Special Issue "Research Data Management"

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (31 January 2016)

Special Issue Editors

Guest Editor
Dr. Constanze Curdt

GIS & RS Group, Institute of Geography, University of Cologne, D-50923 Cologne, Germany
Website | E-Mail
Interests: research data management, metadata, spatial data infrastructures
Guest Editor
Dipl.-Geogr. Christian Willmes

GIS & RS Group, Institute of Geography, University of Cologne, D-50923 Cologne, Germany
Website | E-Mail
Interests: internet based geoinformation systems, spatio-temporal data modeling, semantic data interoperability, spatial data infrastructures
Guest Editor
Prof. Dr. Georg Bareth

GIS & RS Group, Institute of Geography, University of Cologne, D-50923 Cologne, Germany
Website | E-Mail
Fax: +49-221-470-1638
Interests: low-weight UAVs; hyperspectral and multisepctral remote sensing; field spectrometry; terrestrial lasercanning; 3D analysis; plant biomass; plant nitrogen; change detection; matter fluxes; precision agriculture; spatial data management

Special Issue Information

Dear Colleagues,

Digital information and data have experienced rapid growth in many disciplines over the last decade as a consequence of the fourth digital information revolution. New technologies have facilitated the automatic and digital creation of more data. Thus, research data management (RDM), as well as digital curation and preservation, have become more important. As a result, a variety of infrastructures supporting RDM (e.g., data repositories, archives or project databases) have emerged in recent years. These infrastructures handle research data within the context of project-based, national, international or institutional approaches (e.g., at universities). In the context of spatial data handling, several spatial data infrastructures (SDI) have been established. Funding organizations, like the German Research Foundation or the National Science Foundation, are aware of the importance of RDM. Likewise, several initiatives, such as the global Research Data Alliance or the German Priority Initiative, “Digital Information,” emphasize the importance of RDM for the conduct of science. Thus, they request the preparation of data management plans and support the set-up of RDM infrastructures.

This Special Issues shall explore new trends and developments in the management of data (e.g., research data, spatial data created in a specific or interdisciplinary context, etc.). All kinds of data intensive sciences (e-Science) will be considered, as well as aspects of data handling and processing that concern the conduct of research. We invite original research contributions covering a broad variety of aspects related to data management in different research fields and organizations. We encourage papers across disciplines that focus on the themes of this Special Issue. Topics include, but are not limited to:

  • Management of data resulting from various disciplines
  • Case studies of institutional, national or international infrastructures supporting RDM (g., data repositories, project databases, data archives, data platforms)
  • Data life cycle management
  • Data publishing (g., forms, metrics)
  • Data curation and preservation
  • Metadata and Metadata Schemas for RDM
  • Spatial Data Infrastructures (SDI) and spatial data handling
  • Data management services
  • Data processing and visualization
  • Linked Sciences, linked data, semantic interoperability
  • Data models and vocabularies
  • Semantic e-Science
  • Approaches in training for RDM

 

In addition, selected and extended papers, originally presented at the 2nd Data Management Workshop (http://www.tr32db.uni-koeln.de/workshop2014/) at the University of Cologne (Germany), will be included in this Special Issue.

Dr. Constanze Curdt
Dipl.-Geogr. Christian Willmes
Prof. Dr. Georg Bareth
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Management of data resulting from various disciplines
  • Case studies of institutional, national or international infrastructures supporting RDM (g., data repositories, project databases, data archives, and data platforms)
  • Data life cycle management
  • Data publishing (g., forms, metrics, etc.)
  • Data curation and preservation
  • Metadata and Metadata Schemas for RDM
  • Spatial Data Infrastructures (SDI) and spatial data handling
  • Data management services
  • Data processing and visualization
  • Linked Sciences, linked data, semantic interoperability
  • Data models and vocabularies
  • Semantic e-Science
  • Approaches in training for RDM

Published Papers (16 papers)

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Open AccessArticle Data Autodiscovery—The Role of the OPD
ISPRS Int. J. Geo-Inf. 2016, 5(10), 167; doi:10.3390/ijgi5100167
Received: 29 January 2016 / Revised: 12 September 2016 / Accepted: 18 September 2016 / Published: 22 September 2016
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Abstract
The importance of open data and the benefits it can offer have received recognition on the international stage with the signing of the G8 Open Data Charter in June 2013. The charter has an early focus on 14 high value areas, including transport
[...] Read more.
The importance of open data and the benefits it can offer have received recognition on the international stage with the signing of the G8 Open Data Charter in June 2013. The charter has an early focus on 14 high value areas, including transport and education, where governments have greater influence. In the UK, we have seen the funding of the Open Data Institute (ODI) with a remit to support small and medium sized enterprises (SMEs) in identifying benefits from using open data, whereas, within HE, open data discussion is in its infancy although is acknowledged as a sector challenge by the Russell Group of universities. There is an evident need for the academic community to influence the adoption of applications using linked open data techniques in data management and service delivery. This article introduces the concept of “data autodiscovery”, highlighting the role of the Organisation Profile Document (OPD) and its contribution to the early success of the UK National Equipment Portal, equipment.data, along with discussing the need for greater dialogue in linked and open data standards development. Full article
(This article belongs to the Special Issue Research Data Management)
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Open AccessArticle The Göttingen eResearch Alliance: A Case Study of Developing and Establishing Institutional Support for Research Data Management
ISPRS Int. J. Geo-Inf. 2016, 5(8), 133; doi:10.3390/ijgi5080133
Received: 1 March 2016 / Revised: 28 June 2016 / Accepted: 14 July 2016 / Published: 1 August 2016
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Abstract
The Göttingen eResearch Alliance is presented as a case study for establishing institutional support for research data management within the context of the Göttingen Campus, a particular alliance of several research institutes at Göttingen. The cross-cutting, “horizontal” approach of the Göttingen eResearch Alliance,
[...] Read more.
The Göttingen eResearch Alliance is presented as a case study for establishing institutional support for research data management within the context of the Göttingen Campus, a particular alliance of several research institutes at Göttingen. The cross-cutting, “horizontal” approach of the Göttingen eResearch Alliance, established by two research-oriented infrastructure providers, a research library and a computing and IT competence center, aims to coordinate Campus-led activities to establish sustainable and innovative services to support all phases of the research data life cycle. In this article, the core activities of the first phase aimed at developing a modular approach to provide support for research data management to researchers will be described. It closes with lessons learned and an outlook on future activities. Full article
(This article belongs to the Special Issue Research Data Management)
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Open AccessArticle The HD(CP)2 Data Archive for Atmospheric Measurement Data
ISPRS Int. J. Geo-Inf. 2016, 5(7), 124; doi:10.3390/ijgi5070124
Received: 28 January 2016 / Revised: 30 June 2016 / Accepted: 8 July 2016 / Published: 19 July 2016
Cited by 4 | PDF Full-text (2331 KB) | HTML Full-text | XML Full-text
Abstract
The archiving of scientific data is a sophisticated mission in nearly all research projects. In this paper, we introduce a new online archive of atmospheric measurement data from the "High definition clouds and precipitation for advancing climate prediction" (HD(CP)2) research initiative.
[...] Read more.
The archiving of scientific data is a sophisticated mission in nearly all research projects. In this paper, we introduce a new online archive of atmospheric measurement data from the "High definition clouds and precipitation for advancing climate prediction" (HD(CP)2) research initiative. The project data archive is quality managed, easy to use, and is now open for other atmospheric research data. The archive’s creation was already taken into account during the HD(CP)2 project planning phase and the necessary resources were granted. The funding enabled the HD(CP)2 project to build a sound archive structure, which guarantees that the collected data are accessible for all researchers in the project and beyond. Full article
(This article belongs to the Special Issue Research Data Management)
Open AccessArticle River Basin Information System: Open Environmental Data Management for Research and Decision Making
ISPRS Int. J. Geo-Inf. 2016, 5(7), 123; doi:10.3390/ijgi5070123
Received: 25 March 2016 / Revised: 14 June 2016 / Accepted: 11 July 2016 / Published: 18 July 2016
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Abstract
An open, standardized data management and related service infrastructure is a crucial requirement for a seamless storage and exchange of data and information within research projects, for the dissemination of project results and for their application in decision making processes. However, typical project
[...] Read more.
An open, standardized data management and related service infrastructure is a crucial requirement for a seamless storage and exchange of data and information within research projects, for the dissemination of project results and for their application in decision making processes. However, typical project databases often refer to only one research project and are limited to specific purposes. Once implemented, those systems are often not further maintained and updated, rendering the stored information useless once the system stops operating. The River Basin Information System (RBIS) presented here is designed to fit not only the requirements of one research project, but focuses on generic functions, extensibility and standards compliance typically found in interdisciplinary environmental research. Developed throughout more than 10 years of research cooperation worldwide, RBIS is designed to manage different types of environmental data with and without spatial context together with a rich set of metadata. Beside data management and storage, RBIS provides functions for the visualization, linking, analysis and processing of different types of data to support research, decision making, result dissemination and information discovery for all kinds of users. The focus of this paper is on the description of the technical implementation and the presentation of functions. This will be complemented by an overview of example applications and experiences during RBIS development and operation. Full article
(This article belongs to the Special Issue Research Data Management)
Open AccessArticle Towards Narrowing the Curation Gap—Theoretical Considerations and Lessons Learned from Decades of Practice
ISPRS Int. J. Geo-Inf. 2016, 5(6), 91; doi:10.3390/ijgi5060091
Received: 31 January 2016 / Revised: 4 May 2016 / Accepted: 3 June 2016 / Published: 14 June 2016
Cited by 1 | PDF Full-text (3059 KB) | HTML Full-text | XML Full-text
Abstract
Research as a digital enterprise has created new, often poorly addressed challenges for the management and curation of research to ensure continuity, transparency, and accountability. There is a common misunderstanding that curation can be considered at a later point in the research cycle
[...] Read more.
Research as a digital enterprise has created new, often poorly addressed challenges for the management and curation of research to ensure continuity, transparency, and accountability. There is a common misunderstanding that curation can be considered at a later point in the research cycle or delegated or that it is too burdensome or too expensive due to a lack of efficient tools. This creates a curation gap between research practice and curation needs. We argue that this gap can be narrowed if curators provide attractive support that befits research needs and if researchers consistently manage their work according to generic concepts consistently from the beginning. A rather uniquely long-term case study demonstrates how such concepts have helped to pragmatically implement a research practice intentionally using only minimalist tools for sustained, self-contained archiving since 1989. The paper sketches the concepts underlying three core research activities. (i) handling of research data, (ii) reference management as part of scholarly publishing, and (iii) advancing theories through modelling and simulation. These concepts represent a universally transferable best research practice, while technical details are obviously prone to continuous change. We hope it stimulates researchers to manage research similarly and that curators gain a better understanding of the curation challenges research practice actually faces. Full article
(This article belongs to the Special Issue Research Data Management)
Open AccessArticle Requirements on Long-Term Accessibility and Preservation of Research Results with Particular Regard to Their Provenance
ISPRS Int. J. Geo-Inf. 2016, 5(4), 49; doi:10.3390/ijgi5040049
Received: 29 January 2016 / Revised: 15 March 2016 / Accepted: 28 March 2016 / Published: 11 April 2016
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Abstract
Since important national and international funders of research projects require statements on the long-term accessibility of research results, many new solutions appeared to fulfil these demands. The solutions are implemented on various scopes, starting from specific solutions for one research group up to
[...] Read more.
Since important national and international funders of research projects require statements on the long-term accessibility of research results, many new solutions appeared to fulfil these demands. The solutions are implemented on various scopes, starting from specific solutions for one research group up to solutions with a national focus (i.e., the RADAR project). While portals for globally standardized research data (e.g., climate data) are available, there is currently no provision for the large amount of data resulting from specialized research in individual research foci, the so called long-tail of sciences. In this article we describe the considerations regarding the implementation of a local research data repository for the Collaborative Research Centre (CRC) 840. The main focus will be on the examination of requirements for, and an agenda of, a possible technical implementation. Requirements were derived from a more theoretical examination of similar projects and relevant literature, diverse discussions with researchers and project leaders, by analysis of existing publication data, and finally the prototypical implementation with refining iterations. Notably, the discussions with the researchers lead to new features going beyond the challenges of the mere long-term preservation of research data. Besides the need for an infrastructure that permits long-term preservation and retrieval of research data, our system will allow the reconstruction of the complete provenance of published research results. This requirement is a serious diversification of the problem, because it creates the need to qualify additional transformation data, describing the transformation process from primary research data to research results. Full article
(This article belongs to the Special Issue Research Data Management)
Open AccessArticle Open Data and Beyond
ISPRS Int. J. Geo-Inf. 2016, 5(4), 48; doi:10.3390/ijgi5040048
Received: 22 January 2016 / Revised: 11 March 2016 / Accepted: 22 March 2016 / Published: 7 April 2016
Cited by 2 | PDF Full-text (1929 KB) | HTML Full-text | XML Full-text
Abstract
In recent years, there has been an increasing trend of releasing public sector information as open data. Governments worldwide see the potential benefits of opening up their data. The potential benefits are more transparency, increased governmental efficiency and effectiveness, and external benefits, including
[...] Read more.
In recent years, there has been an increasing trend of releasing public sector information as open data. Governments worldwide see the potential benefits of opening up their data. The potential benefits are more transparency, increased governmental efficiency and effectiveness, and external benefits, including societal and economic benefits. The private sector also recognizes potential benefits of making their datasets available as open data. One such company is Liander, an energy network administrator in the Netherlands. Liander views open data as a contributing factor to energy conservation. However, to date there has been little research done into the actual effects of open data. This research has developed a monitoring framework to assess the effects of open data, and has applied the framework to Liander’s small-scale energy consumption dataset. Full article
(This article belongs to the Special Issue Research Data Management)
Open AccessArticle Migrating 2 and 3D Datasets: Preserving AutoCAD at the Archaeology Data Service
ISPRS Int. J. Geo-Inf. 2016, 5(4), 44; doi:10.3390/ijgi5040044
Received: 25 January 2016 / Revised: 7 March 2016 / Accepted: 16 March 2016 / Published: 25 March 2016
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Abstract
The Archaeology Data Service (ADS) is a digital archive that has been promoting good practice in the use of digital archaeological data and supporting research, learning and teaching with high quality and dependable digital resources for twenty years. The ADS does this by
[...] Read more.
The Archaeology Data Service (ADS) is a digital archive that has been promoting good practice in the use of digital archaeological data and supporting research, learning and teaching with high quality and dependable digital resources for twenty years. The ADS does this by preserving digital data in the long-term and by promoting and disseminating, open and free datasets, gathered from all sectors of archaeology. An integral component of the ADS remit has been the life-cycle principle of preservation, curation and dissemination of data in order to enable re-use. The ADS practices a combination of normalization, version migration, format migration and refreshment for the active management and ongoing preservation of all archived data types. This paper highlights the importance of the ongoing management of research data for long-term preservation. In particular this paper focuses on the challenges of migrating spatial data, specifically Computer Aided Design (CAD) files. Successful data migration of these files ensures that data is accessible and usable, and provides many opportunities through data re-use to combine and re-interrogate datasets, allowing new archaeological interpretations to be developed. Full article
(This article belongs to the Special Issue Research Data Management)
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Open AccessArticle Research Data Management Training for Geographers: First Impressions
ISPRS Int. J. Geo-Inf. 2016, 5(4), 40; doi:10.3390/ijgi5040040
Received: 21 September 2015 / Revised: 2 February 2016 / Accepted: 17 February 2016 / Published: 23 March 2016
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Abstract
Sharing and secondary analysis of data have become increasingly important for research. Especially in geography, the collection of digital data has grown due to technological changes. Responsible handling and proper documentation of research data have therefore become essential for funders, publishers and higher
[...] Read more.
Sharing and secondary analysis of data have become increasingly important for research. Especially in geography, the collection of digital data has grown due to technological changes. Responsible handling and proper documentation of research data have therefore become essential for funders, publishers and higher education institutions. To achieve this goal, universities offer support and training in research data management. This article presents the experiences of a pilot workshop in research data management, especially for geographers. A discipline-specific approach to research data management training is recommended. The focus of this approach increases researchers’ interest and allows for more specific guidance. The instructors identified problems and challenges of research data management for geographers. In regards to training, the communication of benefits and reaching the target groups seem to be the biggest challenges. Consequently, better incentive structures as well as communication channels have to be established. Full article
(This article belongs to the Special Issue Research Data Management)
Open AccessArticle Semantic Specification of Data Types for a World of Open Data
ISPRS Int. J. Geo-Inf. 2016, 5(3), 38; doi:10.3390/ijgi5030038
Received: 10 December 2015 / Revised: 25 February 2016 / Accepted: 8 March 2016 / Published: 16 March 2016
Cited by 2 | PDF Full-text (1797 KB) | HTML Full-text | XML Full-text
Abstract
Data interoperability is an ongoing challenge for global open data initiatives. The machine-readable specification of data types for datasets will help address interoperability issues. Data types have typically been at the syntactical level such as integer, float and string, etc. in programming languages.
[...] Read more.
Data interoperability is an ongoing challenge for global open data initiatives. The machine-readable specification of data types for datasets will help address interoperability issues. Data types have typically been at the syntactical level such as integer, float and string, etc. in programming languages. The work presented in this paper is a model design for the semantic specification of data types, such as a topographic map. The work was conducted in the context of the Semantic Web. The model differentiates the semantic data type from the basic data type. The former are instances (e.g., topographic map) of a specific data type class that is defined in the developed model. The latter are classes (e.g., Image) of resource types in existing ontologies. A data resource is an instance of a basic data type and is tagged with one or more specific data types. The implementation of the model is given within an existing production data portal that enables one to register specific data types and use them to annotate data resources. Data users can obtain explicating assumptions or information inherent in a dataset through the specific data types of that dataset. The machine-readable information of specific data types also paves the way for further studies, such as dataset recommendation. Full article
(This article belongs to the Special Issue Research Data Management)
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Open AccessArticle The Strategy for the Development of the Infrastructure for Spatial Information in the Czech Republic
ISPRS Int. J. Geo-Inf. 2016, 5(3), 33; doi:10.3390/ijgi5030033
Received: 30 November 2015 / Revised: 20 January 2016 / Accepted: 22 February 2016 / Published: 10 March 2016
Cited by 3 | PDF Full-text (1288 KB) | HTML Full-text | XML Full-text
Abstract
Spatial information is often not effectively handled and used, e.g., in public administration. The key reason is that information about what spatial data exists, and where and under which circumstances it can be used, is missing. This leads to a situation whereby data
[...] Read more.
Spatial information is often not effectively handled and used, e.g., in public administration. The key reason is that information about what spatial data exists, and where and under which circumstances it can be used, is missing. This leads to a situation whereby data are gathered and maintained multiple times. In October 2014, the Czech government approved the conception of The Strategy for the Development of the Infrastructure for Spatial Information in the Czech Republic to 2020 (GeoInfoStrategy), which serves as a basis for the National Spatial Data Infrastructure (NSDI). Furthermore, in June 2015 the GeoInfoStrategy Action Plan was approved. The vision of the GeoInfoStrategy is that the Czech Republic will use spatial information effectively by 2020. The innovative approach of the GeoInfoStrategy to build the NSDI includes cooperation between all parties—not only public administration, but also the private sector, academia, professional associations and user communities. The principles defined in the GeoInfoStrategy are general and can serve as best practice for other countries building an NSDI that should meet the requirements of all target groups working with spatial information. Full article
(This article belongs to the Special Issue Research Data Management)
Open AccessArticle Open Polar Server (OPS)—An Open Source Infrastructure for the Cryosphere Community
ISPRS Int. J. Geo-Inf. 2016, 5(3), 32; doi:10.3390/ijgi5030032
Received: 24 November 2015 / Revised: 4 February 2016 / Accepted: 29 February 2016 / Published: 9 March 2016
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Abstract
The Center for Remote Sensing of Ice Sheets (CReSIS) at the University of Kansas has collected approximately 1000 terabytes (TB) of radar depth sounding data over the Arctic and Antarctic ice sheets since 1993 in an effort to map the thickness of the
[...] Read more.
The Center for Remote Sensing of Ice Sheets (CReSIS) at the University of Kansas has collected approximately 1000 terabytes (TB) of radar depth sounding data over the Arctic and Antarctic ice sheets since 1993 in an effort to map the thickness of the ice sheets and ultimately understand the impacts of climate change and sea level rise. In addition to data collection, the storage, management, and public distribution of the dataset are also primary roles of the CReSIS. The Open Polar Server (OPS) project developed a free and open source infrastructure to store, manage, analyze, and distribute the data collected by CReSIS in an effort to replace its current data storage and distribution approach. The OPS infrastructure includes a spatial database management system (DBMS), map and web server, JavaScript geoportal, and MATLAB application programming interface (API) for the inclusion of data created by the cryosphere community. Open source software including GeoServer, PostgreSQL, PostGIS, OpenLayers, ExtJS, GeoEXT and others are used to build a system that modernizes the CReSIS data distribution for the entire cryosphere community and creates a flexible platform for future development. Usability analysis demonstrates the OPS infrastructure provides an improved end user experience. In addition, interpolating glacier topography is provided as an application example of the system. Full article
(This article belongs to the Special Issue Research Data Management)
Open AccessArticle A Semi-Automated Workflow Solution for Data Set Publication
ISPRS Int. J. Geo-Inf. 2016, 5(3), 30; doi:10.3390/ijgi5030030
Received: 20 December 2015 / Revised: 18 February 2016 / Accepted: 25 February 2016 / Published: 8 March 2016
Cited by 1 | PDF Full-text (4072 KB) | HTML Full-text | XML Full-text
Abstract
To address the need for published data, considerable effort has gone into formalizing the process of data publication. From funding agencies to publishers, data publication has rapidly become a requirement. Digital Object Identifiers (DOI) and data citations have enhanced the integration and availability
[...] Read more.
To address the need for published data, considerable effort has gone into formalizing the process of data publication. From funding agencies to publishers, data publication has rapidly become a requirement. Digital Object Identifiers (DOI) and data citations have enhanced the integration and availability of data. The challenge facing data publishers now is to deal with the increased number of publishable data products and most importantly the difficulties of publishing diverse data products into an online archive. The Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC), a NASA-funded data center, faces these challenges as it deals with data products created by individual investigators. This paper summarizes the challenges of curating data and provides a summary of a workflow solution that ORNL DAAC researcher and technical staffs have created to deal with publication of the diverse data products. The workflow solution presented here is generic and can be applied to data from any scientific domain and data located at any data center. Full article
(This article belongs to the Special Issue Research Data Management)
Open AccessArticle The RADAR Project—A Service for Research Data Archival and Publication
ISPRS Int. J. Geo-Inf. 2016, 5(3), 28; doi:10.3390/ijgi5030028
Received: 26 November 2015 / Revised: 20 January 2016 / Accepted: 17 February 2016 / Published: 4 March 2016
PDF Full-text (937 KB) | HTML Full-text | XML Full-text
Abstract
The aim of the RADAR (Research Data Repository) project is to set up and establish an infrastructure that facilitates research data management: the infrastructure will allow researchers to store, manage, annotate, cite, curate, search and find scientific data in a digital platform available
[...] Read more.
The aim of the RADAR (Research Data Repository) project is to set up and establish an infrastructure that facilitates research data management: the infrastructure will allow researchers to store, manage, annotate, cite, curate, search and find scientific data in a digital platform available at any time that can be used by multiple (specialized) disciplines. While appropriate and innovative preservation strategies and systems are in place for the big data communities (e.g., environmental sciences, space, and climate), the stewardship for many other disciplines, often called the “long tail research domains”, is uncertain. Funded by the German Research Foundation (DFG), the RADAR collaboration project develops a service oriented infrastructure for the preservation, publication and traceability of (independent) research data. The key aspect of RADAR is the implementation of a two-stage business model for data preservation and publication: clients may preserve research results for up to 15 years and assign well-graded access rights, or to publish data with a DOI assignment for an unlimited period of time. Potential clients include libraries, research institutions, publishers and open platforms that desire an adaptable digital infrastructure to archive and publish data according to their institutional requirements and workflows. Full article
(This article belongs to the Special Issue Research Data Management)
Open AccessArticle panMetaDocs, eSciDoc, and DOIDB—An Infrastructure for the Curation and Publication of File-Based Datasets for GFZ Data Services
ISPRS Int. J. Geo-Inf. 2016, 5(3), 25; doi:10.3390/ijgi5030025
Received: 30 November 2015 / Revised: 19 January 2016 / Accepted: 17 February 2016 / Published: 2 March 2016
Cited by 1 | PDF Full-text (2129 KB) | HTML Full-text | XML Full-text
Abstract
The GFZ German Research Centre for Geosciences is the national laboratory for Geosciences in Germany. As part of the Helmholtz Association, providing and maintaining large-scale scientific infrastructures are an essential part of GFZ activities. This includes the generation of significant volumes and numbers
[...] Read more.
The GFZ German Research Centre for Geosciences is the national laboratory for Geosciences in Germany. As part of the Helmholtz Association, providing and maintaining large-scale scientific infrastructures are an essential part of GFZ activities. This includes the generation of significant volumes and numbers of research data, which subsequently become source materials for data publications. The development and maintenance of data systems is a key component of GFZ Data Services to support state-of-the-art research. A challenge lies not only in the diversity of scientific subjects and communities, but also in different types and manifestations of how data are managed by research groups and individual scientists. The data repository of GFZ Data Services provides a flexible IT infrastructure for data storage and publication, including minting of digital object identifiers (DOI). It was built as a modular system of several independent software components linked together through Application Programming Interfaces (APIs) provided by the eSciDoc framework. Principal application software are panMetaDocs for data management and DOIDB for logging and moderating data publications activities. Wherever possible, existing software solutions were integrated or adapted. A summary of our experiences made in operating this service is given. Data are described through comprehensive landing pages and supplementary documents, like journal articles or data reports, thus augmenting the scientific usability of the service. Full article
(This article belongs to the Special Issue Research Data Management)

Other

Jump to: Research

Open AccessProject Report Data Management in Collaborative Interdisciplinary Research Projects—Conclusions from the Digitalization of Research in Sustainable Manufacturing
ISPRS Int. J. Geo-Inf. 2016, 5(4), 41; doi:10.3390/ijgi5040041
Received: 29 January 2016 / Revised: 10 March 2016 / Accepted: 16 March 2016 / Published: 23 March 2016
PDF Full-text (2314 KB) | HTML Full-text | XML Full-text
Abstract
As research topics become increasingly complex, large scale interdisciplinary research projects are commonly established to foster cross-disciplinary cooperation and to utilize potential synergies. In the case of the Collaborative Research Center (CRC) 1026, 19 individual projects from different disciplines are brought together to
[...] Read more.
As research topics become increasingly complex, large scale interdisciplinary research projects are commonly established to foster cross-disciplinary cooperation and to utilize potential synergies. In the case of the Collaborative Research Center (CRC) 1026, 19 individual projects from different disciplines are brought together to investigate perspectives and solutions for sustainable manufacturing. Beside overheads regarding the coordination of activities and communication, such interdisciplinary projects are also facing challengs regarding data management. For exchange and combination of research results, data from individual projects have to be stored systematically, categorized, and linked according to the logical interrelations of the involved disciplinary knowledge domains. In the CRC 1026, the project for information infrastructure observed and analysed collaboration practices and developed IT-supported solutions to facilitate and foster research collaboration. Data management measures in this period were mainly focused on building a shared conceptual framework, and the organization of task related data. For the former aspect, an ontology basesd apporach was developed and prototypically implemented. For the latter aspect, a message board integrated task management system was developed and applied. Full article
(This article belongs to the Special Issue Research Data Management)

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