Conference Presentations 2011

Colectica is a platform for documenting and sharing data using open standards such as DDI 3. This workshop covers the following topics: Introduction to DDI 3-based data sharing; Hands on tutorial Document concepts and general study design; Design and document surveys; Share questions with question banks; Create and document datasets; Share variables with variable banks; Ingest existing datasets, variables, and questions and Publish data documentation on the Web.

In this workshop we will showcase the materials we have produced at the UK Data Archive as part of our support and outreach work on managing research data from the social sciences. The areas we are focusing on are: consent and ethics; IPR; data description and data formatting.

The workshop will use a combination of ppt presentations (reflecting materials given to researchers and support staff) and hands-on activities such as: assessing and evaluating authentic consent forms for data sharing; anonymisation exercises; and assessing data formats such as interview transcription. Participants will learn about practical strategies that can help research centres or hubs set up in-house procedures to manage their own live project and legacy data. The workshop will showcase how the UK Data Archive has worked with: 1) Research Ethics Committees to help them appreciate how to accommodate data protection vs data sharing in their own advice, and 2) Continuous Professional Development training programmes within institutions to support core skills of data handling and data security; and 3) PhD and early career research training courses to support data awareness and data management.

A new version of Nesstar, Nesstar 4.0, with a lot of new functionality has recently been released. The metadata editor and publishing tool Nesstar Publisher is now also made available as freeware. The new version includes, among other things, support for multilingual metadata, powerful support for aggregate data, subscriptions/notifications, cell notes/missing data symbols, and embedding of live data into web pages.

This workshop will be a hands-on one, and participants will learn how to use Nesstar to: Prepare and publish survey data with multilingual metadata Produce, prepare and publish aggregate data (cubes) Notify subscribing users about changes in the published material Add thematic mapping capabilities to microdata and aggregate data sets Embed tables, analyses, charts and thematic maps into ordinary web-pages.

R, the open source statistical environment,is growing rapidly in use and increasing in visibility. R is one of 7 Computing Languages on the Rise, has been profiled in the New York Times, and will be featured in an upcoming issue of Forbes. This program will begin with an introduction to R, its features, and the characteristics that have led to its popularity in the data world. Hands on work will introduce R programming, data manipulation capabilities, basic statistical operations, and graphing functionality. Add-on packages, including graphical interfaces and data mining tools, will be illustrated. Finally, the workshop will discuss how R is being used with “big data”, interacting with databases and large data feeds to perform analysis.

This panel addresses recent developments in the DDI implementation landscape - new tools developments, and related developments in the standards. There has been much activity in the DDI community within the past year. Some of the existing tools have been extended with major new features; there are several new tools which support and use DDI 3, and there have been some developments for the DDI standards by the DDI Alliance itself, which will influence on-going tools support. Discussion covers both open-source and freely available tools, and also commercial tools which support DDI 3. This panel summarizes these recent developments, and highlights the points of interest. The panel is divided in three blocks A1, C1 and D1.

This tool demonstrates how a structured questionnaire design can be leveraged to harvest metadata, which can then be used to drive tasks downstream in the data lifecycle with greater ease. The application takes in a questionnaire designed in Microsoft Office Word 2007 (.docx format) document and uses LINQ to extract different meta components that make up the questionnaire. The extracted components are then translated into a XAML document that describes the data entry screen and a corresponding DDI document that describes the questionnaire. These two documents are then used to drive the data entry process and preform basic validations like restricting entered values to the codes in a coding scheme, basic data typing, data length and skips. Once the data is entered, the DDI is again leveraged to configure the export process that allows for selecting which variables to export and filtering by error status. The export process also uses the DDI to construct setup files for STATA and produce customized user documentation. Overall, this application demonstrate that creating DDI documentation does not have to be a painstaking, time consuming process done by hand and the advantages of documenting early in the data lifecycle, so that it can be used to drive onward data management activities consistently and efficiently.

In January 2010, the University of Guelph Library launched a new data management and preservation service for researchers on campus. While the new service was in its initial stages of development, research groups on campus were eager to volunteer their research projects to serve as pilot test cases. Ultimately, two large, long-term research groups were selected and, following the administration of needs assessments, management plans have been developed around the issues identified for each research group. This paper will track the development of the service with particular attention being paid to the complex needs of the different groups involved in the pilot project. Subsidiary services for graduate students which have been incorporated into the program will also be discussed. Reactions to these new services will be explored.

The need for reference metadata has been recognized and identified as crucial within the financial industry. Unique and standardized identification of legal entities has become a top priority for the financial industry. It is now widely recognized that such an identifier is critical to efficient financial transaction processing and is critical for clear and unambiguous identification of parties and counterparties involved in all financial activities. Although the need for unique entity identification across government agencies, data vendors, and financial market participants has been discussed for years there is currently no entity identification schema used across the financial industry. The events of the last several years and the recent financial reform highlight the need for legal entity identifiers that cross organizations. The paper is the collaborate result of several financial regulators and:
• Explores the current state of entity identification throughout the financial industry,
• Presents the business cases for why unique and standardized identification is necessary,
• Summarizes the industry best practices and requirements for entity identification, and
• Identifies alternative approaches to implementing industry-wide identifiers.

The reuse and secondary analysis of digital data in the environmental and social sciences is aided greatly by well-established data repositories and a research culture that fosters trusted data sharing, respectively. However, relatively few studies in either of these disciplines have considered the component activities of reusing data beyond an initial phase of discovery; more often, studies have identified barriers to access or focused on the need to properly attribute datasets. We present a comparative analysis of those activities and practices surrounding secondary use of publicly available data in the environmental and social sciences. Identified activities in these two disciplines are grounded in the current literature, which include: selection criteria for reuse, methodological approaches as they vary by discipline, transfer protocols, citation practices, and explicit barriers to access and use of secondary data. This comparison of data practices provides a formalization of the implicit activities surrounding reuse that will prove highly valuable to data librarians and data scientists in their interactions with an increasingly interdisciplinary and collaborative research community. An analysis of data reuse also offers much needed insight to the development and maintenance of deployed cyberinfrastructures, particularly as these large-scale systems are geared toward data-centric research.

The expansion of data holdings to incorporate qualitative content has been a major emphasis of the Australian Data Archive since 2007, focussed on the establishment of ADA Qualitative (formerly AQuA). While there have been significant challenges in efforts during this time to encourage qualitative researchers to deposit content with the archive, the deposit of these new data forms have also created new challenges for the archive in ingesting, processing and dissemination. These challenges have been threefold: - methodological: what changes do researchers need to make in their methods to support archival practice - technical: how does ADA adapt its existing metadata schema and data management software (DDI2 and Nesstar) to support qualitative content - practical: how are processing procedures for archivists changed when documenting qualitative content This paper explores each of these challenges in turn, focussing particularly on the adoption of the QuDEx schema developed by the UK Data Archive to support qualitative data archiving. The paper will discuss ADA's experience with the use of the QuDEx schema to address these three challenges, and provide suggestions for future developments of the schema and qualitative archiving more generally.

Rewarding investigators who share data, assessing the impact of data repositories, and measuring the intended and unintended effects of data policy decisions all depend on being able to track dataset reuse. Unfortunately, tracking data reuse is currently extraordinarily difficult due to diverse attribution practices, tool limitations, and data source restrictions. Through a Pecha Kucha overview and subsequent details in a more traditional format, this talk will summarize recent experiences in tracking data reuse. Examples will be drawn from the ongoing project Tracking Data Reuse: Following one thousand datasets from public repositories into the published literature (winner of the 2010 ASIS&T SIGUSE Elfreda A. Chatman Research Proposal Award).

The questionnaire of the recent EVS wave 2008 was translated into 38 languages and adjusted to 46 different cultural contexts to ensure that questions measure the same phenomena. This translation process was closely monitored and well documented, and it was the starting point for a workflow designed by GESIS that aims at high quality documentation of data with original question texts. This documentation is valuable for secondary users who want to look at the question wording used in different languages, countries or waves. We presented the ongoing project at IASSIST/IFDO 2009 and are now able to report on the findings. With the full data release of EVS 2008 in December 2010 the documentation process will be finished and the original language documentation will be published through online retrieval systems, an interactive online overview, and English/original language variable reports (http://www.europeanvaluesstudy.eu/). With the release of the longitudinal file 1981-2008 in June 2011 the original questions for two waves will be available and comparisons of questions across time will be possible. The workflow includes long-term preservation of all key information and databases. Also it allows for the re-use of the original language documentation as basis for questionnaire translation of coming waves.

QDDS is a general approach to create and design questionnaires and to document the changes and design decisions made in the process. This documentation is especially important for panels or other surveys that re-use instruments, as it allows the users to participate from the decisions already made and existing questionnaire elements. The alternative, to document the changes manually, is labor intensive and complex. Also, the goal is to have a multiple-purpose questionnaire editor that can be used to design surveys regardless of the target distribution system. Currently, we are using the DDI 2.1 standard as general file format and work on a switch to DDI 3.1. Using these standards makes it possible to import questionnaires into structured survey documentations without any loss of information. In this paper, we describe how we manage to hide the complexity of DDI by focusing on the main entities. We also describe the architecture and how it leads to the easy-to-use interface that allows primary researchers to use this tool efficiently, without in-depth documentation skills. Furthermore, we sketch out the necessary changes that are necessary to switch to DDI 3.1 and how that will improve the interaction with future information systems based on DDI 3.1. In the presentation on the last IASSIST we showed mainly the overall concept and reason for the support of DDI 3. For this IASSIST we want to show a first view on the actual solution and the corresponding changes on user interface level that are necessary.

Part of our data archive is open for self-archiving, which requires that researchers who deposit their data add metadata themselves. In line with this practice and current trends such as Web 2.0. we are interested in enriching our current metadata with user reviews. Moreover, whereas research quality is also measured by the number and quality of publications, it makes sense to value the quality of the underlying data and the degree to which they are fit for re-use. Therefore we recently carried out a pilot study among researchers who downloaded data sets from our archive. We asked them to review the downloaded data set on several dimensions and also to provide keywords "tags" that should help other researchers to find this data set. Next, we have presented both the tags and the averaged review scores as part of that set’s metadata. In this presentation we will give an impression of the reviews and the user tags and how these tags relate to professional keywords.

Building the infrastructure, expertise, and tools to meet the multifaceted needs of researchers using confidential data confronts challenges in cost, security and legality. To answer these challenges, the Cornell Institute for Social and Economic Research (CISER) staffs and hosts the Cornell Restricted Access Data Center (CRADC). Since its inception in 1999, the CRADC has provided secure access to confidential research data and has become the Cornell University custodian of restricted access data sets. The endeavor to balance a resource-rich and highly-usable collaborative computing environment that also meets security requirements demands technological leadership as well as expert service related to a great variety of data providers and software packages. This presentation will describe how CISER facilitates this balance, via a synthesis of technology, expert service and tools to empower sanctioned and secure scientific research on restricted access data at Cornell University.

The Social Science Japan Data Archive (SSJDA) plays the role of a major data provider for those who seek to analyze the Japanese society using micro data. Deposited datasets to the SSJDA are described in various formats and we have many works to create metadata of the each survey. This situation is not good for managing our archive. We thought this situation can be changed through disseminating the Data Documentation Initiative (DDI). Due to its complexity of the specification of the DDI, the metadata are often created with certain software such as Nesstar, Colectica and so on. With these applications, researchers can easily create DDI documents, but these applications are relatively expensive for individual researchers. In addition, Japanese researchers have difficulty to use them because of language barrier. Thus we are developing free software to edit DDI documents. In this presentation, we will show a prototype of open source metadata editor and its process.

The Ontario Council of University Libraries (OCUL) is a consortium of twenty-one university libraries in the province of Ontario that collaborates on resource sharing, access to resources and technologies. OCUL was represented at IASSIST 2010 with a pecha kucha session that explored and demonstrated our vision for an online geospatial portal, a project that is currently in development. Our vision includes the provision of tools for identifying, exploring, and downloading licensed geospatial data, as well as collaboration and teaching tools. The vision also involves the creation and open sharing of standards-based geospatial metadata. In Fall 2011, OCUL will be launching its first release of the geospatial portal. The spring 2011 IASSIST session will provide a preview of the portal, demonstrating the available tools. The session will also discuss the expected impact of the portal at Ontario universities, assessment plans, and future development goals.

Katharin Peter will provide a look at models and opportunities for one-shot group instruction within the library and across campus including course-specific instruction, workshops, and instructional partnerships.

An overview of major data resources available for Latin America, Spain, and Portugal will be provided.

The University of Porto is currently concerned with the curation of and the access to the scientific data generated by its researchers. There is a growing awareness of the fragility of digital archives, and researchers feel that they need to keep their data assets alive as the scientific infrastructure becomes more sophisticated. The possibilities of scientific impact derived from open datasets are also becoming evident to them. As a result of an identification task, we present a preliminary study on the datasets which are being used in current research, picking examples from life sciences, engineering, social sciences and arts. The identification also provides insight on current models for data curation, both formal and informal, and on the sensitivity of researchers with respect to open access to their data.

As data professionals, our work often requires explaining and justifying our positions and our data resources. Whether we are data librarians in large research institutions with well-established services or social science librarians at small institutions with few data users, we all must fight for resources that may seem overly expensive and esoteric to non-data users. In this pecha kucha I will highlight efforts at various libraries to make data services and resources accessible (and appealing) to non-data users. These efforts are not limited to the use of creative marketing techniques; they also include approaches to teaching and virtual reference that introduce users to data resources without overwhelming them. At the most basic level, the way that we communicate and explain our services on our websites impact how our users will interact with us and our resources. In a world of 20% budget reductions data professionals must fight for the right to data while developing relationships with partners throughout our user communities that will lead to better understanding of, and as a result, higher use of data resources.

The DDI Alliance is publishing controlled vocabularies for a number of descriptive elements that are frequently used in data documentation. These vocabularies are issued as a separate product from the DDI schemas. They are declared in Genericode - an XML standard for defining code lists and an OASIS committee specification - and they are suitable to use in conjunction with DDI 3 and DDI 2 elements, as well as any matching elements in other data documentation standards. Multiple language translations are also supported. Our presentation will review the first set of published vocabularies, demonstrate how they can be accessed and used, and will offer a preview of those lists on which work is still in progress. We will also discuss the Controlled Vocabularies Working Group's approach to building these code lists, some of the challenges we faced, as well as plans to manage and develop the vocabularies moving forward.

Markus Quandt (GESIS) emphasizes how the project will work towards making metadata available for discovery on the CESSDA portal.

The North Carolina Geospatial Data Archiving Project (NCGDAP) was a joint effort between North Carolina State University Libraries and the North Carolina Center for Geographic Information & Analysis, in cooperation with the Library of Congress under the National Digital Information Infrastructure and Preservation Program (NDIIPP). That initial project served to catalyze discussions about data preservation needs within the network of data producers and custodians that form spatial data infrastructure, and led to the formal involvement of state archives in data preservation of activities. Cross-fertilization with activities in other states led to a subsequent NDIIPP initiative called GeoMAPP (Geospatial Multistate Archive and Preservation Partnership), which has built on the initial learning experiences of NCGDAP and has focused more explicitly on formal archival processes such as selection, appraisal, retention scheduling, and content transfer. GeoMAPP has recently expanded to include five participant states, and is now focused on preservation and data transfer, storage and access, industry outreach, mentoring peer states, and business planning. The experience of both NCGDAP and GeoMAPP has shown the value of providing producers and managers of geospatial data with access to information resources that support data preservation efforts.

The DataSHaPER (DataSchema and Harmonization Platform for Epidemiological Research; http://www.datashaper.org) was developed to provide a flexible, but structured approach to the harmonization and pooling of selected information between studies. In this poster/demonstration, this methodological tool is used to demonstrate the potential of sharing harmonized data (148 reference variables) between 53 large population-based studies (6.9 million participants). The DataSHaPER approach to retrospective harmonization is threefold. Firstly, rules reflecting the formal criteria that determine if a particular reference variable can be recreated from the assessment items of each study are defined. These rules also determine the quality of the match between reference variables and assessment items. Secondly, rules are applied for each reference variable and for each study participating in the harmonization process. Finally, results from this exercise are tabulated to illustrate the data sharing potential between participating studies. Results from this harmonization exercise show that a number of important reference variables can potentially be shared and co-analyzed by a large number of participating studies. The data harmonization potential thus demonstrated by the DataSHaPER tool offers the promise of greatly enhanced collaborative research generated through synthesized databases in many fields including health, environmental, and social sciences.

At its annual meeting on May 31, 2010, the DDI Alliance Expert Committee agreed to charge a newly formed group with the revision of the DDI Tools Catalog (http://www.ddialliance.org/resources/tools), which aims to support the social science data community by providing a comprehensive, web-accessible database of tools for utilizing DDI metadata. This live preview of the revised Tools Catalog will show its new features and workflow for developer submissions. Feedback from the social science data community on what would make the DDI Tools Catalog even more useful in the future, and volunteers for editing its contents, will also be invited.

Query-based access is an alternative approach to dissemination-based access for making statistics available. It takes advantage of high performance computing and new information privacy protection methods to reduce the amount of up front work required from the provider and increase the level of access to data for end users. It is particularly useful when your statistics are in demand from researchers.

Cursory research of literature and select US and foreign institutions' websites on the emerging field of digital curation reveal varied definitions of digital curation with some definitions possessing ambiguous interpretations when digital curation and data curation appear to be used interchangeably to define digital curation. Hence, a survey titled defining digital curation understanding was developed to address this research issue. The goal of this survey is to understand the public’s perception of data curation, digital preservation, digital curation, and life cycle terms. This survey was created to illuminate common terminology development across multiple research disciplines for deeper inter-disciplinary research exploration and collaboration within the broader context of data management. Since digital curation involves multiple research disciplines, institutions and organizations, there is a need to assess the public’s response to the development towards common nomenclature of definitions and interpretations across multiple disciplines. The data from this survey will be used to support and stimulate discussions toward impacting decisions for the establishment of baseline terminology agreement across disciplines, institutions, and organizations in the US with practical implications for contributions to curriculum, theoretical, and professional development.

This exploratory research poster will use text, graphics, and survey results to explore defining digital curation understanding across disciplines, institutions, and organizations in the US, provide insight into future digital curation curriculum development, and contribute to existing literature in the emerging field of digital curation research in the US.

ICPSR is building Fedora Commons data models for social science research data and documentation that conform to the OAIS reference model, and which will facilitate the generation of key OAIS products such as the Archival Information Package (AIP). This presentation will share the results of an NSF-funded INTEROP grant which has funded this work since late 2009.

The UK Economic and Social Research Council has recently funded a new Secure Data Service to provide remote secure access to data previously considered too sensitive or detailed to be allowed offsite. After a 2-year pilot and a long journey of collaboration with the UK Office for National Statistics and other major UK data producers, the Secure Data Service has launched a fullblown service for UK academic researchers. The poster will demonstrate what the service offers and how.

This paper will describe the tools, resources and communication strategy designed to support researchers across multiple disciplines, to think about their data from project inception and planning through to publication and promotion. It describes a staged approach to data management planning, just-in-time information design, and tools and techniques for collaborating. This project, based at the University of Technology, Sydney was designed to improve data management planning, capture and discovery across the University as well as influence management policies and processes, but it also demonstrates the value of designing a user needs approach rather than relying on a compliance-based system. The deliverables from the project, including data management checklists and guidelines, guides to data archives, metadata approaches, protocols and tools for promotion will be discussed.

Since the publication of DDI 3 in 2008, a lot of attention has focused on the expanded features and tools being developed around this new structure. At the same time DDI 2 and earlier versions continue to support the work of data archives worldwide and, with the advent of the IHSN Microdata Toolkit, they also facilitate the collection and management of survey data in many developing and transitional countries. DDI 2 has a stable and growing community of users who will either continue to use this development line or will eventually work in an environment where both DDI development lines are used. In order to support this user base and its evolving needs, DDI 2.5 was developed. This new version adds coverage for features of simple surveys found in DDI 3 and better supports the translation of metadata between the two DDI development lines. DDI 2.5 is backwards-compatible with earlier versions while adding support for new elements and better communication with the DDI 3 structures. This presentation will highlight new features and explore some of the use cases in which DDI 2.5 can benefit the current user community.

The Census Dissemination Unit (CDU) at Mimas provides access to the Census aggregate datasets for the UK academic community and champions the needs of that community in discussions with the Office for National Statistics (ONS), the UK statistics authority. This paper will describe how the CDU engaged with the ONS to develop a new way that aggregate census statistics are stored, delivered and used, working in collaboration with them to revolutionise the data delivery mechanism for the 2011 Census. The ONS is now committed to using these ideas to create a ‘data feed’ approach to delivering the 2011 Census. What has developed is a synergistic relationship that allows the transfer of knowledge from the academic community and utilises the skills of both parties to develop ideas and products that will enhance the way that the 2011 Census is used not only by the academic community, but by business, government and third party census application developers. The ONS is currently co-funding a project at the CDU to create test datasets for use in developing an Application Programming Interface that the CDU and other developers can utilise to develop applications for delivering census data to their respective communities.

For data sharing, access and management in the future to become a higher priority within scholarly communication than it is now, new generations of scientists and scholars need to learn to do research in ways that support these ends. The Research Data MANTRA project (2010-2011) aims to develop online learning materials which reflect best practice in research data management grounded in three disciplinary contexts: social science, clinical psychology, and geoscience. The resulting materials will be embedded in three participating postgraduate programmes and made available through the university's Transkills programme for use by all postgraduate and early career researchers as well as made available generally through an open license and deposited in JorumOpen, a national repository for open educational resources. In addition to web-based 'chapters' that students can work through at their own pace, the course will include video interviews with leading academics about data management challenges, and practical exercises in handling data in four software analysis environments: SPSS, NVivo, R and ArcGIS. The project is a partnership between the Data Library in Information Services and the Institute for Academic Development, at the University of Edinburgh and is funded by JISC as a part of its UK programme, Managing Research Data.

This paper will look at the new Criminal Justice Data Archive for Australia, which is being developed as part of the Australian Data Archive. Among the topics covered will be the various types of data being included, and the sources of the datasets. The archive draws on datasets from multiple agencies in both State and Federal jurisdictions, and the paper will discuss the complexities involved in obtaining and delivering data from a range of different government bodies. The new archive is a partnership between the Australian Data Archive and the National Criminal Justice Research Data Network. The paper will discuss the respective roles of the two partners and their expectations from the service. Requirements and arrangements for managing security and access will also be examined. We will conclude by comparing the Australian service with international models, especially the U.S. National Archive of Criminal Justice Data.

Considerable demand exists from researchers for detailed data collected by European-wide surveys. However, the benefits from analysing such data are little realised because of poor access. The problem is often compounded by the risk-averse nature of data owners. Researchers face considerable hurdles in accessing data, especially from more than one country - often they must travel considerable distances to access data at 'safe rooms' located in National Statistics Institutes, which consumes precious time and money, and deters young researchers. Fortunately, Research Data Centres (RDCs) have emerged which provide innovative access solutions for the convenience of researchers and data owners. This paper considers how more extensive 'Decentralised Access' could work in practice. We explore how the research community can reap benefits from an integrated network of RDCs, striving to deliver access to data of different sensitivities, and from different countries, throughout the European Union. We argue that 'friendly' competition amongst RDCs to provide better and innovative solutions for researchers and data owners can only lead to better provision of access to micro-data.

Many studies have shown an increasing use of Online Social Networks for scientific work. Social networking platforms therefore provide the strategic chance of enhancing knowledge exchanging and networking processes in science by getting into a digital dialogue with a broader community and, in particular, by making use of the viral effects of Online Social Networks. However, Online Social Networks are usually not linked with scientific databases such that larger amounts of scientific content cannot easily be transferred to and shared via Online Social Networks. The major goal of ScholarLib therefore is to provide a framework for close coupling of Online Social Networks with scientific information portals. The goal is to make search functionality of portals available at Online Social Networks and, the other way around, to enrich scientific portals by social information provided by Online Social Networks. The paper presents a first prototype that links existing social networking platforms (e.g. Xing, iversity) to the German Social Science information portal sowiport, allowing the users in Online Social Networks to search, share and annotate publications provided by sowiport.