Scaling Up Perma.cc: Ensuring the Integrity of the Digital Scholarly Record

Authors: Kim Dulin and Adam Ziegler

Abstract: IMLS awarded the Harvard Library Innovation Lab a National Digital Platform grant to further develop the Lab’s Perma.cc web archiving service. The funds will be used to provide technical enhancements to support an expanded user base, aid in outreach efforts to implement Perma.cc in the nation’s academic libraries, and develop a commercial model for the service that will sustain the free service for the academic community. Perma.cc is a web archiving tool that puts the ability to archive a source in the hands of the author who is citing it. Once saved, Perma.cc assigns the source a new URL, which can be added to the original URL cited in the author’s work, so that if the original link rots or is changed the Perma.cc URL will still lead to the original source. Perma.cc is being used widely in the legal community with great success; the IMLS grant will make the tool available to other areas of scholarship where link rot occurs and will provide a solution for those in the commercial arena who do not currently have one.

Citation: Dulin, K., & Ziegler, A. (2017). Scaling Up Perma.cc: Ensuring the Integrity of the Digital Scholarly Record. D-Lib Magazine, 23(5/6). https://doi.org/10.1045/may2017-dulin

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ReplicationWiki: Improving Transparency in Social Sciences Research

Author: Jan H. Höffler

Abstract: In empirical social sciences research, only a small minority of study material is publicly available, therefore allowing full replication. The number of replication studies published in academic journals is even smaller. Our wiki documents the results of more than 300 replications, so far mainly in economics. It includes a database of more than 2,600 empirical studies. For each study we provide information about the availability of material for replication. This helps instructors to identify practical examples for courses focusing on empirical methods or on particular topics. Furthermore, it gives researchers better access to information on previous studies they can build on or compare their work with. We provide an overview of journals and their policies regarding data availability and publication of replications. The project has attracted interest from various fields and is open for expansion.

Citation: Jan H. Höffler. (2017). ReplicationWiki: Improving Transparency in Social Sciences Research. D-LIB Magazine, 23(3/4). https://doi.org/10.1045/march2017-hoeffler

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Opening the Publication Process with Executable Research Compendia

Authors: Daniel Nüst, Markus Konkol, Edzer Pebesma, Christian Kray, Marc Schutzeichel, Holger Przibytzin, Jörg Lorenz

 

Abstract: A strong movement towards openness has seized science. Open data and methods, open source software, Open Access, open reviews, and open research platforms provide the legal and technical solutions to new forms of research and publishing. However, publishing reproducible research is still not common practice. Reasons include a lack of incentives and a missing standardized infrastructure for providing research material such as data sets and source code together with a scientific paper. Therefore we first study fundamentals and existing approaches. On that basis, our key contributions are the identification of core requirements of authors, readers, publishers, curators, as well as preservationists and the subsequent description of an executable research compendium (ERC). It is the main component of a publication process providing a new way to publish and access computational research. ERCs provide a new standardisable packaging mechanism which combines data, software, text, and a user interface description. We discuss the potential of ERCs and their challenges in the context of user requirements and the established publication processes. We conclude that ERCs provide a novel potential to find, explore, reuse, and archive computer-based research.

 

Citation: Nüst, D, Konkol, M, Pebsema, E, Kray, C, Schutzeichel, M, Przibytzin, H, Lorenz, J. (2017) Opening the Publication Process with Executable Research Compendia D-Lib Magazine 23(1-2). https://doi.org/10.1045/january2017-nuest

 

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The Scholix Framework for Interoperability in Data-Literature Information Exchange

Authors: Adrian Burton, Amir Aryani, Hylke Koers, Paolo Manghi, Sandro La Bruzzo, Markus Stocker, Michael Diepenbroek, Uwe Schindler, Martin Fenner

 

Abstract: The Scholix Framework (SCHOlarly LInk eXchange) is a high level interoperability framework for exchanging information about the links between scholarly literature and data, as well as between datasets. Over the past decade, publishers, data centers, and indexing services have agreed on and implemented numerous bilateral agreements to establish bidirectional links between research data and the scholarly literature. However, because of the considerable differences inherent to these many agreements, there is very limited interoperability between the various solutions. This situation is fueling systemic inefficiencies and limiting the value of these, separated, sets of links. Scholix, a framework proposed by the RDA/WDS Publishing Data Services working group, envisions a universal interlinking service and proposes the technical guidelines of a multi-hub interoperability framework. Hubs are natural collection and aggregation points for data-literature information from their respective communities. Relevant hubs for the communities of data centers, repositories, and journals include DataCite, OpenAIRE, and Crossref, respectively. The framework respects existing community-specific practices while enabling interoperability among the hubs through a common conceptual model, an information model and open exchange protocols. The proposed framework will make research data, and the related literature, easier to find and easier to interpret and reuse, and will provide additional incentives for researchers to share their data.

 

Citation: Burton, A, Aryani, A, Koers, H, Manghi, P, La Burzzo, S, Stocker, M, Diepenbroek, M, Schindler, U, Fenner, M. (2017) The Scholix Framework for Interoperability in Data-Literature Information Exchange D-Lib Magazine 23(1-2). https://doi.org/10.1045/january2017-burton

 

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Assessing Stewardship Maturity of the Global Historical Climatology Network-Monthly (GHCN-M) Dataset: Use Case Study and Lessons Learned

Authors: Ge Peng, Jay Lawrimore, Valerie Toner, Christina Lief, Richard Baldwin, Nancy Ritchey, Danny Brinegar, Stephen A. Del Greco

 

Abstract: Assessing stewardship maturity — the current state of how datasets are documented, preserved, stewarded, and made accessible publicly — is a critical step towards meeting U.S. federal regulations, organizational requirements, and user needs. The scientific data stewardship maturity matrix (DSMM), developed in partnership with NOAA’s National Centers of Environmental Information (NCEI) and the Cooperative Institute for Climate and Satellites-North Carolina (CICS-NC), provides a consistent framework for assessing stewardship maturity of individual Earth Science datasets and capturing justifications for transparency. The consolidated stewardship maturity information will allow users and decision-makers to make informed use decisions based on their unique data needs. This DSMM was applied to a widely utilized monthly-land-surface-temperature dataset derived from the Global Historical Climatology Network (GHCN-M). This paper describes the stewardship maturity ratings of GHCN-M version 3 and provides actionable recommendations for improving the maturity of the dataset. The results from the use case study show that an application of DSMM like this one is useful to people who produce or care for digital environmental datasets. Assessments can identify the strengths and weaknesses of an individual dataset or organization’s preservation and stewardship practices, including how information about the dataset is integrated into different systems.

 

Citation: Peng, G., Lawrimore, J., Toner, V., Lief, C., Baldwin, R., Ritchey, N., . . . Greco, S. A. (2016). Assessing Stewardship Maturity of the Global Historical Climatology Network-Monthly (GHCN-M) Dataset: Use Case Study and Lessons Learned. D-Lib Magazine, 22(11/12). doi.org/10.1045/november2016-peng

 

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