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1.  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.
PMCID: PMC2606933  PMID: 18706852
Collaboration; Biomedical informatics; Computer supported collaborative work; Collaboratories; Social and technical issues; Bioinformatics
2.  A suite of web applications to streamline the interdisciplinary collaboration in secondary data analyses 
We describe a system of web applications designed to streamline the interdisciplinary collaboration in outcomes research.
The outcomes research process can be described as a set of three interrelated phases: design and selection of data sources, analysis, and output. Each of these phases has inherent challenges that can be addressed by a group of five web applications developed by our group. QuestForm allows for the formulation of relevant and well-structured outcomes research questions; Research Manager facilitates the project management and electronic file exchange among researchers; Analysis Charts facilitate the communication of complex statistical techniques to clinicians with varying previous levels of statistical knowledge; Literature Matrices improve the efficiency of literature reviews. An outcomes research question is used to illustrate the use of the system.
The system presents an alternative to streamline the interdisciplinary collaboration of clinicians, statisticians, programmers, and graduate students.
PMCID: PMC544191  PMID: 15596017
biomedical research; statistical data interpretation; research design; planning techniques; Internet; computer-assisted instruction
3.  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.
PMCID: PMC2229842  PMID: 18286178
4.  Understanding life together: A brief history of collaboration in biology 
Endeavour  2013;37(3):162-171.
The history of science shows a shift from single-investigator ‘little science’ to increasingly large, expensive, multinational, interdisciplinary and interdependent ‘big science’. In physics and allied fields this shift has been well documented, but the rise of collaboration in the life sciences and its effect on scientific work and knowledge has received little attention. Research in biology exhibits different historical trajectories and organisation of collaboration in field and laboratory – differences still visible in contemporary collaborations such as the Census of Marine Life and the Human Genome Project. We employ these case studies as strategic exemplars, supplemented with existing research on collaboration in biology, to expose the different motives, organisational forms and social dynamics underpinning contemporary large-scale collaborations in biology and their relations to historical patterns of collaboration in the life sciences. We find the interaction between research subject, research approach as well as research organisation influencing collaboration patterns and the work of scientists.
PMCID: PMC3878597  PMID: 23578694
5.  The RICORDO approach to semantic interoperability for biomedical data and models: strategy, standards and solutions 
BMC Research Notes  2011;4:313.
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.
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.
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.
PMCID: PMC3192696  PMID: 21878109
6.  The Collaboratory for MS3D: A New Cyberinfrastructure for the Structural Elucidation of Biological Macromolecules and their Assemblies Using Mass Spectrometry-based Approaches 
Journal of proteome research  2008;7(11):4848-4857.
Modern biomedical research is evolving with the rapid growth of diverse data types, biophysical characterization methods, computational tools and extensive collaboration among researchers spanning various communities and having complementary backgrounds and expertise. Collaborating researchers are increasingly dependent on shared data and tools made available by other investigators with common interests, thus forming communities that transcend the traditional boundaries of the single research lab or institution. Barriers, however, remain to the formation of these virtual communities, usually due to the steep learning curve associated with becoming familiar with new tools, or with the difficulties associated with transferring data between tools. Recognizing the need for shared reference data and analysis tools, we are developing an integrated knowledge environment that supports productive interactions among researchers. Here we report on our current collaborative environment, which focuses on bringing together structural biologists working in the area of mass spectrometric based methods for the analysis of tertiary and quaternary macromolecular structures (MS3D) called the Collaboratory for MS3D (C-MS3D). C-MS3D is a web-portal designed to provide collaborators with a shared work environment that integrates data storage and management with data analysis tools. Files are stored and archived along with pertinent meta data in such a way as to allow file handling to be tracked (data provenance) and data files to be searched using keywords and modification dates. While at this time the portal is designed around a specific application, the shared work environment is a general approach to building collaborative work groups. The goal of which is to not only provide a common data sharing and archiving system but also to assist in the building of new collaborations and to spur the development of new tools and technologies.
PMCID: PMC2677910  PMID: 18817429
Collaboratory; data analysis tools; structural biology; mass spectrometry
7.  Synergizing expectation and execution for stroke communities of practice innovations 
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.
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.
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.
PMCID: PMC2890694  PMID: 20529305
8.  Collaborative software for traditional and translational research 
Human Genomics  2012;6(1):21.
Biomedical research has entered a period of renewed vigor with the introduction and rapid development of genomic technologies and next-generation sequencing methods. This research paradigm produces extremely large datasets that are both difficult to store and challenging to mine for relevant data. Additionally, the thorough exploration of such datasets requires more resources, personnel, and multidisciplinary expertise to properly analyze and interpret the data. As a result, modern biomedical research practices are increasingly designed to include multi-laboratory collaborations that effectively distribute the scientific workload and expand the pool of expertise within a project. The scope of biomedical research is further complicated by increased efforts in translational research, which mandates the translation of basic laboratory research results into the human medical application space, adding to the complexity of potential collaborations. This increase in multidisciplinary, multi-laboratory, and biomedical translational research identifies a specific need for formalized collaboration practices and software applications that support such efforts. Here, we describe formal technological requirements for such efforts and we review several software solutions that can effectively improve the organization, communication, and formalization of collaborations in biomedical research today.
PMCID: PMC3500217  PMID: 23157911
9.  The BRIDG Project: A Technical Report 
The Biomedical Research Integrated Domain Group (BRIDG) project is a collaborative initiative between the National Cancer Institute (NCI), the Clinical Data Interchange Standards Consortium (CDISC), the Regulated Clinical Research Information Management Technical Committee (RCRIM TC) of Health Level 7 (HL7), and the Food and Drug Administration (FDA) to develop a model of the shared understanding of the semantics of clinical research.
The BRIDG project is based on open-source collaborative principles and an implementation-independent, use-case driven approach to model development. In the BRIDG model, declarative and procedural knowledge are represented using the Unified Modeling Language (UML) class, activity and state diagrams.
The BRIDG model currently contains harmonized semantics from four project use cases: the caXchange project and the patient study calendar project from caBIG™; the standard data tabular model (SDTM) from CDISC; and the regulated products submission model (RPS) from HL7. Scalable harmonization processes have been developed to expand the model with content from additional use cases.
The first official release of the BRIDG model was published in June 2007. Use of the BRIDG model by the NCI has supported the rapid development of semantic interoperability across applications within the caBIG™ program.
The BRIDG project has brought together different standards communities to clarify the semantics of clinical research across pharmaceutical, regulatory, and research organizations. Currently, the NCI uses the BRIDG model to support interoperable application development in the caBIG™, and CDISC and HL7 are using the BRIDG model to support standards development.
PMCID: PMC2274793  PMID: 18096907
10.  CIS8/469: Introduction of New Information and Communication Technology into the Workflow of General Practitioners - Examination of the consequences on the interaction between doctor and patient 
Since 1997 an interdisciplinary research project is taking place at the Heidelberg University clinics with the subject "Mobile communication tools at the clinical practice". It was focused mainly on the introduction of new technologies to support stationary as well as ambulant medical and nursing occupation. Within the frame of construction of new information systems at hospitals the research works concentrated on aspects as the access to data banks of medical knowledge, electronic file management, picture transmission and knowledge based decision support. In the field of interpersonal communication the use of mobile radio equipment for the duty in service was to the fore. One of the main questions concerns the forecast of psychosocial technical consequences.
The research on hand focuses on consequences of new luK-technologies on the interaction between doctor and patient on the field of the general practitioner. An IST-SOLL analyses was made among general practitioners, internists, paediatricians, dentists (N=48) and their patients (N=116) by means of half-structured interviews and questionnaires. With the instruments it was at first possible to make out a judgement of doctors and patients in view of their doctor-patient interaction and the actual technical status quo. In addition they inquired an assessment of the person what changes they would expect on the corresponding fields by the introduction of new technologies.
The results show that negative influences of new technologies on the doctor-patient interaction are expected by 18.5% of the questioned doctors and only 4.4% of the questioned patients. Doctors would approve the introduction of new technologies on condition that it would be user-friendly and that data protection, restriction to main functions as well as data exchange with clinics and other medical institutions would be guaranteed.
The results of the study are to be regarded as prognostics with regard to the development and introduction of new technologies. Statements will be possible in two areas:
Consequences on the contact between doctor and patient
Which innovations are regarded as useful by the doctors and which aspects should be taken into consideration in case of construction?
PMCID: PMC1761827
Integrated Advanced Information Management Systems; Physicians; Doctor-Patient-Interaction; IuK-Technologies
11.  TOLKIN – Tree of Life Knowledge and Information Network: Filling a Gap for Collaborative Research in Biological Systematics 
PLoS ONE  2012;7(6):e39352.
The development of biological informatics infrastructure capable of supporting growing data management and analysis environments is an increasing need within the systematics biology community. Although significant progress has been made in recent years on developing new algorithms and tools for analyzing and visualizing large phylogenetic data and trees, implementation of these resources is often carried out by bioinformatics experts, using one-off scripts. Therefore, a gap exists in providing data management support for a large set of non-technical users. The TOLKIN project (Tree of Life Knowledge and Information Network) addresses this need by supporting capabilities to manage, integrate, and provide public access to molecular, morphological, and biocollections data and research outcomes through a collaborative, web application. This data management framework allows aggregation and import of sequences, underlying documentation about their source, including vouchers, tissues, and DNA extraction. It combines features of LIMS and workflow environments by supporting management at the level of individual observations, sequences, and specimens, as well as assembly and versioning of data sets used in phylogenetic inference. As a web application, the system provides multi-user support that obviates current practices of sharing data sets as files or spreadsheets via email.
PMCID: PMC3377657  PMID: 22724002
12.  Facebook for Scientists: Requirements and Services for Optimizing How Scientific Collaborations Are Established 
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.
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?
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.
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.
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.
PMCID: PMC2553246  PMID: 18701421
Expertise locating systems; computer supported collaborative work; information systems; collaborators; research; social networks; translational research
13.  Wikis and Collaborative Writing Applications in Health Care: A Scoping Review Protocol 
JMIR Research Protocols  2012;1(1):e1.
The rapid rise in the use of collaborative writing applications (eg, wikis, Google Documents, and Google Knol) has created the need for a systematic synthesis of the evidence of their impact as knowledge translation (KT) tools in the health care sector and for an inventory of the factors that affect their use. While researchers have conducted systematic reviews on a range of software-based information and communication technologies as well as other social media (eg, virtual communities of practice, virtual peer-to-peer communities, and electronic support groups), none have reviewed collaborative writing applications in the medical sector. The overarching goal of this project is to explore the depth and breadth of evidence for the use of collaborative writing applications in health care. Thus, the purposes of this scoping review will be to (1) map the literature on collaborative writing applications; (2) compare the applications’ features; (3) describe the evidence of each application’s positive and negative effects as a KT intervention in health care; (4) inventory and describe the barriers and facilitators that affect the applications’ use; and (5) produce an action plan and a research agenda. A six-stage framework for scoping reviews will be used: (1) identifying the research question; (2) identifying relevant studies within the selected databases (using the EPPI-Reviewer software to classify the studies); (3) selecting studies (an iterative process in which two reviewers search the literature, refine the search strategy, and review articles for inclusion); (4) charting the data (using EPPI-Reviewer’s data-charting form); (5) collating, summarizing, and reporting the results (performing a descriptive, numerical, and interpretive synthesis); and (6) consulting knowledge users during three planned meetings. Since this scoping review concerns the use of collaborative writing applications as KT interventions in health care, we will use the Knowledge to Action (KTA) framework to describe and compare the various studies and collaborative writing projects we find. In addition to guiding the use of collaborative writing applications in health care, this scoping review will advance the science of KT by testing tools that could be used to evaluate other social media. We also expect to identify areas that require further systematic reviews and primary research and to produce a highly relevant research agenda that explores and leverages the potential of collaborative writing software. To date, this is the first study to use the KTA framework to study the role collaborative writing applications in KT, and the first to involve three national and international institutional knowledge users as part of the research process.
PMCID: PMC3626140  PMID: 23612481
14.  Addressing Health Disparities through Multi-institutional, Multidisciplinary Collaboratories 
Ethnicity & disease  2008;18(2 Suppl 2):S2-161-7.
The national research leadership has recently become aware of the tremendous potential of translational research as an approach to address health disparities. The Research Centers in Minority Institutions (RCMI) Translational Research Network (RTRN) is a research network that supports multi-institutional, multidisciplinary collaboration with a focus on key diseases and conditions for which disproportionately adverse racial and ethnic health disparities exist. The RTRN is designed to facilitate the movement of scientific advances across the translational research spectrum by providing researchers at different institutions with the infrastructure and tools necessary to collaborate on interdisciplinary and transdisciplinary research projects relating to specific health outcomes for which major racial/ethnic disparities exist. In the past, the difficulty of overcoming the restrictions imposed by time and space have made it difficult to carry out this type of large-scale, multilevel collaboration efficiently. To address this formidable challenge, the RTRN will deploy a translational research cluster system that uses “cyber workspaces” to bring researchers with similar interests together by using online collaboratory technology. These virtual meeting environments will provide a number of tools, including videoconferences (seminars, works in progress, meetings); project management tools (WebCT, Microsoft Share Point); and posting areas for projects, concepts, and other research and educational activities. This technology will help enhance access to resources across institutions with a common mission, minimize many of the logistical hurdles that impede intellectual exchange, streamline the planning and implementation of innovative interdisciplinary research, and assess the use of protocols and practices to assist researchers in interacting across and within cyber workspaces.
PMCID: PMC2705198  PMID: 18646341
Translational Research; Health Disparities; Conceptual Framework
15.  Qualitative Analysis of the Interdisciplinary Interaction between Data Analysis Specialists and Novice Clinical Researchers 
PLoS ONE  2010;5(2):e9400.
The inherent complexity of statistical methods and clinical phenomena compel researchers with diverse domains of expertise to work in interdisciplinary teams, where none of them have a complete knowledge in their counterpart's field. As a result, knowledge exchange may often be characterized by miscommunication leading to misinterpretation, ultimately resulting in errors in research and even clinical practice. Though communication has a central role in interdisciplinary collaboration and since miscommunication can have a negative impact on research processes, to the best of our knowledge, no study has yet explored how data analysis specialists and clinical researchers communicate over time.
Methods/Principal Findings
We conducted qualitative analysis of encounters between clinical researchers and data analysis specialists (epidemiologist, clinical epidemiologist, and data mining specialist). These encounters were recorded and systematically analyzed using a grounded theory methodology for extraction of emerging themes, followed by data triangulation and analysis of negative cases for validation. A policy analysis was then performed using a system dynamics methodology looking for potential interventions to improve this process. Four major emerging themes were found. Definitions using lay language were frequently employed as a way to bridge the language gap between the specialties. Thought experiments presented a series of “what if” situations that helped clarify how the method or information from the other field would behave, if exposed to alternative situations, ultimately aiding in explaining their main objective. Metaphors and analogies were used to translate concepts across fields, from the unfamiliar to the familiar. Prolepsis was used to anticipate study outcomes, thus helping specialists understand the current context based on an understanding of their final goal.
The communication between clinical researchers and data analysis specialists presents multiple challenges that can lead to errors.
PMCID: PMC2827555  PMID: 20195374
16.  Use of social network analysis tools to validate a resources infrastructure for interinstitutional translational research: a case study* 
How can knowledge management and innovative technology, cornerstones of library practice, be leveraged to validate the progress of Clinical and Translational Science Awards?
The Indiana Clinical and Translational Sciences Institute (Indiana CTSI) promotes interdisciplinary research across academic institutions.
Using social networking tools and knowledge management skills enabled the department of knowledge informatics and translation to create a visualization of utilization of resources across different Indiana CTSI programs and coauthorship and citation patterns.
Contacts with different resources per investigator increased; every targeted program was shown to be linked to another. Analysis of publications established a baseline to further analyze the scientific contribution of Indiana CTSI projects.
Knowledge management and social networking utilities validated the efficacy of the Indiana CTSI resources infrastructure and demonstrated visualization of collaboration. The bibliometric analysis of publications provides a basis for assessing longer-term contributions of support to scientific discovery and transdisciplinary science.
PMCID: PMC3257477  PMID: 22272159
17.  Informatics and Standards for Nanomedicine Technology 
There are several issues to be addressed concerning the management and effective use of information (or data), generated from nanotechnology studies in biomedical research and medicine. These data are large in volume, diverse in content, and are beset with gaps and ambiguities in the description and characterization of nanomaterials. In this work, we have reviewed three areas of nanomedicine informatics: information resources; taxonomies, controlled vocabularies, and ontologies; and information standards. Informatics methods and standards in each of these areas are critical for enabling collaboration, data sharing, unambiguous representation and interpretation of data, semantic (meaningful) search and integration of data; and for ensuring data quality, reliability, and reproducibility. In particular, we have considered four types of information standards in this review, which are standard characterization protocols, common terminology standards, minimum information standards, and standard data communication (exchange) formats. Currently, due to gaps and ambiguities in the data, it is also difficult to apply computational methods and machine learning techniques to analyze, interpret and recognize patterns in data that are high dimensional in nature, and also to relate variations in nanomaterial properties to variations in their chemical composition, synthesis, characterization protocols, etc. Progress towards resolving the issues of information management in nanomedicine using informatics methods and standards discussed in this review will be essential to the rapidly growing field of nanomedicine informatics.
PMCID: PMC3189420  PMID: 21721140
18.  Life Sciences and the web: a new era for collaboration 
The World Wide Web has revolutionized how researchers from various disciplines collaborate over long distances. This is nowhere more important than in the Life Sciences, where interdisciplinary approaches are becoming increasingly powerful as a driver of both integration and discovery. Data access, data quality, identity, and provenance are all critical ingredients to facilitate and accelerate these collaborative enterprises and it is here where Semantic Web technologies promise to have a profound impact. This paper reviews the need for, and explores advantages of as well as challenges with these novel Internet information tools as illustrated with examples from the biomedical community.
PMCID: PMC2516361  PMID: 18594519
AJAX; OWL; RDF; Semantic Web; SPARQL; Web 2.0
19.  Social media use among patients and caregivers: a scoping review 
BMJ Open  2013;3(5):e002819.
To map the state of the existing literature evaluating the use of social media in patient and caregiver populations.
Scoping review.
Data sources
Medline, CENTRAL, ERIC, PubMed, CINAHL Plus Full Text, Academic Search Complete, Alt Health Watch, Health Source, Communication and Mass Media Complete, Web of Knowledge and ProQuest (2000–2012).
Study selection
Studies reporting primary research on the use of social media (collaborative projects, blogs/microblogs, content communities, social networking sites, virtual worlds) by patients or caregivers.
Data extraction
Two reviewers screened studies for eligibility; one reviewer extracted data from relevant studies and a second performed verification for accuracy and completeness on a 10% sample. Data were analysed to describe which social media tools are being used, by whom, for what purpose and how they are being evaluated.
Two hundred eighty-four studies were included. Discussion forums were highly prevalent and constitute 66.6% of the sample. Social networking sites (14.8%) and blogs/microblogs (14.1%) were the next most commonly used tools. The intended purpose of the tool was to facilitate self-care in 77.1% of studies. While there were clusters of studies that focused on similar conditions (eg, lifestyle/weight loss (12.7%), cancer (11.3%)), there were no patterns in the objectives or tools used. A large proportion of the studies were descriptive (42.3%); however, there were also 48 (16.9%) randomised controlled trials (RCTs). Among the RCTs, 35.4% reported statistically significant results favouring the social media intervention being evaluated; however, 72.9% presented positive conclusions regarding the use of social media.
There is an extensive body of literature examining the use of social media in patient and caregiver populations. Much of this work is descriptive; however, with such widespread use, evaluations of effectiveness are required. In studies that have examined effectiveness, positive conclusions are often reported, despite non-significant findings.
PMCID: PMC3651969  PMID: 23667163
social media; scoping review
20. Collaborative Annotation and Project Management Resource Integrated With the Tranche Repository 
Journal of proteome research  2010;9(6):2809-2811. has implemented a resource that incorporates concepts of Web 2.0 social networking for collaborative annotation of data sets placed in the Tranche repository. The annotation tools are part of a project management resource that is effective for individual laboratories or large distributed groups. The creation of the resource was motivated by the need for a way to encourage annotation of data sets with high accuracy and compliance rates. The system is designed to respond to the dynamic nature of research in an easy-to-use fashion through the use of a dynamic data model that does not inhibit the innovation that is important for basic research. Placing the annotation tool within a project manager allows annotation to occur over the life of the project and provides the security and monitoring capabilities needed for large or small collaborative projects. The resource effectively supports distributed groups of investigators working on common data sets and is available immediately at In addition, a silver compliant data resource based on has been developed for cancer Biomedical Informatics Grid (caBIG) to allow much broader access to the annotations describing data sets in the Tranche repository.
PMCID: PMC3560570  PMID: 20356086
Collaboration tool; annotation management; Proteome Commons;; Tranche; data service
21.  The InterMed Approach to Sharable Computer-interpretable Guidelines: A Review 
InterMed is a collaboration among research groups from Stanford, Harvard, and Columbia Universities. The primary goal of InterMed has been to develop a sharable language that could serve as a standard for modeling computer-interpretable guidelines (CIGs). This language, called GuideLine Interchange Format (GLIF), has been developed in a collaborative manner and in an open process that has welcomed input from the larger community. The goals and experiences of the InterMed project and lessons that the authors have learned may contribute to the work of other researchers who are developing medical knowledge-based tools. The lessons described include (1) a work process for multi-institutional research and development that considers different viewpoints, (2) an evolutionary lifecycle process for developing medical knowledge representation formats, (3) the role of cognitive methodology to evaluate and assist in the evolutionary development process, (4) development of an architecture and (5) design principles for sharable medical knowledge representation formats, and (6) a process for standardization of a CIG modeling language.
PMCID: PMC305452  PMID: 14527977
22.  Building and Sustaining Community-Institutional Partnerships for Prevention Research: Findings from a National Collaborative 
The Examining Community-Institutional Partnerships for Prevention Research Project began in October 2002 with funding from the Centers for Disease Control and Prevention Research Center Program Office through a cooperative agreement between the Association of Schools of Public Health and the CDC. The three-year project aimed to synthesize knowledge about community-institutional partnerships for prevention research and to build community and institutional capacity for participatory research. These ten organizations collaborated on the project because they were all involved in community-institutional partnerships for prevention research, had access to research and evaluation data on these partnerships, and believed that the shared learning and action that would result through a collaborative effort could significantly advance collective knowledge about partnerships and lead to substantive capacity-building responses: the Community Health Scholars Program, Community-Based Public Health Caucus of the American Public Health Association, Community–Campus Partnerships for Health, Detroit Community-Academic Urban Research Center, Harlem Health Promotion Center, National Community Committee of the CDC Prevention Research Centers Program, New York Urban Research Center, Seattle Partners for Healthy Communities, Yale-Griffin Prevention Research Center and the Wellesley Institute. This paper reports on the project’s findings, including common characteristics of successful partnerships and recommendations for strengthening emerging and established partnerships.
PMCID: PMC3261296  PMID: 17082993
Community-academic partnerships; Community-based participatory research; Partnership; Prevention.
23.  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.
PMCID: PMC3558557  PMID: 23188758
Cancer modeling; model repository; oncology; Semantic Web; systems biology
24.  Rat Genome Database (RGD): mapping disease onto the genome 
Nucleic Acids Research  2002;30(1):125-128.
The Rat Genome Database (RGD, is an NIH-funded project whose stated mission is ‘to collect, consolidate and integrate data generated from ongoing rat genetic and genomic research efforts and make these data widely available to the scientific community’. In a collaboration between the Bioinformatics Research Center at the Medical College of Wisconsin, the Jackson Laboratory and the National Center for Biotechnology Information, RGD has been created to meet these stated aims. The rat is uniquely suited to its role as a model of human disease and the primary focus of RGD is to aid researchers in their study of the rat and in applying their results to studies in a wider context. In support of this we have integrated a large amount of rat genetic and genomic resources in RGD and these are constantly being expanded through ongoing literature and bulk dataset curation. RGD version 2.0, released in June 2001, includes curated data on rat genes, quantitative trait loci (QTL), microsatellite markers and rat strains used in genetic and genomic research. VCMap, a dynamic sequence-based homology tool was introduced, and allows researchers of rat, mouse and human to view mapped genes and sequences and their locations in the other two organisms, an essential tool for comparative genomics. In addition, RGD provides tools for gene prediction, radiation hybrid mapping, polymorphic marker selection and more. Future developments will include the introduction of disease-based curation expanding the curated information to cover popular disease systems studied in the rat. This will be integrated with the emerging rat genomic sequence and annotation pipelines to provide a high-quality disease-centric resource, applicable to human and mouse via comparative tools such as VCMap. RGD has a defined community outreach focus with a Visiting Scientist program and the Rat Community Forum, a web-based forum for rat researchers and others interested in using the rat as an experimental model. Thus, RGD is not only a valuable resource for those working with the rat but also for researchers in other model organisms wishing to harness the existing genetic and physiological data available in the rat to complement their own work.
PMCID: PMC99132  PMID: 11752273
25.  Directions for Clinical Research and Genomic Research into the Next Decade 
Medical informatics is defined largely by its host disciplines in clinical and biological medicine, and to project the agenda for informatics into the next decade, the health community must envision the broad context of biomedical research. This paper is a sketch of this vision, taking into account pressures from changes in the U.S. health care system, the need for more objective information on which to base health care decisions, and the accelerating progress and clinical impact of genomics research. The lessons of modern genomics research demonstrate the power of computing and communication tools to facilitate rapid progress through the adoption of open community standards for information exchange and collaboration. While aspects of this vision are speculative, it seems clear that the core agenda for informatics must be the development of interoperating systems that can facilitate the secure gathering, interchange, and analysis of high-quality information and can gain leverage from worldwide collaboration in advancing and applying new medical knowledge.
PMCID: PMC61320  PMID: 9760387

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