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1.  Eurocan plus report: feasibility study for coordination of national cancer research activities 
Summary
The EUROCAN+PLUS Project, called for by the European Parliament, was launched in October 2005 as a feasibility study for coordination of national cancer research activities in Europe. Over the course of the next two years, the Project process organized over 60 large meetings and countless smaller meetings that gathered in total over a thousand people, the largest Europe–wide consultation ever conducted in the field of cancer research.
Despite a strong tradition in biomedical science in Europe, fragmentation and lack of sustainability remain formidable challenges for implementing innovative cancer research and cancer care improvement. There is an enormous duplication of research effort in the Member States, which wastes time, wastes money and severely limits the total intellectual concentration on the wide cancer problem. There is a striking lack of communication between some of the biggest actors on the European scene, and there are palpable tensions between funders and those researchers seeking funds.
It is essential to include the patients’ voice in the establishment of priority areas in cancer research at the present time. The necessity to have dialogue between funders and scientists to establish the best mechanisms to meet the needs of the entire community is evident. A top priority should be the development of translational research (in its widest form), leading to the development of effective and innovative cancer treatments and preventive strategies. Translational research ranges from bench–to–bedside innovative cancer therapies and extends to include bringing about changes in population behaviours when a risk factor is established.
The EUROCAN+PLUS Project recommends the creation of a small, permanent and independent European Cancer Initiative (ECI). This should be a model structure and was widely supported at both General Assemblies of the project. The ECI should assume responsibility for stimulating innovative cancer research and facilitating processes, becoming the common voice of the cancer research community and serving as an interface between the cancer research community and European citizens, patients’ organizations, European institutions, Member States, industry and small and medium enterprises (SMEs), putting into practice solutions aimed at alleviating barriers to collaboration and coordination of cancer research activities in the European Union, and dealing with legal and regulatory issues. The development of an effective ECI will require time, but this entity should be established immediately. As an initial step, coordination efforts should be directed towards the creation of a platform on translational research that could encompass (1) coordination between basic, clinical and epidemiological research; (2) formal agreements of co–operation between comprehensive cancer centres and basic research laboratories throughout Europe and (3) networking between funding bodies at the European level.
The European Parliament and its instruments have had a major influence in cancer control in Europe, notably in tobacco control and in the implementation of effective population–based screening. To make further progress there is a need for novelty and innovation in cancer research and prevention in Europe, and having a platform such as the ECI, where those involved in all aspects of cancer research can meet, discuss and interact, is a decisive development for Europe.
Executive Summary
Cancer is one of the biggest public health crises facing Europe in the 21st century—one for which Europe is currently not prepared nor preparing itself. Cancer is a major cause of death in Europe with two million casualties and three million new cases diagnosed annually, and the situation is set to worsen as the population ages.
These facts led the European Parliament, through the Research Directorate-General of the European Commission, to call for initiatives for better coordination of cancer research efforts in the European Union. The EUROCAN+PLUS Project was launched in October 2005 as a feasibility study for coordination of national cancer research activities. Over the course of the next two years, the Project process organized over 60 large meetings and countless smaller meetings that gathered in total over a thousand people. In this respect, the Project became the largest Europe-wide consultation ever conducted in the field of cancer research, implicating researchers, cancer centres and hospitals, administrators, healthcare professionals, funding agencies, industry, patients’ organizations and patients.
The Project first identified barriers impeding research and collaboration in research in Europe. Despite a strong tradition in biomedical science in Europe, fragmentation and lack of sustainability remain the formidable challenges for implementing innovative cancer research and cancer care improvement. There is an enormous duplication of research effort in the Member States, which wastes time, wastes money and severely limits the total intellectual concentration on the wide cancer problem. There is a striking lack of communication between some of the biggest actors on the European scene, and there are palpable tensions between funders and those researchers seeking funds.
In addition, there is a shortage of leadership, a multiplicity of institutions each focusing on its own agenda, sub–optimal contact with industry, inadequate training, non–existent career paths, low personnel mobility in research especially among clinicians and inefficient funding—all conspiring against efficient collaboration in cancer care and research. European cancer research today does not have a functional translational research continuum, that is the process that exploits biomedical research innovations and converts them into prevention methods, diagnostic tools and therapies. Moreover, epidemiological research is not integrated with other types of cancer research, and the implementation of the European Directives on Clinical Trials 1 and on Personal Data Protection 2 has further slowed the innovation process in Europe. Furthermore, large inequalities in health and research exist between the EU–15 and the New Member States.
The picture is not entirely bleak, however, as the European cancer research scene presents several strengths, such as excellent basic research and clinical research and innovative etiological research that should be better exploited.
When considering recommendations, several priority dimensions had to be retained. It is essential that proposals include actions and recommendations that can benefit all Member States of the European Union and not just States with the elite centres. It is also essential to have a broader patient orientation to help provide the knowledge to establish cancer control possibilities when we exhaust what can be achieved by the implementation of current knowledge. It is vital that the actions proposed can contribute to the Lisbon Strategy to make Europe more innovative and competitive in (cancer) research.
The Project participants identified six areas for which consensus solutions should be implemented in order to obtain better coordination of cancer research activities. The required solutions are as follows. The proactive management of innovation, detection, facilitation of collaborations and maintenance of healthy competition within the European cancer research community.The establishment of an exchange portal of information for health professionals, patients and policy makers.The provision of guidance for translational and clinical research including the establishment of a translational research platform involving comprehensive cancer centres and cancer research centres.The coordination of calls and financial management of cancer research projects.The construction of a ‘one–stop shop’ as a contact interface between the industry, small and medium enterprises, scientists and other stakeholders.The support of greater involvement of healthcare professionals in translational research and multidisciplinary training.
In the course of the EUROCAN+PLUS consultative process, several key collaborative projects emerged between the various groups and institutes engaged in the consultation. There was a collaboration network established with Europe’s leading Comprehensive Cancer Centres; funding was awarded for a closer collaboration of Owners of Cancer Registries in Europe (EUROCOURSE); there was funding received from FP7 for an extensive network of leading Biological Resource Centres in Europe (BBMRI); a Working Group identified the special needs of Central, Eastern and South–eastern Europe and proposed a remedy (‘Warsaw Declaration’), and the concept of developing a one–stop shop for dealing with academia and industry including the Innovative Medicines Initiative (IMI) was discussed in detail.
Several other dimensions currently lacking were identified. There is an absolute necessity to include the patients’ voice in the establishment of priority areas in cancer research at the present time. It was a salutary lesson when it was recognized that all that is known about the quality of life of the cancer patient comes from the experience of a tiny proportion of cancer patients included in a few clinical trials. The necessity to have dialogue between funders and scientists to establish the best mechanisms to meet the needs of the entire community was evident. A top priority should be the development of translational research (in its widest form) and the development of effective and innovative cancer treatments and preventative strategies in the European Union. Translational research ranges from bench-to-bedside innovative cancer therapies and extends to include bringing about changes in population behaviours when a risk factor is established.
Having taken note of the barriers and the solutions and having examined relevant examples of existing European organizations in the field, it was agreed during the General Assembly of 19 November 2007 that the EUROCAN+PLUS Project had to recommend the creation of a small, permanent and neutral ECI. This should be a model structure and was widely supported at both General Assemblies of the project. The proposal is based on the successful model of the European Molecular Biology Organisation (EMBO), and its principal aims include providing a forum where researchers from all backgrounds and from all countries can meet with members of other specialities including patients, nurses, clinicians, funders and scientific administrators to develop priority programmes to make Europe more competitive in research and more focused on the cancer patient.
The ECI should assume responsibility for: stimulating innovative cancer research and facilitating processes;becoming the common voice of the cancer research community and serving as an interface between the cancer research community and European citizens, patients’ and organizations;European institutions, Member States, industry and small and medium enterprises;putting into practice the aforementioned solutions aimed at alleviating barriers and coordinating cancer research activities in the EU;dealing with legal and regulatory issues.
Solutions implemented through the ECI will lead to better coordination and collaboration throughout Europe, more efficient use of resources, an increase in Europe’s attractiveness to the biomedical industry and better quality of cancer research and education of health professionals.
The Project considered that European legal instruments currently available were inadequate for addressing many aspects of the barriers identified and for the implementation of effective, lasting solutions. Therefore, the legal environment that could shelter an idea like the ECI remains to be defined but should be done so as a priority. In this context, the initiative of the European Commission for a new legal entity for research infrastructure might be a step in this direction. The development of an effective ECI will require time, but this should be established immediately. As an initial step, coordination efforts should be directed towards the creation of a platform on translational research that could encompass: (1) coordination between basic, clinical and epidemiological research; (2) formal agreements of co-operation between comprehensive cancer centres and basic research laboratories throughout Europe; (3) networking between funding bodies at the European level. Another topic deserving immediate attention is the creation of a European database on cancer research projects and cancer research facilities.
Despite enormous progress in cancer control in Europe during the past two decades, there was an increase of 300,000 in the number of new cases of cancer diagnosed between 2004 and 2006. The European Parliament and its instruments have had a major influence in cancer control, notably in tobacco control and in the implementation of effective population–based screening. To make further progress there is a need for novelty and innovation in cancer research and prevention in Europe, and having a platform such as the ECI, where those involved in all aspects of cancer research can meet, discuss and interact, is a decisive development for Europe.
doi:10.3332/ecancer.2011.84
PMCID: PMC3234055  PMID: 22274749
2.  Facebook for Scientists: Requirements and Services for Optimizing How Scientific Collaborations Are Established 
Background
As biomedical research projects become increasingly interdisciplinary and complex, collaboration with appropriate individuals, teams, and institutions becomes ever more crucial to project success. While social networks are extremely important in determining how scientific collaborations are formed, social networking technologies have not yet been studied as a tool to help form scientific collaborations. Many currently emerging expertise locating systems include social networking technologies, but it is unclear whether they make the process of finding collaborators more efficient and effective.
Objective
This study was conducted to answer the following questions: (1) Which requirements should systems for finding collaborators in biomedical science fulfill? and (2) Which information technology services can address these requirements?
Methods
The background research phase encompassed a thorough review of the literature, affinity diagramming, contextual inquiry, and semistructured interviews. This phase yielded five themes suggestive of requirements for systems to support the formation of collaborations. In the next phase, the generative phase, we brainstormed and selected design ideas for formal concept validation with end users. Then, three related, well-validated ideas were selected for implementation and evaluation in a prototype.
Results
Five main themes of systems requirements emerged: (1) beyond expertise, successful collaborations require compatibility with respect to personality, work style, productivity, and many other factors (compatibility); (2) finding appropriate collaborators requires the ability to effectively search in domains other than your own using information that is comprehensive and descriptive (communication); (3) social networks are important for finding potential collaborators, assessing their suitability and compatibility, and establishing contact with them (intermediation); (4) information profiles must be complete, correct, up-to-date, and comprehensive and allow fine-grained control over access to information by different audiences (information quality and access); (5) keeping online profiles up-to-date should require little or no effort and be integrated into the scientist’s existing workflow (motivation). Based on the requirements, 16 design ideas underwent formal validation with end users. Of those, three were chosen to be implemented and evaluated in a system prototype, “Digital|Vita”: maintaining, formatting, and semi-automated updating of biographical information; searching for experts; and building and maintaining the social network and managing document flow.
Conclusions
In addition to quantitative and factual information about potential collaborators, social connectedness, personal and professional compatibility, and power differentials also influence whether collaborations are formed. Current systems only partially model these requirements. Services in Digital|Vita combine an existing workflow, maintaining and formatting biographical information, with collaboration-searching functions in a novel way. Several barriers to the adoption of systems such as Digital|Vita exist, such as potential adoption asymmetries between junior and senior researchers and the tension between public and private information. Developers and researchers may consider one or more of the services described in this paper for implementation in their own expertise locating systems.
doi:10.2196/jmir.1047
PMCID: PMC2553246  PMID: 18701421
Expertise locating systems; computer supported collaborative work; information systems; collaborators; research; social networks; translational research
3.  The Impact of eHealth on the Quality and Safety of Health Care: A Systematic Overview 
PLoS Medicine  2011;8(1):e1000387.
Aziz Sheikh and colleagues report the findings of their systematic overview that assessed the impact of eHealth solutions on the quality and safety of health care.
Background
There is considerable international interest in exploiting the potential of digital solutions to enhance the quality and safety of health care. Implementations of transformative eHealth technologies are underway globally, often at very considerable cost. In order to assess the impact of eHealth solutions on the quality and safety of health care, and to inform policy decisions on eHealth deployments, we undertook a systematic review of systematic reviews assessing the effectiveness and consequences of various eHealth technologies on the quality and safety of care.
Methods and Findings
We developed novel search strategies, conceptual maps of health care quality, safety, and eHealth interventions, and then systematically identified, scrutinised, and synthesised the systematic review literature. Major biomedical databases were searched to identify systematic reviews published between 1997 and 2010. Related theoretical, methodological, and technical material was also reviewed. We identified 53 systematic reviews that focused on assessing the impact of eHealth interventions on the quality and/or safety of health care and 55 supplementary systematic reviews providing relevant supportive information. This systematic review literature was found to be generally of substandard quality with regards to methodology, reporting, and utility. We thematically categorised eHealth technologies into three main areas: (1) storing, managing, and transmission of data; (2) clinical decision support; and (3) facilitating care from a distance. We found that despite support from policymakers, there was relatively little empirical evidence to substantiate many of the claims made in relation to these technologies. Whether the success of those relatively few solutions identified to improve quality and safety would continue if these were deployed beyond the contexts in which they were originally developed, has yet to be established. Importantly, best practice guidelines in effective development and deployment strategies are lacking.
Conclusions
There is a large gap between the postulated and empirically demonstrated benefits of eHealth technologies. In addition, there is a lack of robust research on the risks of implementing these technologies and their cost-effectiveness has yet to be demonstrated, despite being frequently promoted by policymakers and “techno-enthusiasts” as if this was a given. In the light of the paucity of evidence in relation to improvements in patient outcomes, as well as the lack of evidence on their cost-effectiveness, it is vital that future eHealth technologies are evaluated against a comprehensive set of measures, ideally throughout all stages of the technology's life cycle. Such evaluation should be characterised by careful attention to socio-technical factors to maximise the likelihood of successful implementation and adoption.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
There is considerable international interest in exploiting the potential of digital health care solutions, often referred to as eHealth—the use of information and communication technologies—to enhance the quality and safety of health care. Often accompanied by large costs, any large-scale expenditure on eHealth—such as electronic health records, picture archiving and communication systems, ePrescribing, associated computerized provider order entry systems, and computerized decision support systems—has tended to be justified on the grounds that these are efficient and cost-effective means for improving health care. In 2005, the World Health Assembly passed an eHealth resolution (WHA 58.28) that acknowledged, “eHealth is the cost-effective and secure use of information and communications technologies in support of health and health-related fields, including health-care services, health surveillance, health literature, and health education, knowledge and research,” and urged member states to develop and implement eHealth technologies. Since then, implementing eHealth technologies has become a main priority for many countries. For example, England has invested at least £12.8 billion in a National Programme for Information Technology for the National Health Service, and the Obama administration in the United States has committed to a US$38 billion eHealth investment in health care.
Why Was This Study Done?
Despite the wide endorsement of and support for eHealth, the scientific basis of its benefits—which are repeatedly made and often uncritically accepted—remains to be firmly established. A robust evidence-based perspective on the advantages on eHealth could help to suggest priority areas that have the greatest potential for benefit to patients and also to inform international eHealth deliberations on costs. Therefore, in order to better inform the international community, the authors systematically reviewed the published systematic review literature on eHealth technologies and evaluated the impact of these technologies on the quality and safety of health care delivery.
What Did the Researchers Do and Find?
The researchers divided eHealth technologies into three main categories: (1) storing, managing, and transmission of data; (2) clinical decision support; and (3) facilitating care from a distance. Then, implementing methods based on those developed by the Cochrane Collaboration and the NHS Service Delivery and Organisation Programme, the researchers used detailed search strategies and maps of health care quality, safety, and eHealth interventions to identify relevant systematic reviews (and related theoretical, methodological, and technical material) published between 1997 and 2010. Using these techniques, the researchers retrieved a total of 46,349 references from which they identified 108 reviews. The 53 reviews that the researchers finally selected (and critically reviewed) provided the main evidence base for assessing the impact of eHealth technologies in the three categories selected.
In their systematic review of systematic reviews, the researchers included electronic health records and picture archiving communications systems in their evaluation of category 1, computerized provider (or physician) order entry and e-prescribing in category 2, and all clinical information systems that, when used in the context of eHealth technologies, integrate clinical and demographic patient information to support clinician decision making in category 3.
The researchers found that many of the clinical claims made about the most commonly used eHealth technologies were not substantiated by empirical evidence. The evidence base in support of eHealth technologies was weak and inconsistent and importantly, there was insubstantial evidence to support the cost-effectiveness of these technologies. For example, the researchers only found limited evidence that some of the many presumed benefits could be realized; importantly, they also found some evidence that introducing these new technologies may on occasions also generate new risks such as prescribers becoming over-reliant on clinical decision support for e-prescribing, or overestimate its functionality, resulting in decreased practitioner performance.
What Do These Findings Mean?
The researchers found that despite the wide support for eHealth technologies and the frequently made claims by policy makers when constructing business cases to raise funds for large-scale eHealth projects, there is as yet relatively little empirical evidence to substantiate many of the claims made about eHealth technologies. In addition, even for the eHealth technology tools that have proven to be successful, there is little evidence to show that such tools would continue to be successful beyond the contexts in which they were originally developed. Therefore, in light of the lack of evidence in relation to improvements in patient outcomes, as well as the lack of evidence on their cost-effectiveness, the authors say that future eHealth technologies should be evaluated against a comprehensive set of measures, ideally throughout all stages of the technology's life cycle, and include socio-technical factors to maximize the likelihood of successful implementation and adoption in a given context. Furthermore, it is equally important that eHealth projects that have already been commissioned are subject to rigorous, multidisciplinary, and independent evaluation.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000387.
The authors' broader study is: Car J, Black A, Anandan C, Cresswell K, Pagliari C, McKinstry B, et al. (2008) The Impact of eHealth on the Quality and Safety of Healthcare. Available at: http://www.haps.bham.ac.uk/publichealth/cfhep/001.shtml
More information is available on the World Health Assembly eHealth resolution
The World Health Organization provides information at the Global Observatory on eHealth, as well as a global insight into eHealth developments
The European Commission provides Information on eHealth in Europe and some examples of good eHealth practice
More information is provided on NHS Connecting for Health
doi:10.1371/journal.pmed.1000387
PMCID: PMC3022523  PMID: 21267058
4.  Transforming Epidemiology for 21st Century Medicine and Public Health 
In 2012, the National Cancer Institute (NCI) engaged the scientific community to provide a vision for cancer epidemiology in the 21st century. Eight overarching thematic recommendations, with proposed corresponding actions for consideration by funding agencies, professional societies, and the research community emerged from the collective intellectual discourse. The themes are (i) extending the reach of epidemiology beyond discovery and etiologic research to include multilevel analysis, intervention evaluation, implementation, and outcomes research; (ii) transforming the practice of epidemiology by moving towards more access and sharing of protocols, data, metadata, and specimens to foster collaboration, to ensure reproducibility and replication, and accelerate translation; (iii) expanding cohort studies to collect exposure, clinical and other information across the life course and examining multiple health-related endpoints; (iv) developing and validating reliable methods and technologies to quantify exposures and outcomes on a massive scale, and to assess concomitantly the role of multiple factors in complex diseases; (v) integrating “big data” science into the practice of epidemiology; (vi) expanding knowledge integration to drive research, policy and practice; (vii) transforming training of 21st century epidemiologists to address interdisciplinary and translational research; and (viii) optimizing the use of resources and infrastructure for epidemiologic studies. These recommendations can transform cancer epidemiology and the field of epidemiology in general, by enhancing transparency, interdisciplinary collaboration, and strategic applications of new technologies. They should lay a strong scientific foundation for accelerated translation of scientific discoveries into individual and population health benefits.
doi:10.1158/1055-9965.EPI-13-0146
PMCID: PMC3625652  PMID: 23462917
big data; clinical trials; cohort studies; epidemiology; genomics; medicine; public health; technologies; training; translational research
5.  Google Wave: Have CTSA-Minded Institutions Caught It? 
Background
Google Wave was touted as the next big communication tool—combining e-mail, social networking, and chat within a single “wave”—with the potential to create a new world for collaboration. Information professionals who are knowledgeable of this tool and its capabilities could become uniquely situated to use it, evaluate it, and teach it. This seemed especially true for those working within Clinical and Translational Science Award (CTSA)-minded institutions, given the promise of interdisciplinary collaboration between investigators and the potential for creating new authorship models. This case study on Google Wave users who are affiliated with CTSA-minded institutions, was designed for and presented at the Evidence-Based Scholarly Communication Conference held by the University of New Mexico Health Sciences Library and Information Center. It provides an early evidence based evaluation of Google Wave's potential.
Methods
Two “waves” were created. The first consisted of five survey questions designed to collect demographic data on the respondents' roles, a general impression of Wave, the specific tools within Wave that might be useful, and potential collaborators with whom the respondents might use Wave. The second wave was a private, guided discussion on Wave's collaboration potential. Individuals from CTSA-minded institutions were invited to participate with messages on Twitter, forums, blogs, and electronic mail lists, although there were difficulties reaching out to these institutions as a group.
Results
By the conclusion of the study, only a small number of people (n=11, with a viable n=9) had responded to the survey. Given this small result set, it made sense to group the responses by the respondents' roles (CTSA staff and researchers, support staff, medical librarian, or general public) and to treat them as individual cases. Most of the respondents were librarians and support staff who felt that Wave might have potential for collaboration; there were no CTSA researcher respondents. For the second part of the study, the discussion wave, only one participant explicitly expressed interest in joining. All were invited to join, but there was no participation in the discussion wave at the conclusion of the study.
Conclusions
The results of this study implied that Google Wave was not on the forefront of CTSA-minded institutions' communication strategies. However, it was being used, and it did demonstrate new collaboration and authorship capabilities. Being generally aware of these capabilities may be useful to information professionals who seek to be current and informed regarding developing technology and to those interested in scholarly communication practices. In addition, the difficulties encountered during this case study in attempting to reach out to CTSA-minded institutions raised the question of how members currently communicate with each other as institutions and as individuals. There was a lesson learned in the usefulness of doing case-study research to evaluate new technologies; the cost in terms of time was relatively low, and knowledge about the technology itself was gained while establishing a base level of evidence to potentially build on in the future.
PMCID: PMC3068201  PMID: 21461135
6.  The IGOR Cloud Platform: Collaborative, Scalable, and Peer-Reviewed NGS Data Analysis 
Technical challenges facing researchers performing next-generation sequencing (NGS) analysis threaten to slow the pace of discovery and delay clinical applications of genomics data. Particularly for core laboratories, these challenges include: (1) Computation and storage have to scale with the vase amount of data generated. (2) Analysis pipelines are complex to design, set up, and share. (3) Collaboration, reproducibility, and sharing are hampered by privacy concerns and the sheer volume of data involved. Based on hands-on experience from large-scale NGS projects such as the 1000 Genomes Project, Seven Bridges Genomics has developed IGOR, a comprehensive cloud platform for NGS Data analysis that fully addresses these challenges: IGOR is a cloud-based platform for researchers and facilities to manage NGS data, design and run complex analysis pipelines, and efficiently collaborate on projects.Over a dozen curated and peer-reviewed NGS data analysis pipelines are publicly available for free, including alignment, variant calling, and RNA-Seq. All pipelines are based on open source tools and built to peer-reviewed specifications in close collaboration with researchers at leading institutions such as the Harvard Stem Cell Institute.Without any command-line knowledge, NGS pipelines can be built and customized in an intuitive graphical editor choosing from over 50 open source tools.When executing pipelines, IGOR automatically takes care of all resource management. Resources are seamlessly and automatically made available from Amazon Web Services and optimized for time and cost.Collaboration is facilitated through a project structure that allows researchers working in and across institutions to share files and pipelines. Fine-grained permissions allow detailed access control on a user-by-user basis for each project. Pipelines can be embedded and accessed through web pages akin to YouTube videos.Extensive batch processing and parallelization capabilities mean that hundreds of samples can be analyzed in the same amount of time that a single sample can be processed. Using file metadata, batch processing can be automated, e.g., by file, library, sample or lane.
The IGOR platform enables NGS research as a “turnkey” solution: Researchers can set up and run complex pipelines without expertise in command-line utilities or cloud computing. From a lab and facility perspective, the cloud-based architecture also eliminates the need to set up and maintain a large-scale infrastructure, typically resulting in at least 50% cost savings on infrastructure. By facilitating collaboration and easing analysis replication, the IGOR platform frees up the time of core laboratories to emphasize and focus on the research questions that ultimately guide them.
PMCID: PMC3635388
7.  Incorporating collaboratory concepts into informatics in support of translational interdisciplinary biomedical research 
Due to its complex nature, modern biomedical research has become increasingly interdisciplinary and collaborative in nature. Although a necessity, interdisciplinary biomedical collaboration is difficult. There is, however, a growing body of literature on the study and fostering of collaboration in fields such as computer supported cooperative work (CSCW) and information science (IS). These studies of collaboration provide insight into how to potentially alleviate the difficulties of interdisciplinary collaborative research. We, therefore, undertook a cross cutting study of science and engineering collaboratories to identify emergent themes. We review many relevant collaboratory concepts: (a) general collaboratory concepts across many domains: communication, common workspace and coordination, and data sharing and management, (b) specific collaboratory concepts of particular biomedical relevance: data integration and analysis, security structure, metadata and data provenance, and interoperability and data standards, (c) environmental factors that support collaboratories: administrative and management structure, technical support, and available funding as critical environmental factors, and (d) future considerations for biomedical collaboration: appropriate training and long-term planning. In our opinion, the collaboratory concepts we discuss can guide planning and design of future collaborative infrastructure by biomedical informatics researchers to alleviate some of the difficulties of interdisciplinary biomedical collaboration.
doi:10.1016/j.ijmedinf.2008.06.011
PMCID: PMC2606933  PMID: 18706852
Collaboration; Biomedical informatics; Computer supported collaborative work; Collaboratories; Social and technical issues; Bioinformatics
8.  Data harmonization and federated analysis of population-based studies: the BioSHaRE project 
Abstracts
Background
Individual-level data pooling of large population-based studies across research centres in international research projects faces many hurdles. The BioSHaRE (Biobank Standardisation and Harmonisation for Research Excellence in the European Union) project aims to address these issues by building a collaborative group of investigators and developing tools for data harmonization, database integration and federated data analyses.
Methods
Eight population-based studies in six European countries were recruited to participate in the BioSHaRE project. Through workshops, teleconferences and electronic communications, participating investigators identified a set of 96 variables targeted for harmonization to answer research questions of interest. Using each study’s questionnaires, standard operating procedures, and data dictionaries, harmonization potential was assessed. Whenever harmonization was deemed possible, processing algorithms were developed and implemented in an open-source software infrastructure to transform study-specific data into the target (i.e. harmonized) format. Harmonized datasets located on server in each research centres across Europe were interconnected through a federated database system to perform statistical analysis.
Results
Retrospective harmonization led to the generation of common format variables for 73% of matches considered (96 targeted variables across 8 studies). Authenticated investigators can now perform complex statistical analyses of harmonized datasets stored on distributed servers without actually sharing individual-level data using the DataSHIELD method.
Conclusion
New Internet-based networking technologies and database management systems are providing the means to support collaborative, multi-center research in an efficient and secure manner. The results from this pilot project show that, given a strong collaborative relationship between participating studies, it is possible to seamlessly co-analyse internationally harmonized research databases while allowing each study to retain full control over individual-level data. We encourage additional collaborative research networks in epidemiology, public health, and the social sciences to make use of the open source tools presented herein.
doi:10.1186/1742-7622-10-12
PMCID: PMC4175511  PMID: 24257327
9.  How can scientists bring research to use: the HENVINET experience 
Environmental Health  2012;11(Suppl 1):S2.
Background
Health concerns have driven the European environmental policies of the last 25 years, with issues becoming more complex. Addressing these concerns requires an approach that is both interdisciplinary and engages scientists with society. In response to this requirement, the FP6 coordination action “Health and Environment Network” HENVINET was set up to create a permanent inter-disciplinary network of professionals in the field of health and environment tasked to bridge the communication gap between science and society. In this paper we describe how HENVINET delivered on this task.
Methods
The HENVINET project approached the issue of inter-disciplinary collaboration in four ways. (1) The Drivers-Pressures-State-Exposure-Effect-Action framework was used to structure information gathering, collaboration and communication between scientists in the field of health and the environment. (2) Interactive web-based tools were developed to enhance methods for knowledge evaluation, and use these methods to formulate policy advice. (3) Quantification methods were adapted to measure scientific agreement. And (4) Open architecture web technology was used to develop an information repository and a web portal to facilitate collaboration and communication among scientists.
Results
Twenty-five organizations from Europe and five from outside Europe participated in the Health and Environment Network HENVINET, which lasted for 3.5 years. The consortium included partners in environmental research, public health and veterinary medicine; included medical practitioners and representatives of local administrations; and had access to national policy making and EEA and WHO expertise. Dedicated web-based tools for visualisation of environmental health issues and knowledge evaluation allowed remote expert elicitation, and were used as a basis for developing policy advice in five health areas (asthma and allergies; cancer; neurodevelopmental disorders; endocrine disruption; and engineered nanoparticles in the environment). An open searchable database of decision support tools was established and populated. A web based social networking tool was developed to enhance collaboration and communication between scientists and society.
Conclusions
HENVINET addressed key issues that arise in inter-disciplinary research on health and environment and in communicating research results to policy makers and society. HENVINET went beyond traditional scientific tools and methods to bridge the communication gap between science and policy makers. The project identified the need for a common framework and delivered it. It developed and implemented a variety of novel methods and tools and, using several representative examples, demonstrated the process of producing politically relevant scientific advice based on an open participation of experts. It highlighted the need for, and benefits of, a liaison between health and environment professionals and professionals in the social sciences and liberal arts. By adopting critical complexity thinking, HENVINET extended the traditional approach to environment and health research, and set the standard for current approaches to bridge the gap between science and society.
doi:10.1186/1476-069X-11-S1-S2
PMCID: PMC3388450  PMID: 22759502
10.  Guidelines, Editors, Pharma And The Biological Paradigm Shift 
Mens Sana Monographs  2007;5(1):27-30.
Private investment in biomedical research has increased over the last few decades. At most places it has been welcomed as the next best thing to technology itself. Much of the intellectual talent from academic institutions is getting absorbed in lucrative positions in industry. Applied research finds willing collaborators in venture capital funded industry, so a symbiotic growth is ensured for both.
There are significant costs involved too. As academia interacts with industry, major areas of conflict of interest especially applicable to biomedical research have arisen. They are related to disputes over patents and royalty, hostile encounters between academia and industry, as also between public and private enterprise, legal tangles, research misconduct of various types, antagonistic press and patient-advocate lobbies and a general atmosphere in which commercial interest get precedence over patient welfare.
Pharma image stinks because of a number of errors of omission and commission. A recent example is suppression of negative findings about Bayer's Trasylol (Aprotinin) and the marketing maneuvers of Eli Lilly's Xigris (rhAPC). Whenever there is a conflict between patient vulnerability and profit motives, pharma often tends to tilt towards the latter. Moreover there are documents that bring to light how companies frequently cross the line between patient welfare and profit seeking behaviour.
A voluntary moratorium over pharma spending to pamper drug prescribers is necessary. A code of conduct adopted recently by OPPI in India to limit pharma company expenses over junkets and trinkets is a welcome step.
Clinical practice guidelines (CPG) are considered important as they guide the diagnostic/therapeutic regimen of a large number of medical professionals and hospitals and provide recommendations on drugs, their dosages and criteria for selection. Along with clinical trials, they are another area of growing influence by the pharmaceutical industry. For example, in a relatively recent survey of 2002, it was found that about 60% of 192 authors of clinical practice guidelines reported they had financial connections with the companies whose drugs were under consideration. There is a strong case for making CPGs based not just on effectivity but cost effectivity. The various ramifications of this need to be spelt out. Work of bodies like the Appraisal of Guidelines Research and Evaluation (AGREE) Collaboration and Guidelines Advisory Committee (GAC) are also worth a close look.
Even the actions of Foundations that work for disease amelioration have come under scrutiny. The process of setting up ‘Best Practices’ Guidelines for interactions between the pharmaceutical industry and clinicians has already begun and can have important consequences for patient care. Similarly, Good Publication Practice (GPP) for pharmaceutical companies have also been set up aimed at improving the behaviour of drug companies while reporting drug trials
The rapidly increasing trend toward influence and control by industry has become a concern for many. It is of such importance that the Association of American Medical Colleges has issued two relatively new documents - one, in 2001, on how to deal with individual conflicts of interest; and the other, in 2002, on how to deal with institutional conflicts of interest in the conduct of clinical research. Academic Medical Centers (AMCs), as also medical education and research institutions at other places, have to adopt means that minimize their conflicts of interest.
Both medical associations and research journal editors are getting concerned with individual and institutional conflicts of interest in the conduct of clinical research and documents are now available which address these issues. The 2001 ICMJE revision calls for full disclosure of the sponsor's role in research, as well as assurance that the investigators are independent of the sponsor, are fully accountable for the design and conduct of the trial, have independent access to all trial data and control all editorial and publication decisions. However the findings of a 2002 study suggest that academic institutions routinely participate in clinical research that does not adhere to ICMJE standards of accountability, access to data and control of publication.
There is an inevitable slant to produce not necessarily useful but marketable products which ensure the profitability of industry and research grants outflow to academia. Industry supports new, not traditional, therapies, irrespective of what is effective. Whatever traditional therapy is supported is most probably because the company concerned has a product with a big stake there, which has remained a ‘gold standard’ or which that player thinks has still some ‘juice’ left.
Industry sponsorship is mainly for potential medications, not for trying to determine whether there may be non-pharmacological interventions that may be equally good, if not better. In the paradigm shift towards biological psychiatry, the role of industry sponsorship is not overt but probably more pervasive than many have realised, or the right thinking may consider good, for the health of the branch in the long run.
An issue of major concern is protection of the interests of research subjects. Patients agree to become research subjects not only for personal medical benefit but, as an extension, to benefit the rest of the patient population and also advance medical research.
We all accept that industry profits have to be made, and investment in research and development by the pharma industry is massive. However, we must also accept there is a fundamental difference between marketing strategies for other entities and those for drugs.
The ultimate barometer is patient welfare and no drug that compromises it can stand the test of time. So, how does it make even commercial sense in the long term to market substandard products? The greatest mistake long-term players in industry may make is try to adopt the shady techniques of the upstart new entrant. Secrecy of marketing/sales tactics, of the process of manufacture, of other strategies and plans of business expansion, of strategies to tackle competition are fine business tactics. But it is critical that secrecy as a tactic not extend to reporting of research findings, especially those contrary to one's product.
Pharma has no option but to make a quality product, do comprehensive adverse reaction profiles, and market it only if it passes both tests.
Why does pharma adopt questionable tactics? The reasons are essentially two:
What with all the constraints, a drug comes to the pharmacy after huge investments. There are crippling overheads and infrastructure costs to be recovered. And there are massive profit margins to be maintained. If these were to be dependent only on genuine drug discoveries, that would be taking too great a risk.Industry players have to strike the right balance between profit making and credibility. In profit making, the marketing champions play their role. In credibility ratings, researchers and paid spokes-persons play their role. All is hunky dory till marketing is based on credibility. When there is nothing available to make for credibility, something is projected as one and marketing carried out, in the calculated hope that profits can accrue, since profit making must continue endlessly. That is what makes pharma adopt even questionable means to make profits.
Essentially, there are four types of drugs. First, drugs that work and have minimal side-effects; second, drugs which work but have serious side-effects; third, drugs that do not work and have minimal side-effects; and fourth, drugs which work minimally but have serious side-effects. It is the second and fourth types that create major hassles for industry. Often, industry may try to project the fourth type as the second to escape censure.
The major cat and mouse game being played by conscientious researchers is in exposing the third and fourth for what they are and not allowing industry to palm them off as the first and second type respectively. The other major game is in preventing the second type from being projected as the first. The third type are essentially harmless, so they attract censure all right and some merriment at the antics to market them. But they escape anything more than a light rap on the knuckles, except when they are projected as the first type.
What is necessary for industry captains and long-term players is to realise:
Their major propelling force can only be producing the first type. 2. They accept the second type only till they can lay their hands on the first. 3. The third type can be occasionally played around with to shore up profits, but never by projecting them as the first type. 4. The fourth type are the laggards, real threat to credibility and therefore do not deserve any market hype or promotion.
In finding out why most pharma indulges in questionable tactics, we are lead to some interesting solutions to prevent such tactics with the least amount of hassles for all concerned, even as both profits and credibility are kept intact.
doi:10.4103/0973-1229.32176
PMCID: PMC3192391  PMID: 22058616
Academia; Pharmaceutical Industry; Clinical Practice Guidelines; Best Practice Guidelines; Academic Medical Centers; Medical Associations; Research Journals; Clinical Research; Public Welfare; Pharma Image; Corporate Welfare; Biological Psychiatry; Law Suits Against Industry
11.  Synergizing expectation and execution for stroke communities of practice innovations 
Background
Regional networks have been recognized as an interesting model to support interdisciplinary and inter-organizational interactions that lead to meaningful care improvements. Existing communities of practice within the a regional network, the Montreal Stroke Network (MSN) offers a compelling structure to better manage the exponential growth of knowledge and to support care providers to better manage the complex cases they must deal with in their practices. This research project proposes to examine internal and external factors that influence individual and organisational readiness to adopt national stroke best practices and to assess the impact of an e-collaborative platform in facilitating knowledge translation activities.
Methods
We will develop an e-collaborative platform that will include various social networking and collaborative tools. We propose to create online brainstorming sessions ('jams') around each best practice recommendation. Jam postings will be analysed to identify emergent themes. Syntheses of these analyses will be provided to members to help them identify priority areas for practice change. Discussions will be moderated by clinical leaders, whose role will be to accelerate crystallizing of ideas around 'how to' implement selected best practices. All clinicians (~200) involved in stroke care among the MSN will be asked to participate. Activities during face-to-face meetings and on the e-collaborative platform will be documented. Content analysis of all activities will be performed using an observation grid that will use as outcome indicators key elements of communities of practice and of the knowledge creation cycle developed by Nonaka. Semi-structured interviews will be conducted among users of the e-collaborative platform to collect information on variables of the knowledge-to-action framework. All participants will be asked to complete three questionnaires: the typology questionnaire, which classifies individuals into one of four mutually exclusive categories of information seeking; the e-health state of readiness, which covers ten domains of the readiness to change; and a community of practice evaluation survey.
Summary
This project is expected to enhance our understanding of collaborative work across disciplines and organisations in accelerating implementation of best practices along the continuum of care, and how e-technologies influence access, sharing, creation, and application of knowledge.
doi:10.1186/1748-5908-5-44
PMCID: PMC2890694  PMID: 20529305
12.  PragmatiX: An Interactive Tool for Visualizing the Creation Process Behind Collaboratively Engineered Ontologies 
With the emergence of tools for collaborative ontology engineering, more and more data about the creation process behind collaborative construction of ontologies is becoming available. Today, collaborative ontology engineering tools such as Collaborative Protégé offer rich and structured logs of changes, thereby opening up new challenges and opportunities to study and analyze the creation of collaboratively constructed ontologies. While there exists a plethora of visualization tools for ontologies, they have primarily been built to visualize aspects of the final product (the ontology) and not the collaborative processes behind construction (e.g. the changes made by contributors over time). To the best of our knowledge, there exists no ontology visualization tool today that focuses primarily on visualizing the history behind collaboratively constructed ontologies. Since the ontology engineering processes can influence the quality of the final ontology, we believe that visualizing process data represents an important stepping-stone towards better understanding of managing the collaborative construction of ontologies in the future. In this application paper, we present a tool – PragmatiX – which taps into structured change logs provided by tools such as Collaborative Protégé to visualize various pragmatic aspects of collaborative ontology engineering. The tool is aimed at managers and leaders of collaborative ontology engineering projects to help them in monitoring progress, in exploring issues and problems, and in tracking quality-related issues such as overrides and coordination among contributors. The paper makes the following contributions: (i) we present PragmatiX, a tool for visualizing the creation process behind collaboratively constructed ontologies (ii) we illustrate the functionality and generality of the tool by applying it to structured logs of changes of two large collaborative ontology-engineering projects and (iii) we conduct a heuristic evaluation of the tool with domain experts to uncover early design challenges and opportunities for improvement. Finally, we hope that this work sparks a new line of research on visualization tools for collaborative ontology engineering projects.
doi:10.4018/jswis.2013010103
PMCID: PMC3901413  PMID: 24465189
Collaborative Ontology Engineering; pragmatic analysis; ontology monitoring; ontology engineering visualization; ontology evaluation; ontology tool
13.  Enriched biodiversity data as a resource and service 
Background: Recent years have seen a surge in projects that produce large volumes of structured, machine-readable biodiversity data. To make these data amenable to processing by generic, open source “data enrichment” workflows, they are increasingly being represented in a variety of standards-compliant interchange formats. Here, we report on an initiative in which software developers and taxonomists came together to address the challenges and highlight the opportunities in the enrichment of such biodiversity data by engaging in intensive, collaborative software development: The Biodiversity Data Enrichment Hackathon.
Results: The hackathon brought together 37 participants (including developers and taxonomists, i.e. scientific professionals that gather, identify, name and classify species) from 10 countries: Belgium, Bulgaria, Canada, Finland, Germany, Italy, the Netherlands, New Zealand, the UK, and the US. The participants brought expertise in processing structured data, text mining, development of ontologies, digital identification keys, geographic information systems, niche modeling, natural language processing, provenance annotation, semantic integration, taxonomic name resolution, web service interfaces, workflow tools and visualisation. Most use cases and exemplar data were provided by taxonomists.
One goal of the meeting was to facilitate re-use and enhancement of biodiversity knowledge by a broad range of stakeholders, such as taxonomists, systematists, ecologists, niche modelers, informaticians and ontologists. The suggested use cases resulted in nine breakout groups addressing three main themes: i) mobilising heritage biodiversity knowledge; ii) formalising and linking concepts; and iii) addressing interoperability between service platforms. Another goal was to further foster a community of experts in biodiversity informatics and to build human links between research projects and institutions, in response to recent calls to further such integration in this research domain.
Conclusions: Beyond deriving prototype solutions for each use case, areas of inadequacy were discussed and are being pursued further. It was striking how many possible applications for biodiversity data there were and how quickly solutions could be put together when the normal constraints to collaboration were broken down for a week. Conversely, mobilising biodiversity knowledge from their silos in heritage literature and natural history collections will continue to require formalisation of the concepts (and the links between them) that define the research domain, as well as increased interoperability between the software platforms that operate on these concepts.
doi:10.3897/BDJ.2.e1125
PMCID: PMC4092319  PMID: 25057255
Biodiversity informatics; Data enrichment; Hackathon; Intelligent openness; Linked data; Open source; Software; Semantic Web; Taxonomy; Web services
14.  Accelerating Cancer Systems Biology Research through Semantic Web Technology 
Cancer systems biology is an interdisciplinary, rapidly expanding research field in which collaborations are a critical means to advance the field. Yet the prevalent database technologies often isolate data rather than making it easily accessible. The Semantic Web has the potential to help facilitate web-based collaborative cancer research by presenting data in a manner that is self-descriptive, human and machine readable, and easily sharable. We have created a semantically linked online Digital Model Repository (DMR) for storing, managing, executing, annotating, and sharing computational cancer models. Within the DMR, distributed, multidisciplinary, and inter-organizational teams can collaborate on projects, without forfeiting intellectual property. This is achieved by the introduction of a new stakeholder to the collaboration workflow, the institutional licensing officer, part of the Technology Transfer Office. Furthermore, the DMR has achieved silver level compatibility with the National Cancer Institute’s caBIG®, so users can not only interact with the DMR through a web browser but also through a semantically annotated and secure web service. We also discuss the technology behind the DMR leveraging the Semantic Web, ontologies, and grid computing to provide secure inter-institutional collaboration on cancer modeling projects, online grid-based execution of shared models, and the collaboration workflow protecting researchers’ intellectual property.
doi:10.1002/wsbm.1200
PMCID: PMC3558557  PMID: 23188758
Cancer modeling; model repository; oncology; Semantic Web; systems biology
15.  C-ME: A 3D Community-Based, Real-Time Collaboration Tool for Scientific Research and Training 
PLoS ONE  2008;3(2):e1621.
The need for effective collaboration tools is growing as multidisciplinary proteome-wide projects and distributed research teams become more common. The resulting data is often quite disparate, stored in separate locations, and not contextually related. Collaborative Molecular Modeling Environment (C-ME) is an interactive community-based collaboration system that allows researchers to organize information, visualize data on a two-dimensional (2-D) or three-dimensional (3-D) basis, and share and manage that information with collaborators in real time. C-ME stores the information in industry-standard databases that are immediately accessible by appropriate permission within the computer network directory service or anonymously across the internet through the C-ME application or through a web browser. The system addresses two important aspects of collaboration: context and information management. C-ME allows a researcher to use a 3-D atomic structure model or a 2-D image as a contextual basis on which to attach and share annotations to specific atoms or molecules or to specific regions of a 2-D image. These annotations provide additional information about the atomic structure or image data that can then be evaluated, amended or added to by other project members.
doi:10.1371/journal.pone.0001621
PMCID: PMC2229842  PMID: 18286178
16.  A digital repository with an extensible data model for biobanking and genomic analysis management 
BMC Genomics  2014;15(Suppl 3):S3.
Motivation
Molecular biology laboratories require extensive metadata to improve data collection and analysis. The heterogeneity of the collected metadata grows as research is evolving in to international multi-disciplinary collaborations and increasing data sharing among institutions. Single standardization is not feasible and it becomes crucial to develop digital repositories with flexible and extensible data models, as in the case of modern integrated biobanks management.
Results
We developed a novel data model in JSON format to describe heterogeneous data in a generic biomedical science scenario. The model is built on two hierarchical entities: processes and events, roughly corresponding to research studies and analysis steps within a single study. A number of sequential events can be grouped in a process building up a hierarchical structure to track patient and sample history. Each event can produce new data. Data is described by a set of user-defined metadata, and may have one or more associated files. We integrated the model in a web based digital repository with a data grid storage to manage large data sets located in geographically distinct areas. We built a graphical interface that allows authorized users to define new data types dynamically, according to their requirements. Operators compose queries on metadata fields using a flexible search interface and run them on the database and on the grid. We applied the digital repository to the integrated management of samples, patients and medical history in the BIT-Gaslini biobank. The platform currently manages 1800 samples of over 900 patients. Microarray data from 150 analyses are stored on the grid storage and replicated on two physical resources for preservation. The system is equipped with data integration capabilities with other biobanks for worldwide information sharing.
Conclusions
Our data model enables users to continuously define flexible, ad hoc, and loosely structured metadata, for information sharing in specific research projects and purposes. This approach can improve sensitively interdisciplinary research collaboration and allows to track patients' clinical records, sample management information, and genomic data. The web interface allows the operators to easily manage, query, and annotate the files, without dealing with the technicalities of the data grid.
doi:10.1186/1471-2164-15-S3-S3
PMCID: PMC4083403  PMID: 25077808
17.  The RICORDO approach to semantic interoperability for biomedical data and models: strategy, standards and solutions 
BMC Research Notes  2011;4:313.
Background
The practice and research of medicine generates considerable quantities of data and model resources (DMRs). Although in principle biomedical resources are re-usable, in practice few can currently be shared. In particular, the clinical communities in physiology and pharmacology research, as well as medical education, (i.e. PPME communities) are facing considerable operational and technical obstacles in sharing data and models.
Findings
We outline the efforts of the PPME communities to achieve automated semantic interoperability for clinical resource documentation in collaboration with the RICORDO project. Current community practices in resource documentation and knowledge management are overviewed. Furthermore, requirements and improvements sought by the PPME communities to current documentation practices are discussed. The RICORDO plan and effort in creating a representational framework and associated open software toolkit for the automated management of PPME metadata resources is also described.
Conclusions
RICORDO is providing the PPME community with tools to effect, share and reason over clinical resource annotations. This work is contributing to the semantic interoperability of DMRs through ontology-based annotation by (i) supporting more effective navigation and re-use of clinical DMRs, as well as (ii) sustaining interoperability operations based on the criterion of biological similarity. Operations facilitated by RICORDO will range from automated dataset matching to model merging and managing complex simulation workflows. In effect, RICORDO is contributing to community standards for resource sharing and interoperability.
doi:10.1186/1756-0500-4-313
PMCID: PMC3192696  PMID: 21878109
18.  RMS: a platform for managing cross-disciplinary and multi-institutional research project collaboration 
Background
Cross-institutional cross-disciplinary collaboration has become a trend as researchers move toward building more productive and innovative teams for scientific research. Research collaboration is significantly changing the organizational structure and strategies used in the clinical and translational science domain. However, due to the obstacles of diverse administrative structures, differences in area of expertise, and communication barriers, establishing and managing a cross-institutional research project is still a challenging task. We address these challenges by creating an integrated informatics platform to reduce the barriers to biomedical research collaboration.
Results
The Request Management System (RMS) is an informatics infrastructure designed to transform a patchwork of expertise and resources into an integrated support network. The RMS facilitates investigators’ initiation of new collaborative projects and supports the management of the collaboration process. In RMS, experts and their knowledge areas are categorized and managed structurally to provide consistent service. A role-based collaborative workflow is tightly integrated with domain experts and services to streamline and monitor the life-cycle of a research project. The RMS has so far tracked over 1,500 investigators with over 4,800 tasks. The research network based on the data collected in RMS illustrated that the investigators’ collaborative projects increased close to 3 times from 2009 to 2012. Our experience with RMS indicates that the platform reduces barriers for cross-institutional collaboration of biomedical research projects.
Conclusion
Building a new generation of infrastructure to enhance cross-disciplinary and multi-institutional collaboration has become an important yet challenging task. In this paper, we share the experience of developing and utilizing a collaborative project management system. The results of this study demonstrate that a web-based integrated informatics platform can facilitate and increase research interactions among investigators.
doi:10.1186/s12911-014-0106-6
PMCID: PMC4264263  PMID: 25433526
Biomedical research; Organization & administration; Research collaboration; System design and development; Collaborative research; Communication networks; Systems integration; Data-driven analysis
19.  VAMPS: a website for visualization and analysis of microbial population structures 
BMC Bioinformatics  2014;15:41.
Background
The advent of next-generation DNA sequencing platforms has revolutionized molecular microbial ecology by making the detailed analysis of complex communities over time and space a tractable research pursuit for small research groups. However, the ability to generate 105–108 reads with relative ease brings with it many downstream complications. Beyond the computational resources and skills needed to process and analyze data, it is difficult to compare datasets in an intuitive and interactive manner that leads to hypothesis generation and testing.
Results
We developed the free web service VAMPS (Visualization and Analysis of Microbial Population Structures, http://vamps.mbl.edu) to address these challenges and to facilitate research by individuals or collaborating groups working on projects with large-scale sequencing data. Users can upload marker gene sequences and associated metadata; reads are quality filtered and assigned to both taxonomic structures and to taxonomy-independent clusters. A simple point-and-click interface allows users to select for analysis any combination of their own or their collaborators’ private data and data from public projects, filter these by their choice of taxonomic and/or abundance criteria, and then explore these data using a wide range of analytic methods and visualizations. Each result is extensively hyperlinked to other analysis and visualization options, promoting data exploration and leading to a greater understanding of data relationships.
Conclusions
VAMPS allows researchers using marker gene sequence data to analyze the diversity of microbial communities and the relationships between communities, to explore these analyses in an intuitive visual context, and to download data, results, and images for publication. VAMPS obviates the need for individual research groups to make the considerable investment in computational infrastructure and bioinformatic support otherwise necessary to process, analyze, and interpret massive amounts of next-generation sequence data. Any web-capable device can be used to upload, process, explore, and extract data and results from VAMPS. VAMPS encourages researchers to share sequence and metadata, and fosters collaboration between researchers of disparate biomes who recognize common patterns in shared data.
doi:10.1186/1471-2105-15-41
PMCID: PMC3922339  PMID: 24499292
Microbiome; Microbial ecology; Microbial diversity; Data visualization; Website; Bacteria; SSU rRNA; Next-generation sequencing
20.  Achieving Holistic Health for the Individual through Person-Centered Collaborative Care Supported by Informatics 
Objectives
This article seeks to describe the current state of informatics supported collaborative care and to point out areas of future research in this highly interdisciplinary field.
Methods
In this article, person-centered collaborative care is seen as a concept addressing both the provision of care over organizational borders between health and social care, and within care teams as well as the changed patient/client-care provider relationship characterized by increased patient/client involvement.
Results
From a health systems perspective, there are several attempts to describe the conceptual and theoretical basis for collaborative care indicating that agreement on core concepts and terminology is difficult. From an informatics perspective, focus is on standardization of clinical content models and terminology to achieve interoperability of information technology systems and to support standardized care pathways. Few examples look into how ad-hoc collaborative care processes can be supported using information technology and informatics standards. Nevertheless, promising examples do exist showing that integrational Information Communication Technology services can be supportive for collaborative care developments. However, the current landscape consists of many fragmented, often technology-driven eHealth solutions targeting specific diagnostic groups in geographically and/or organizationally restricted settings.
Conclusions
A systematic approach incorporating organizational, clinical, informatics and social science knowledge is needed to perform further research in areas such as virtual team partnerships, new paradigms of care delivery, data and knowledge management as well as its secure sharing. Also organizational and legal aspects need to be further researched in order to facilitate the coordinated provision of health and social care to citizens including self-management, utilizing informatics support in a societal context.
doi:10.4258/hir.2013.19.1.3
PMCID: PMC3633169  PMID: 23626912
Social Welfare; Health Information Management; Integrated Delivery of Health Care; Cooperative Behavior
21.  A self-updating road map of The Cancer Genome Atlas 
Bioinformatics  2013;29(10):1333-1340.
Motivation: Since 2011, The Cancer Genome Atlas’ (TCGA) files have been accessible through HTTP from a public site, creating entirely new possibilities for cancer informatics by enhancing data discovery and retrieval. Significantly, these enhancements enable the reporting of analysis results that can be fully traced to and reproduced using their source data. However, to realize this possibility, a continually updated road map of files in the TCGA is required. Creation of such a road map represents a significant data modeling challenge, due to the size and fluidity of this resource: each of the 33 cancer types is instantiated in only partially overlapping sets of analytical platforms, while the number of data files available doubles approximately every 7 months.
Results: We developed an engine to index and annotate the TCGA files, relying exclusively on third-generation web technologies (Web 3.0). Specifically, this engine uses JavaScript in conjunction with the World Wide Web Consortium’s (W3C) Resource Description Framework (RDF), and SPARQL, the query language for RDF, to capture metadata of files in the TCGA open-access HTTP directory. The resulting index may be queried using SPARQL, and enables file-level provenance annotations as well as discovery of arbitrary subsets of files, based on their metadata, using web standard languages. In turn, these abilities enhance the reproducibility and distribution of novel results delivered as elements of a web-based computational ecosystem. The development of the TCGA Roadmap engine was found to provide specific clues about how biomedical big data initiatives should be exposed as public resources for exploratory analysis, data mining and reproducible research. These specific design elements align with the concept of knowledge reengineering and represent a sharp departure from top-down approaches in grid initiatives such as CaBIG. They also present a much more interoperable and reproducible alternative to the still pervasive use of data portals.
Availability: A prepared dashboard, including links to source code and a SPARQL endpoint, is available at http://bit.ly/TCGARoadmap. A video tutorial is available at http://bit.ly/TCGARoadmapTutorial.
Contact: robbinsd@uab.edu
doi:10.1093/bioinformatics/btt141
PMCID: PMC3654710  PMID: 23595662
22.  Comparative Case Study of Two Biomedical Research Collaboratories 
Background
Working together efficiently and effectively presents a significant challenge in large-scale, complex, interdisciplinary research projects. Collaboratories are a nascent method to help meet this challenge. However, formal collaboratories in biomedical research centers are the exception rather than the rule.
Objective
The main purpose of this paper is to compare and describe two collaboratories that used off-the-shelf tools and relatively modest resources to support the scientific activity of two biomedical research centers. The two centers were the Great Lakes Regional Center for AIDS Research (HIV/AIDS Center) and the New York University Oral Cancer Research for Adolescent and Adult Health Promotion Center (Oral Cancer Center).
Methods
In each collaboratory, we used semistructured interviews, surveys, and contextual inquiry to assess user needs and define the technology requirements. We evaluated and selected commercial software applications by comparing their feature sets with requirements and then pilot-testing the applications. Local and remote support staff cooperated in the implementation and end user training for the collaborative tools. Collaboratory staff evaluated each implementation by analyzing utilization data, administering user surveys, and functioning as participant observers.
Results
The HIV/AIDS Center primarily required real-time interaction for developing projects and attracting new participants to the center; the Oral Cancer Center, on the other hand, mainly needed tools to support distributed and asynchronous work in small research groups. The HIV/AIDS Center’s collaboratory included a center-wide website that also served as the launch point for collaboratory applications, such as NetMeeting, Timbuktu Conference, PlaceWare Auditorium, and iVisit. The collaboratory of the Oral Cancer Center used Groove and Genesys Web conferencing. The HIV/AIDS Center was successful in attracting new scientists to HIV/AIDS research, and members used the collaboratory for developing and implementing new research studies. The Oral Cancer Center successfully supported highly distributed and asynchronous research, and the collaboratory facilitated real-time interaction for analyzing data and preparing publications.
Conclusions
The two collaboratory implementations demonstrated the feasibility of supporting biomedical research centers using off-the-shelf commercial tools, but they also identified several barriers to successful collaboration. These barriers included computing platform incompatibilities, network infrastructure complexity, variable availability of local versus remote IT support, low computer and collaborative software literacy, and insufficient maturity of available collaborative software. Factors enabling collaboratory use included collaboration incentives through funding mechanism, a collaborative versus competitive relationship of researchers, leadership by example, and tools well matched to tasks and technical progress. Integrating electronic collaborative tools into routine scientific practice can be successful but requires further research on the technical, social, and behavioral factors influencing the adoption and use of collaboratories.
doi:10.2196/jmir.7.5.e53
PMCID: PMC1408071  PMID: 16403717
Biomedical research; collaboration; collaboratories; community networks; information technology; interdisciplinary research
23.  The Project Data Sphere Initiative: Accelerating Cancer Research by Sharing Data 
The Oncologist  2015;20(5):464-e20.
By providing access to large, late-phase, cancer-trial data sets, the Project Data Sphere initiative has the potential to transform cancer research by optimizing research efficiency and accelerating progress toward meaningful improvements in cancer care. This type of platform provides opportunities for unique research projects that can examine relatively neglected areas and that can construct models necessitating large amounts of detailed data.
Background.
In this paper, we provide background and context regarding the potential for a new data-sharing platform, the Project Data Sphere (PDS) initiative, funded by financial and in-kind contributions from the CEO Roundtable on Cancer, to transform cancer research and improve patient outcomes. Given the relatively modest decline in cancer death rates over the past several years, a new research paradigm is needed to accelerate therapeutic approaches for oncologic diseases. Phase III clinical trials generate large volumes of potentially usable information, often on hundreds of patients, including patients treated with standard of care therapies (i.e., controls). Both nationally and internationally, a variety of stakeholders have pursued data-sharing efforts to make individual patient-level clinical trial data available to the scientific research community.
Potential Benefits and Risks of Data Sharing.
For researchers, shared data have the potential to foster a more collaborative environment, to answer research questions in a shorter time frame than traditional randomized control trials, to reduce duplication of effort, and to improve efficiency. For industry participants, use of trial data to answer additional clinical questions could increase research and development efficiency and guide future projects through validation of surrogate end points, development of prognostic or predictive models, selection of patients for phase II trials, stratification in phase III studies, and identification of patient subgroups for development of novel therapies. Data transparency also helps promote a public image of collaboration and altruism among industry participants. For patient participants, data sharing maximizes their contribution to public health and increases access to information that may be used to develop better treatments. Concerns about data-sharing efforts include protection of patient privacy and confidentiality. To alleviate these concerns, data sets are deidentified to maintain anonymity. To address industry concerns about protection of intellectual property and competitiveness, we illustrate several models for data sharing with varying levels of access to the data and varying relationships between trial sponsors and data access sponsors.
The Project Data Sphere Initiative.
PDS is an independent initiative of the CEO Roundtable on Cancer Life Sciences Consortium, built to voluntarily share, integrate, and analyze comparator arms of historical cancer clinical trial data sets to advance future cancer research. The aim is to provide a neutral, broad-access platform for industry and academia to share raw, deidentified data from late-phase oncology clinical trials using comparator-arm data sets. These data are likely to be hypothesis generating or hypothesis confirming but, notably, do not take the place of performing a well-designed trial to address a specific hypothesis. Prospective providers of data to PDS complete and sign a data sharing agreement that includes a description of the data they propose to upload, and then they follow easy instructions on the website for uploading their deidentified data. The SAS Institute has also collaborated with the initiative to provide intrinsic analytic tools accessible within the website itself.
As of October 2014, the PDS website has available data from 14 cancer clinical trials covering 9,000 subjects, with hopes to further expand the database to include more than 25,000 subject accruals within the next year. PDS differentiates itself from other data-sharing initiatives by its degree of openness, requiring submission of only a brief application with background information of the individual requesting access and agreement to terms of use. Data from several different sponsors may be pooled to develop a comprehensive cohort for analysis. In order to protect patient privacy, data providers in the U.S. are responsible for deidentifying data according to standards set forth by the Privacy Rule of the U.S. Health Insurance Portability and Accountability Act of 1996.
Using Data Sharing to Improve Outcomes in Cancer: The “Prostate Cancer Challenge.”
Control-arm data of several studies among patients with metastatic castration-resistant prostate cancer (mCRPC) are currently available through PDS. These data sets have multiple potential uses. The “Prostate Cancer Challenge” will ask the cancer research community to use clinical trial data deposited in the PDS website to address key research questions regarding mCRPC.
General themes that could be explored by the cancer community are described in this article: prognostic models evaluating the influence of pretreatment factors on survival and patient-reported outcomes; comparative effectiveness research evaluating the efficacy of standard of care therapies, as illustrated in our companion article comparing mitoxantrone plus prednisone with prednisone alone; effects of practice variation in dose, frequency, and duration of therapy; level of patient adherence to elements of trial protocols to inform the design of future clinical trials; and age of subjects, regional differences in health care, and other confounding factors that might affect outcomes.
Potential Limitations and Methodological Challenges.
The number of data sets available and the lack of experimental-arm data limit the potential scope of research using the current PDS. The number of trials is expected to grow exponentially over the next year and may include multiple cancer settings, such as breast, colorectal, lung, hematologic malignancy, and bone marrow transplantation. Other potential limitations include the retrospective nature of the data analyses performed using PDS and its generalizability, given that clinical trials are often conducted among younger, healthier, and less racially diverse patient populations. Methodological challenges exist when combining individual patient data from multiple clinical trials; however, advancements in statistical methods for secondary database analysis offer many tools for reanalyzing data arising from disparate trials, such as propensity score matching. Despite these concerns, few if any comparable data sets include this level of detail across multiple clinical trials and populations.
Conclusion.
Access to large, late-phase, cancer-trial data sets has the potential to transform cancer research by optimizing research efficiency and accelerating progress toward meaningful improvements in cancer care. This type of platform provides opportunities for unique research projects that can examine relatively neglected areas and that can construct models necessitating large amounts of detailed data. The full potential of PDS will be realized only when multiple tumor types and larger numbers of data sets are available through the website.
doi:10.1634/theoncologist.2014-0431
PMCID: PMC4425388  PMID: 25876994
Project Data Sphere; Data sharing; Prostate cancer; Comparative effectiveness research
24.  SOMWeb: A Semantic Web-Based System for Supporting Collaboration of Distributed Medical Communities of Practice 
Background
Information technology (IT) support for remote collaboration of geographically distributed communities of practice (CoP) in health care must deal with a number of sociotechnical aspects of communication within the community. In the mid-1990s, participants of the Swedish Oral Medicine Network (SOMNet) began discussing patient cases in telephone conferences. The cases were distributed prior to the conferences using PowerPoint and email. For the technical support of online CoP, Semantic Web technologies can potentially fulfill needs of knowledge reuse, data exchange, and reasoning based on ontologies. However, more research is needed on the use of Semantic Web technologies in practice.
Objectives
The objectives of this research were to (1) study the communication of distributed health care professionals in oral medicine; (2) apply Semantic Web technologies to describe community data and oral medicine knowledge; (3) develop an online CoP, Swedish Oral Medicine Web (SOMWeb), centered on user-contributed case descriptions and meetings; and (4) evaluate SOMWeb and study how work practices change with IT support.
Methods
Based on Java, and using the Web Ontology Language and Resource Description Framework for handling community data and oral medicine knowledge, SOMWeb was developed using a user-centered and iterative approach. For studying the work practices and evaluating the system, a mixed-method approach of interviews, observations, and a questionnaire was used.
Results
By May 2008, there were 90 registered users of SOMWeb, 93 cases had been added, and 18 meetings had utilized the system. The introduction of SOMWeb has improved the structure of meetings and their discussions, and a tenfold increase in the number of participants has been observed. Users submit cases to seek advice on diagnosis or treatment, to show an unusual case, or to create discussion. Identified barriers to submitting cases are lack of time, concern about whether the case is interesting enough, and showing gaps in one’s own knowledge. Three levels of member participation are discernable: a core group that contributes most cases and most meeting feedback; an active group that participates often but only sometimes contribute cases and feedback; and a large peripheral group that seldom or never contribute cases or feedback.
Conclusions
SOMWeb is beneficial for individual clinicians as well as for the SOMNet community. The system provides an opportunity for its members to share both high quality clinical practice knowledge and external evidence related to complex oral medicine cases. The foundation in Semantic Web technologies enables formalization and structuring of case data that can be used for further reasoning and research. Main success factors are the long history of collaboration between different disciplines, the user-centered development approach, the existence of a “champion” within the field, and nontechnical community aspects already being in place.
doi:10.2196/jmir.1059
PMCID: PMC2626431  PMID: 18725355
Dental informatics; medical informatics applications; communications applications; community networks; group and organization interfaces; interdisciplinary communication; Internet; knowledge bases; online information services; user/machine systems
25.  A repository based on a dynamically extensible data model supporting multidisciplinary research in neuroscience 
Background
Robust, extensible and distributed databases integrating clinical, imaging and molecular data represent a substantial challenge for modern neuroscience. It is even more difficult to provide extensible software environments able to effectively target the rapidly changing data requirements and structures of research experiments. There is an increasing request from the neuroscience community for software tools addressing technical challenges about: (i) supporting researchers in the medical field to carry out data analysis using integrated bioinformatics services and tools; (ii) handling multimodal/multiscale data and metadata, enabling the injection of several different data types according to structured schemas; (iii) providing high extensibility, in order to address different requirements deriving from a large variety of applications simply through a user runtime configuration.
Methods
A dynamically extensible data structure supporting collaborative multidisciplinary research projects in neuroscience has been defined and implemented. We have considered extensibility issues from two different points of view. First, the improvement of data flexibility has been taken into account. This has been done through the development of a methodology for the dynamic creation and use of data types and related metadata, based on the definition of “meta” data model. This way, users are not constrainted to a set of predefined data and the model can be easily extensible and applicable to different contexts. Second, users have been enabled to easily customize and extend the experimental procedures in order to track each step of acquisition or analysis. This has been achieved through a process-event data structure, a multipurpose taxonomic schema composed by two generic main objects: events and processes. Then, a repository has been built based on such data model and structure, and deployed on distributed resources thanks to a Grid-based approach. Finally, data integration aspects have been addressed by providing the repository application with an efficient dynamic interface designed to enable the user to both easily query the data depending on defined datatypes and view all the data of every patient in an integrated and simple way.
Results
The results of our work have been twofold. First, a dynamically extensible data model has been implemented and tested based on a “meta” data-model enabling users to define their own data types independently from the application context. This data model has allowed users to dynamically include additional data types without the need of rebuilding the underlying database. Then a complex process-event data structure has been built, based on this data model, describing patient-centered diagnostic processes and merging information from data and metadata. Second, a repository implementing such a data structure has been deployed on a distributed Data Grid in order to provide scalability both in terms of data input and data storage and to exploit distributed data and computational approaches in order to share resources more efficiently. Moreover, data managing has been made possible through a friendly web interface. The driving principle of not being forced to preconfigured data types has been satisfied. It is up to users to dynamically configure the data model for the given experiment or data acquisition program, thus making it potentially suitable for customized applications.
Conclusions
Based on such repository, data managing has been made possible through a friendly web interface. The driving principle of not being forced to preconfigured data types has been satisfied. It is up to users to dynamically configure the data model for the given experiment or data acquisition program, thus making it potentially suitable for customized applications.
doi:10.1186/1472-6947-12-115
PMCID: PMC3560115  PMID: 23043673
Neuroscience; Data models; Multidisciplinary studies

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