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Objective: This study is part of the Student Counselling Outcomes Research and Evaluation (SCORE) initiative that is pooling university counselling service data to improve datasets and evidence for counselling in this sector. This study aimed to explore university counselling staff views about which data should be included in a national minimum data standard (MDS) to provide evidence for counselling in the sector. Method: Semi‐structured focus groups were conducted with university counselling staff including counsellors, service leaders and mental health advisors. They explored data to include in an MDS, current data collection practices, service and sector level data collection barriers. Two researchers performed content analysis involving identifying fields for inclusion. Thematic analysis was used to identify contextual issues surrounding data collection. Ten focus groups were conducted with 41 participants across 26 university counselling services. Results: Content analysis identified fields of information for the MDS within the categories of student characteristics, demographics, clinical assessment and service evaluation. Thematic analysis explored context and culture surrounding data collection, barriers and facilitators, institutional influence and ideal data collection practices. This highlights the need for service support and training around data collection, clear processes, and adequate IT infrastructure and staff resources. Discussion: These findings will inform the development of an MDS as part of the SCORE study. The next stage will involve further development of the MDS and piloting in services. The longer term aim is to implement an MDS across university counselling services, enabling the growth of evidence for the sector which may allow increased funding and service provision. [ABSTRACT FROM AUTHOR]

Aims: To assess the feasibility of implementing data standards in Australian primary care dietetics practices. Methods: A mixed‐methods pragmatic study of dietitians working in primary care. Using a four‐point Likert scale, participants were surveyed on their baseline use of the 45 business and 33 clinical evidenced‐based data standards. The content validity index and kappa statistic for each standard were calculated with a kappa statistic of 0.60–0.74 considered 'Good' and > 0.74 'Excellent'. After 4 weeks of assessment, dietitians were surveyed on the feasibility of implementing each standard and standards in total. Qualitative feedback on enablers and barriers to implementing standards was gathered and triangulated with interviews with select participants. Results: Forty‐five dietitians from every Australian state and territory completed both surveys (response rate: 100%). At baseline, 24% of business and 79% of clinical standards were rated 'Good' or 'Excellent' for current usage. The feasibility of implementing standards was rated 'Good' or 'Excellent for 86% of the business and 97% of the clinical standards. Software, training and time limitations are enablers and barriers to implementing standards. Conclusion: Embedding data standards within dietetics practices are feasible and have broad applicability for assessing outcomes of care. [ABSTRACT FROM AUTHOR]

Objective The National Institutes of Health (NIH) HEAL Initiative is making data findable, accessible, interoperable, and reusable (FAIR) to maximize the value of the unprecedented federal investment in pain and opioid-use disorder research. This involves standardizing the use of common data elements (CDE) for clinical research. Methods This work describes the process of the selection, processing, harmonization, and design constraints of CDE across a pain and opioid use disorder clinical trials network (NIH HEAL IMPOWR). Results The network alignment allowed for incorporation of newer data standards across the clinical trials. Specific advances included geographic coding (RUCA), deidentified patient identifiers (GUID), shareable clinical survey libraries (REDCap), and concept mapping to standardized concepts (UMLS). Conclusions While complex, harmonization across a network of chronic pain and opioid use disorder clinical trials with separate interventions can be optimized through use of CDEs and data standardization processes. This standardization process will support the robust secondary data analyses. Scaling this process could standardize CDE results across interventions or disease state which could help inform insurance companies or government organizations about coverage determinations. The development of the HEAL CDE program supports connecting isolated studies and solutions to each other, but the practical aspects may be challenging for some studies to implement. Leveraging tools and technology to simplify process and create ready to use resources may support wider adoption of consistent data standards. [ABSTRACT FROM AUTHOR]

Purpose: This paper introduces a new set of equity and rights-based principles for health data governance (HDG) and makes the case for their adoption into global, regional and national policy and practice. Design/methodology/approach: This paper discusses the need for a unified approach to HDG that maximises the value of data for whole populations. It describes the unique process employed to develop a set of HDG principles. The paper highlights lessons learned from the principle development process and proposes steps to incorporate them into data governance policies and practice. Findings: More than 200 individuals from 130 organisations contributed to the development of the HDG principles, which are clustered around three interconnected objectives of protecting people, promoting health value and prioritising equity. The principles build on existing norms and guidelines by bringing a human rights and equity lens to HDG. Practical implications: The principles offer a strong vision for HDG that reaps the public good benefits of health data whilst safeguarding individual rights. They can be used by governments and other actors as a guide for the equitable collection and use of health data. The inclusive model used to develop the principles can be replicated to strengthen future data governance approaches. Originality/value: The article describes the first bottom-up effort to develop a set of principles for HDG. [ABSTRACT FROM AUTHOR]

Background: Data management is the key to the success of all projects and research. The ability to safely store, manipulate, and decipher data in real time is invaluable. Currently data management standards in public health are non-existent. Since the invention of computers real-time data retrieval and analysis has been possible but underutilized by researchers in the field. Historically, most small research studies and field-based projects have utilized spreadsheets for data management, which often proves problematic as the project grows. However, a viable and superior alternative exists in relational databases, such as REDCap. Relational databases allow for easier concatenation of multiple legacy datasets, facilitate data entry with surveys that incorporate branching logic, and allow for real time data entry in the field without the need for WIFI. Methods: One example of a public health project being transitioned from spreadsheet data management to a relational database is the Farmworker Family Health Program based out of the Lillian Carter Center for Global Health & Social Responsibility at Emory University’s Nell Hodgson Woodruff School of Nursing. The data management transition from spreadsheets to REDCap has provided the team with unique insight into the data that has been collected in the 30 years the program has been running. Conclusion: Through this case study, we identify the need for and recommend that those in public health nursing utilize relational databases when collecting data during research studies or as electronic medical records for field clinics. [ABSTRACT FROM AUTHOR]

Although there is guidance from different regulatory agencies, there are opportunities to bring greater consistency and stronger applicability to address the practical issues of establishing and operating a data monitoring committee (DMC) for clinical studies of Chinese medicine. We names it as a Chinese Medicine Data Monitoring Committee (CMDMC). A panel composed of clinical and statistical experts shared their experience and thoughts on the important aspects of CMDMCs. Subsequently, a community standard on CMDMCs (T/CACM 1323-2019) was issued by the China Association of Chinese Medicine on September 12, 2019. This paper summarizes the key content of this standard to help the sponsors of clinical studies establish and operate CMDMCs, which will further develop the scientific integrity and quality of clinical studies. [ABSTRACT FROM AUTHOR]

A correction is presented to the article "NIH HEAL Common Data Elements (CDE) implementation: NIH HEAL Initiative IDEA-CC" which appeared in the July 2023 issue.

The application of big data, radiomics, machine learning, and artificial intelligence (AI) algorithms in radiology requires access to large data sets containing personal health information. Because machine learning projects often require collaboration between different sites or data transfer to a third party, precautions are required to safeguard patient privacy. Safety measures are required to prevent inadvertent access to and transfer of identifiable information. The Canadian Association of Radiologists (CAR) is the national voice of radiology committed to promoting the highest standards in patient-centered imaging, lifelong learning, and research. The CAR has created an AI Ethical and Legal standing committee with the mandate to guide the medical imaging community in terms of best practices in data management, access to health care data, de-identification, and accountability practices. Part 1 of this article will inform CAR members on principles of de-identification, pseudonymization, encryption, direct and indirect identifiers, k-anonymization, risks of reidentification, implementations, data set release models, and validation of AI algorithms, with a view to developing appropriate standards to safeguard patient information effectively. [ABSTRACT FROM AUTHOR]

BACKGROUND: A critical challenge in genomic medicine is identifying the genetic and environmental risk factors for disease. Currently, the available data links a majority of known coding human genes to phenotypes, but the environmental component of human disease is extremely underrepresented in these linked data sets. Without environmental exposure information, our ability to realize precision health is limited, even with the promise of modern genomics. Achieving integration of gene, phenotype, and environment will require extensive translation of data into a standard, computable form and the extension of the existing gene/phenotype data model. The data standards and models needed to achieve this integration do not currently exist. OBJECTIVES: Our objective is to foster development of community-driven data-reporting standards and a computational model that will facilitate the inclusion of exposure data in computational analysis of human disease. To this end, we present a preliminary semantic data model and use cases and competency questions for further community-driven model development and refinement. DISCUSSION: There is a real desire by the exposure science, epidemiology, and toxicology communities to use informatics approaches to improve their research workflow, gain new insights, and increase data reuse. Critical to success is the development of a community-driven data model for describing environmental exposures and linking them to existing models of human disease. [ABSTRACT FROM AUTHOR]

Documentation of code status and advance directives for end-of-life (EOL) care improves care and quality of life, decreases cost of care, and increases the likelihood of an experience desired by the patient and his/her family. However, the use of advance directives and code status remains low and only a few organizations maintain code status in electronic form. Members of the American Medical Informatics Association's Ethics Committee identified a need for a patient's EOL care wishes to be documented correctly and communicated easily through the electronic health record (EHR) using a minimum data set for the storage and exchange of code status information. After conducting an environmental scan that produced multiple resources, Ethics Committee members used multiple conference calls and a shared document to arrive at consensus on the proposed minimum data set. Ethics Committee members developed a minimum required data set with links to the HL7 C_CDA Advance Directives Module. Data categories include information on the organization obtaining the code status information, the patient, any supporting documentation, and finally the desired code status information including mandatory, optional, and conditional elements. The "minimum set of attributes" to exchange advance directive / code status data described in this manuscript enables communication of patient wishes across multiple providers and health care settings. The data elements described serve as a starting point for a dialog among informatics professionals, physicians experienced in EOL care, and EHR vendors, with the goal of developing standards for incorporating this functionality into the EHR systems. [ABSTRACT FROM AUTHOR]

Providing access to the data underlying research results in published literature allows others to reproduce those results or analyze the data in new ways. Health sciences librarians and information professionals have long been advocates of data sharing. It is time for us to practice what we preach and share the data associated with our published research. This editorial describes the activity of a working group charged with developing a research data sharing policy for the Journal of the Medical Library Association. [ABSTRACT FROM AUTHOR]

The development of library customized reports has always been one of the intractable problems that library managers urgently seek to solve. Similarly, library automation system manufacturers are bruised on this issue, not only the high cost of development services, but also the frequent changes in demand. The problem is still difficult to have by a cost-effective solution. In recent years, ExLibris has developed an add-on system Aleph Reporting Center (ARC) for its library automation system Aleph to provide Aleph customers more than 100 pre-defined statistical reports. However, such reporting systems only support specific automation systems, and cannot fully meet the customized needs of libraries'. Data warehouse technology has been quite mature since the 1970s. Most database management systems such as SQL Server also provide tools to support the establishment of data warehouses. Considering the cost-effectiveness and the demand elasticity of customization, this study proposes the data warehouse application model of libraries to solve the above dilemma. The application model proposed in this research, the system environment is constructed by Microsoft SQL Server, EXCEL; design and development are mainly accomplished by the librarian and system librarian. This study concludes with a practical case to verify the feasibility of the proposed model. [ABSTRACT FROM AUTHOR]

We assess the quality of the HRS's measures of out-of-pocket medical spending and health insurance premia, both in the "core interviews" and in the "exit interview" data. We provide detailed evidence on the quality of the HRS insurance premia data, and we compare the HRS exit data to exit data in the MCBS. We document how changes in survey questions, including the introduction of "unfolding brackets," affect the HRS measures. We document what we believe are errors in the HRS imputations and provide some suggestions for improving the accuracy of some imputed variables. Overall, we find the HRS data to be of high quality. However, we believe that many interesting variables in the HRS are under-utilized because users must perform imputations themselves. [ABSTRACT FROM AUTHOR]

Objectives. To obtain consensus on the minimum data items for an observational cohort study in RA in the UK and to make available the process for similar studies and other rheumatic conditions. Methods. Individuals with a diverse range of expertise and backgrounds were invited to participate in a process of proposing a minimum core dataset (MCD) for research studies, commissioned by Arthritis Research UK as part of the larger INBANK project. The group included patients and representatives from clinical and academic rheumatology, outcomes science, stratified medicine, health economics, and national professional and academic bodies/committees. A process was devised based on OMERACT principles for reviewing aims/objectives, defining the scope, identifying the important research questions and selecting key domains. Results. Following the initial multistakeholder meeting, subsequent teleconferences and email communications: consensus was obtained on the most important and relevant research questions; agreement on how the OMERACT Core Areas (life impact, pathophysiological manifestations, resource use and death) could form the basis of a MCD; and consensus on 22 items for inclusion into a MCD. Workshops were undertaken for two essential items that required further exploration: work/social participation and comorbidity. Conclusion. Reaching a consensus for the proposed minimal data items for long-term observational cohort studies of RA in the UK posed novel challenges and opportunities, and was largely successful. Further work is needed for selecting instruments for two important items and for achieving compatibility with other UK national initiatives, and more widely across Europe. [ABSTRACT FROM AUTHOR]

Background: This masterclass introduces the topic of core outcome sets, describing rationale and methods for developing them, and providing some examples that are relevant for clinical research and practice. Method: A core outcome set is a minimum consensus-based set of outcomes that should be measured and reported in all clinical trials for a specific health condition and/or intervention. Issues surrounding outcome assessment, such as selective reporting and inconsistency across studies, can be addressed by the development of a core set. As suggested by key initiatives in this field (i.e. OMERACT and COMET), the development requires achieving consensus on: (1) core outcome domains and (2) core outcome measurement instruments. Different methods can be used to reach consensus, including: literature systematic reviews to inform the process, qualitative research with clinicians and patients, group discussions (e.g. nominal group technique), and structured surveys (e.g. Delphi technique). Various stakeholders should be involved in the process, with particular attention to patients. Results and conclusions: Several COSs have been developed for musculoskeletal conditions including a longstanding one for low back pain, IMMPACT recommendations on outcomes for chronic pain, and OMERACT COSs for hip, knee and hand osteoarthritis. There is a lack of COSs for neurological, geriatric, cardio-respiratory and pediatric conditions, therefore, future research could determine the value of developing COSs for these conditions. [ABSTRACT FROM AUTHOR]

The Deep Dive into KBART preconference workshop provided a comprehensive overview of the National Information Standards Organization Knowledge Bases and Related Tools (KBART) Phase II Recommended Practice (http://www.niso.org/publications/rp/rp-9–2014/). The workshop was divided into four sections. The first provided an overview of the background, purpose, and value of KBART to all members of the information supply chain. The next section focused on the basic guidelines for effective exchange of metadata with knowledgebases, including method of exchange, data format, file naming conventions, and frequency of exchange. The remaining two sections of the workshop addressed the correct use of KBART data fields, first in relation to serials and then to monographs. Through classroom instruction, interactive quizzes, and hands-on exercises, the workshop provided in-depth coverage of all KBART data elements, with special focus on many of the most frequently asked questions about the recommended practice. [ABSTRACT FROM PUBLISHER]

Since its first Code of Practice was published in 2003, setting the first international standard for reporting usage of scholarly content, Counting Online Usage of Networked Electronic Resources (COUNTER) has been continually refining the code of practice to meet the evolving needs of its library, publisher, and vendor membership. The latest release of the Code of Practice went into effect in early 2014 and introduced several improvements over the prior releases. Work is now underway on Release 5 of the COUNTER Code of Practice with a promise that it will provide further improvements to better report on usage of scholarly information in an ever-changing discovery and access environment. This column discusses current challenges and how Release 5 might address them. [ABSTRACT FROM PUBLISHER]

Background: The Tufts Center for the Study of Drug Development (Tufts CSDD) collaborated with the Clinical Data Interchange Standards Consortium (CDISC) on a joint working group study with 10 participating companies including biopharmaceutical, CROs, and eClinical technology vendors. The objective of the study was to examine current and projected use of eClinical technology and standards across respondent organizations and in clinical studies and to gather perceptions and attitudes about technology and standards adoption. Methods: The Tufts CSDD study examined the use of eClinical technology and CDISC standards through a comprehensive survey combined with analyses of clinical study data among biopharmaceutical companies and contract research organizations. Results: The results suggest increasing use of specific eClinical technology solutions and standards. The barriers to adoption of eClinical trial tools are addressed as well as the benefits of standards adoption. Differences between respondent perceptions and actual study data are examined, and the survey results are compared with those from prior studies. Conclusions: The results of the study indicate that increasing use of standards could translate into improvements in time, costs, and overall approval rates. The study also observed an uptake in the use of eClinical technologies that could potentially create efficiencies and streamline operational processes. [ABSTRACT FROM AUTHOR]

Context.— Biospecimens must have appropriate clinical annotation (data) to ensure optimal quality for both patient care and research. Additional clinical preanalytic variables are the focus of this continuing study. Objective.— To complete the identification of the essential preanalytic variables (data fields) that can, and in some instances should, be attached to every collected biospecimen by adding the additional specific variables for clinical chemistry and microbiology to our original 170 variables. Design.— The College of American Pathologists Diagnostic Intelligence and Health Information Technology Committee sponsored a second Biorepository Working Group to complete the list of preanalytic variables for annotating biospecimens. Members of the second Biorepository Working Group are experts in clinical pathology and microbiology. Additional preanalytic area–specific variables were identified and ranked along with definitions and potential negative impacts if the variable is not attached to the biospecimen. The draft manuscript was reviewed by additional national and international stakeholders. Results.— Four additional required preanalytic variables were identified specifically for clinical chemistry and microbiology biospecimens that can be used as a guide for site-specific implementation into patient care and research biorepository processes. Conclusions.— In our collective experience, selecting which of the many preanalytic variables to attach to any specific set of biospecimens used for patient care and/or research is often difficult. The additional ranked list should be of practical benefit when selecting preanalytic variables for a given biospecimen collection. [ABSTRACT FROM AUTHOR]

Context.--Biospecimens must have appropriate clinical annotation (data) to ensure optimal quality for both patient care and research. Clinical preanalytic variables are the focus of this study. Objectives.--To define the essential preanalytic variables (data fields) that should be attached to every collected biospecimen and to provide a complete list of such variables, along with their relative importance, which can vary, depending on downstream use, institutional needs, and information technology capabilities. Design.--The College of American Pathologists Diagnostic Intelligence and Health Information Technology Committee sponsored a Biorepository Working Group to develop a ranked list of the preanalytic variables for annotating biospecimens. Members of the working group were experts in anatomic, clinical, and molecular pathology; biobanking; medical informatics; and accreditation. Several members had experience with federal government programs, such as the National Cancer Institute's Biospecimens and Biorepository Branch and the National Cancer Institute's Community Cancer Center Program. Potential preanalytic variables were identified and ranked along with available supporting evidence, definitions, and potential negative effects if the variable was not attached to the biospecimen. Additional national and international stakeholders reviewed the draft manuscript. Results.--The ranked listing of 170 preanalytic variables produced can be used as a guide for site-specific implementation into patient care and/or research biorepository processes. Conclusions.--In our collective experience, it is often difficult to choose which of the many preanalytic variables to attach to any specific set of biospecimens used for patient care and/or research. The provided ranked list should aid in the selection of preanalytic variables for a given biospecimen collection. [ABSTRACT FROM AUTHOR]

States are working to improve the integration of care for dually eligible individuals, but they face several challenges in demonstrating how these new models improve the quality of care and services provided. This article summarizes efforts to develop an approach to measure quality in integrated care programs. It provides an overview of the measurement approaches for proposed integrated programs, including assessment of quality in specific domains of integrated care such as long-term services and supports, and behavioral health services. It also describes how performance measures can be shaped by stakeholder input. [ABSTRACT FROM AUTHOR]

Donald R. Deutsch joined the US government agency now called the National Institute of Standards and Technology (NIST) in the last 1970s and the X3H2 Database Standards Committee (DSC) in Washington DC in April 1978. Initially chartered only to develop a standard Data Definition Language (DDL) for network DBMSs, in time the DSC became the epicenter of US and international SQL standardization. Deutsch became the DSC vice chair at the second meeting and chair at the committee's 11th meeting in May 1980. Throughout his career that included (in addition to NIST) GE, Sybase, and now Oracle, he has continued to chair the DSC. From this perspective, this article describes how the SQL standard happened. [ABSTRACT FROM PUBLISHER]

Background: Studies using English administrative data from the Hospital Episode Statistics (HES) are increasingly used for the assessment of health-care quality. This study aims to catalogue the published body of studies using HES data to assess health-care outcomes, to assess their methodological qualities and to determine if reporting recommendations can be formulated. Methods: Systematic searches of the EMBASE, Medline and Cochrane databases were performed using defined search terms. Included studies were those that described the use of HES data extracts to assess health-care outcomes. Results: A total of 148 studies were included. The majority of published studies were on surgical specialties (60.8%), and the most common analytic theme was of inequalities and variations in treatment or outcome (27%). The volume of published studies has increased with time (r = 0.82, P < 0.0001), as has the length of study period (r = 0.76, P < 0.001) and the number of outcomes assessed per study (r = 0.72, P = 0.0023). Age (80%) and gender (57.4%) were the most commonly used factors in risk adjustment, and regression modelling was used most commonly (65.2%) to adjust for confounders. Generic methodologic data were better reported than those specific to HES data extraction. For the majority of parameters, there were no improvements with time. Conclusions: Studies published using HES data to report health-care outcomes have increased in volume, scope and complexity with time. However, persisting deficiencies related to both generic and context-specific reporting have been identified. Recommendations have been made to improve these aspects as it is likely that the role of these studies in assessing health care, benchmarking practice and planning service delivery will continue to increase. [ABSTRACT FROM AUTHOR]

Objectives:To develop an International Spinal Cord Injury (SCI) Musculoskeletal Basic Data Set as part of the International SCI Data Sets to facilitate consistent collection and reporting of basic musculoskeletal findings in the SCI population.Setting:International.Methods:A first draft of an SCI Musculoskeletal Basic Data Set was developed by an international working group. This was reviewed by many different organizations, societies and individuals over 9 months. Revised versions were created successively.Results:The final version of the International SCI Musculoskeletal Basic Data Set contains questions on neuro-musculoskeletal history before spinal cord lesion; presence of spasticity/spasms; treatment for spasticity within the last 4 weeks; fracture(s) since the spinal cord lesion; heterotopic ossification; contracture; the location of degenerative neuromuscular and skeletal changes due to overuse after SCI; SCI-related neuromuscular scoliosis; the method(s) used to determine the presence of neuromuscular scoliosis; surgical treatment of the scoliosis; other musculoskeletal problems; if any of the musculoskeletal challenges above interfere with activities of daily living. Instructions for data collection and the data collection form are freely available on the International Spinal Cord Society (ISCoS) website (www.iscos.org.uk).Conclusion:The International SCI Musculoskeletal Basic Data Set will facilitate consistent collection and reporting of basic musculoskeletal findings in the SCI population. [ABSTRACT FROM AUTHOR]

Objectives:To develop the International Spinal Cord Injury (SCI) Pulmonary Function Basic Data Set within the framework of the International SCI Data Sets in order to facilitate consistent collection and reporting of basic bronchopulmonary findings in the SCI population.Setting:International.Methods:The SCI Pulmonary Function Data Set was developed by an international working group. The initial data set document was revised on the basis of suggestions from members of the Executive Committee of the International SCI Standards and Data Sets, the International Spinal Cord Society (ISCoS) Executive and Scientific Committees, American Spinal Injury Association (ASIA) Board, other interested organizations and societies and individual reviewers. In addition, the data set was posted for 2 months on ISCoS and ASIA websites for comments.Results:The final International SCI Pulmonary Function Data Set contains questions on the pulmonary conditions diagnosed before spinal cord lesion,if available, to be obtained only once; smoking history; pulmonary complications and conditions after the spinal cord lesion, which may be collected at any time. These data include information on pneumonia, asthma, chronic obstructive pulmonary disease and sleep apnea. Current utilization of ventilator assistance including mechanical ventilation, diaphragmatic pacing, phrenic nerve stimulation and Bi-level positive airway pressure can be reported, as well as results from pulmonary function testing includes: forced vital capacity, forced expiratory volume in one second and peak expiratory flow. The complete instructions for data collection and the data sheet itself are freely available on the website of ISCoS (http://www.iscos.org.uk). [ABSTRACT FROM AUTHOR]

The article offers information on trends in biobanking. Topics discussed include careful sample management, views of Marcel Brulnenberg, project manager at the LifeLines LlfeStore In Gronlngen, on increasing distinction between a professional blobank and a sample storage facility, the International Organization for Standardization (ISO) to develop standards for biobanks and use of data harmonl:zatlon protocol by most biobanks for blood samples.

The authors reflect on the cancer protocols developed and maintained by the College of American Pathologists (CAP). Topics discussed include standards for accreditation of cancer patients introduced by the Commission on Cancer of the American College of Surgeons in 2004, the three CAP resource committees responsible for creating the protocols, and the seven basic principles that have been defined for trustworthy guidelines.

After welcoming remarks, the 3rd ASIS&T Summit on Research Data Access & Preservation (RDAP) got underway with a panel discussion on data management plans and policies. Panelists described a variety of data management projects in the U.S. and the European Union and the challenges faced during implementation. Additional panels focused on data citation, data curation service models and education for data management practitioners. Data management supporting a sustainability environment was the topic of the Digital Libraries Sustainability SIG panel. The summit closed with a series of fast-paced lightning talks and with demonstrations of the DataNet Federation Consortium, a proposed nationwide data management infrastructure, and RUcore, the Rutgers University community repository. [ABSTRACT FROM AUTHOR]