstetrics has created harmonized standards for sample and data management in biobanks as well as ethical and legal frameworks. Internet - based data management with uniform documentation sheets guarantee high data quality. Material and data are administrated autonomously and can be combined in the context of specific co-operations. Due to the outstanding dynamics over a limited period, the human pregnancy is an attractive field for biobanking and clinical case/control cohorts including disease focused cohorts. Harmonized standards and linkage in a network allow efficient scientific co-operations. Everyone interested is invited to join the study group obstetrics as an equitable member.

AIP: a tool for flexible and transparent data management

Existing data management tools have some limitations such as restrictions to specific file systems or shortage of transparence to applications. In this paper, we present a new data management tool called AIP, which is implemented via the standard data management API, and hence it supports multiple file systems and makes data management operations transparent to applications. First, AIP provides centralized policy-based data management for controlling the placement of files in different storage tiers. Second, AIP uses differentiated collections of file states to improve the execution efficiency of data management policies, with the help of the caching mechanism of file states. Third, AIP also provides a resource arbitration mechanism for controlling the rate of initiated data management operations. Our results from representative experiments demonstrate that AIP has the ability to provide high performance, to introduce low management overhead, and to have good scalability.