New roles of research data infrastructure in research paradigm evolution

Research data infrastructures form the cornerstone in both cyber and physical spaces,driving the progression of the data-intensive scientific research paradigm.This opinion paper presents an overview of global research data infrastructure,drawing insights from national roadmaps and strategic documents related to research data infrastructure.It emphasizes the pivotal role of research data infrastructures by delineating four new missions aimed at positioning them at the core of the current scientific research and communication ecosystem.The four new missions of research data infrastructures are:(1)as a pioneer,to transcend the disciplinary border and address complex,cutting-edge scientific and social challenges with problem-and data-oriented insights;(2)as an architect,to establish a digital,intelligent,flexible research and knowledge services environment;(3)as a platform,to foster the high-end academic communication;(4)as a coordinator,to balance scientific openness with ethics needs.

Assessing the impact of heavy rainfall on the Newcastle upon Tyne transport network using a geospatial data infrastructure

Extreme weather conditions can adversely impact transport networks and driver behaviour,leading to variations in traffic volumes and travel times and increased accident rates.Emergency services that need to navigate to an accident site in the shortest possible time require real-time location-based weather and traffic information to coordinate their response.We therefore require historical and high-resolution temporal real-time data to identify districts and roads that are prone to different types of incidents during inclement weather and to better support emergency services in their decision-making.However,real-time assessment of the current transport network requires a dense sensor network that can provide high-resolution data using internet-enabled technology.In this research,we demonstrate how we obtain historical time-series and real-time data from sensors oper-ated by the Tyne and Wear Urban Traffic and Management Control Centre and the Urban Observatory based at Newcastle upon Tyne,UK.In the study,we assess the impact of rainfall on traffic volume and travel time,and the cascading impacts during a storm event in Newcastle during early October 2021.We also estimate the economic cost of the storm,with regards to transport disruption,as the cost of travel,using the“value of time”based on Department for Transport guidelines(2021).Using spatial-temporal analysis,we chose three locations to demonstrate how traffic parameters varied at different times throughout the storm.We identified increases in travel times of up to 600%and decreases in traffic volume of up to 100%when compared to historical data.Further,we assessed cascading impacts at important traffic locations and their broader implications for city areas.We estimated that the storm’s economic impact on one sensor location increased by up to 370%of the reference value.By analysing historical and real-time data,we detected and explained patterns in the data that would have remained uncovered if they had been examined individually.The combination of different data sources,such as traffic and weather,helps explain temporal fluctuations at locations where incidents were recorded near traffic detectors.We anticipate our study to be a starting point for stakeholders involved in incident response to identify bottleneck locations in the network to help prepare for similar future events.

Diffusion of Spatial Data Infrastructures： Private More Inspired than the Public Sector---A Case of Tanzania

Spatial data is a key resource for national development. There is a lot of potential locked in spatial data and this potential may be realized by making spatial data readily available for various applications. SD1 （Spatial Data Infrastructures） provides a platform for the data users, producers and so on to generate and share spatial data effectively. Though efforts to develop spatial data infrastructures started worldwide in the late 1970s, SDIs are still perceived by many institutions as new innovation; as such, they have not penetrated to all institutions to bring about effective management and development changes. This paper is reporting on a study conducted to assess SDI Readiness Index for Tanzania. The study aimed at identifying problems undermining SD1 implementation in Tanzania, despite its potential in bringing fast socio-economic development elsewhere in the world. This paper is based on a research based on views from stakeholders of geospatial technology industry in Municipal Councils, Private Companies and Government Departments in Tanzania. Results indicated that Private Companies are more inspired than Government institutions towards implementation of SDIs. And those problems affecting implementation of SDIs are lack of National SDI Policy, lack of awareness and knowledge about SDIs, limited funding to operationalise SDI, lack of institutional leadership to coordinate SDI development activities, lack of political commitment from the Government. It is recommended that delibate efforts be devised to raise awareness of SDI amongst the Tanzanian community.

A Diachronic Perspective on the Use of French Spatial Data Infrastructures

Despite the recent development of many worldwide initiatives, there is still a need for the development of observation frameworks that will provide a comprehensive view of SDI’s use. Amongst the many challenges left, a thorough analysis of the information flows between existing SDIs as well as their respective uses and the way that those evolve over time is an important issue to explore. The research presented in this paper introduces a methodological framework oriented to the study of the SDIs use from a diachronic perspective. The approach is based on a Social Network Analysis (SNA) and questionnaires collected by online surveys. We develop a structural and diachronic analysis based on a series of graph-based measures identifying the main patterns that appear over time. The methodological framework is applied to a series of French SDIs and users involved in environmental management. The study identifies a series of structural differences in the data flows that emerge between the users and SDIs. Last, the diachronic network analysis provides an overall understanding on how data flows evolve over time at different institutional levels.

A brief overview of current status of European spatial data infrastructures-relevant developments and perspectives for Bulgaria

The paper aims to present a concise overview of the current status of the national spatial data infrastructures(SDI)of the European Union(EU)member states combined with specific peculiarities for Bulgaria.Some major challenges within the progress of the EU SDIs establishing,which is regulated by the European Directive INSPIRE(Infrastructure for spatial information in Europe)toward establishment of a SDI for environmental policies and activities,are marked out.Available comparative analyses of the main indicators for metadata,data-sets,and data services provided by EU member states are briefly discussed as a special attention is given to the Bulgarian progress.Recent achievements on accelerating the process of implementing the recommendations of the INSPIRE Directive in Bulgaria are outlined.

Expanding the SDI environment:comparing current spatial data infrastructure with emerging indoor location-based services

The authors compare key elements of the emerging field of Indoor Location-Based Services(Indoor LBS)to those currently found in spatial data infrastructure(SDI)programs.After a brief review of SDIs and Location-Based Services,the corresponding drivers,characteristics and emerging issues within the field of Indoor LBS are introduced and discussed.A comparative framework relates the two in terms of the criteria‘People’,‘Data’,‘Technologies’,‘Standards’and‘Policies/Institutional Arrangements’.After highlighting key similarities and differences,the authors suggested three areas–definition of common framework datasets in Indoor LBS,more effective use of volunteered geographic information by SDI programs and development of appropriate privacy policies by both communities–that may benefit from sharing‘lessons learned’.

SIRENE: A Spatial Data Infrastructure to Enhance Communities' Resilience to Disaster-Related Emergency

Planning in advance to prepare for and respond to a natural hazard-induced disaster-related emergency is a key action that allows decision makers to mitigate unexpected impacts and potential damage. To further this aim, a collaborative, modular, and information and communications technology-based Spatial Data Infrastructure(SDI)called SIRENE—Sistema Informativo per la Preparazione e la Risposta alle Emergenze(Information System for Emergency Preparedness and Response) is designed and implemented to access and share, over the Internet, relevant multisource and distributed geospatial data to support decision makers in reducing disaster risks. SIRENE flexibly searches and retrieves strategic information from local and/or remote repositories to cope with different emergency phases. The system collects, queries, and analyzes geographic information provided voluntarily by observers directly in the field(volunteered geographic information(VGI) reports) to identify potentially critical environmental conditions. SIRENE can visualize and cross-validate institutional and research-based data against VGI reports,as well as provide disaster managers with a decision support system able to suggest the mode and timing of intervention, before and in the aftermath of different types of emergencies, on the basis of the available information and in agreement with the laws in force at the national andregional levels. Testing installations of SIRENE have been deployed in 18 hilly or mountain municipalities(12 located in the Italian Central Alps of northern Italy, and six in the Umbria region of central Italy), which have been affected by natural hazard-induced disasters over the past years(landslides, debris flows, floods, and wildfire) and experienced significant social and economic losses.

Scientific geodata infrastructures: challenges, approaches and directions

Based on various experiences in developing Geodata Infrastructures(GDIs)for scientific applications,this article proposes the concept of a Scientific GDI that can be used by scientists in environmental and earth sciences to share and disseminate their research results and related analysis methods.Scientific GDI is understood as an approach to tackle the science case in Digital Earth and to further enhance e-science for environmental research.Creating Scientific GDI to support the research community in efficiently exchanging data and methods related to the various scientific disciplines forming the basis of environmental studies poses numerous challenges on today’s GDI developments.The paper summarizes requirements and recommendations on the publication of scientific geospatial data and on functionalities to be provided in Scientific GDI.Best practices and open issues for governance and policies of a Scientific GDI are discussed and are concluded by deriving a research agenda for the next decade.

Harmonisation requirements and capabilities towards a European spatial data infrastructure (ESDI): the HUMBOLDT protected areas scenario

The HUMBOLDT project has the aim of implementing a Framework for harmonisation of data and services in the geoinformation domain,under the Infrastructure for Spatial Information in Europe(INSPIRE)Directive and in the context of the Global Monitoring for Environment and Security(GMES)Initiative.The two-pronged approach of HUM BOLDT comprises a technical side of software framework development and an application side of scenario testing and validation.Among the HUMBOLDT Application Scenarios designed to demonstrate the capabilities of the Framework there is the one covering Protected Areas themes and use cases It aims to transform geoinformation,managed by park authorities,into a seamless flow that com bines multiple information sources from different governance levels(European,national,regional),and exploits this newly combined information for the purposes of planning,management and tourism promotion.The Scenario constitutes a step further towards the integration of monitoring systems envisaged in the view of Digital Earth.Protected Areas Scenario creates an examples of the use of the HUMBOLDT tools in Desktop and Web GIS environment,together with setting up a server environment exploiting HUMBOLDT harmonisation framework as taking into account user require-ments and needs and providing benefits for making the road to ESDI establish-ment easier.

Spatio-Temporal evolutive Data Infrastructure: a Spatial Data Infrastructure for managing data flows of Territorial Statistical Information

The observation of demographical,economical or environmental indicators over time through maps is crucial.It enables analysing territories and helps stakeholders to take decisions.However,the understanding of Territorial Statistical Information(TSI)is compromised unless comprehensive description of both the statistical methodology used and the spatial and temporal references are given.Thus,in this paper,we stress the importance of metadata descriptions and of their quality that helps assessing data reliability.Furthermore,time-series of such TSI are paramount.They enable analysing a territory over a long period of time and likewise judging the effectiveness of reforms.In light of these observations,we present Spatio-Temporal evolutive Data Infrastructure(STeDI)an innovative Spatial Data Infrastructure(SDI)that enriches the description of a Digital Earth,providing a virtual representation of territories and of their evolution through statistics and time.STeDI aims at managing a whole dataflow of multi-dimensional,multi-scale and multi-temporal TSI,from their acquisition to their dissemination to scientists and policy-makers.The content of this SDI evolves autonomously thanks to automated processes and to a Web platform that help improving the quality of datasets uploaded by experts.Then,STeDI allows visualizing up-to-date time-series reflecting the human activities on a given territory.It helps policy-makers in their decision-making process.

Governance interactions of spatial data infrastructures: an agent-based modelling approach

In order to facilitate and coordinate spatial data sharing and exchange,many organisations have developed spatial data infrastructures(SDIs).SDI governance plays a pivotal role in the development and evolution of an SDI,but as SDIs are complex adaptive systems,governing is a challenge.This research therefore proposes a complexity perspective to SDI governance by exploring the use of agent-based modelling to simulate and examine SDI governance interactions.In this agent-based simulation,we examine interactions between SDI stakeholders,data availability and the effects of different governance styles(hierarchical,network and laissez-faire governance)and budget policies.The simulation shows that it is possible to mimic SDI governance dynamics through agent-based modelling.By running different scenarios,it appears that a network approach is more successful compared to a hierarchical or laissez-faire approach.Expert validation shows that overall the results of the simulation are credible and insightful,although improvements can be made to make the model more realistic.With agent-based modelling,SDI governance becomes more tangible and visible,which facilitates discussion and understanding.Agent-based modelling therefore appears to be a helpful new approach in a better understanding of the complexities and dynamics of SDI governance.

Open data in spatial data infrastructure:the practices and experiences of Poland

As an important facilitator in e-government and society in general,Open SDI merits an assessment of its characteristics and the monitoring of its development.The aim of the study was the proposal of the SDI openness assessment approach based on existing openness assessment frameworks,as well as the presentation of the Polish Spatial Data Infrastructure(PSDI)development towards openness.The results indicated that ten geodetic and cartographic databases fulfilled ten out of eleven criteria of data openness,according to the methodological assumptions,and reached a 3-star level of openness.The need for further development of the infrastructure towards sharing public administration data is recognized,as well as non-governmental data that meet the open data criteria,thus contributing to the openness of the SDI.The proposed assessment method,referenced to a five-level data openness system and providing clear scoring benchmarking for assessing SDI openness,may be used for comparative analysis of SDI openness in different countries,including EU Member States that draw on the experience of the implementation of the INSPIRE Directive.

IDE-OTALEX C. The First Crossborder SDI between Portugal and Spain： Background and Development

IDE-OTALEX is the first crossborder spatial data infrastructure between contiguous Portuguese （Alentejo and Centro） and Spanish （Extremadura） regions. It was implemented to share official geographic information from Alentejo and Extremadura, and now Centro region, with everyone. This is the most effective way to have a distributed and flexible system to be used as a territorial observatory for sustainable development and environment protection in these rural and low populated regions. It also contributes to territorial cohesion, one of the tree main pillars of European Cohesion Policy. It＇s characterized for being a distributed, decentralized, modular and collaborative system, based on standards OGC （Open Geospatial Consortium）, W3C （World Wide Web Consortium）, ISO （International Organization for Standardization） and open source technology, developed to guarantee interoperability between the different GIS （Geographic Information System） provided by each project partner. The geoportal is multilingual （Portuguese, Spanish and English） and integrates a Map viewer, Metadata Catalogue and Gazetteer. It consists in central and local nodes which communicate through WMS （Web Map Services）, CSW （Catalogue Service Web） and WFS （Web Feature Services）. It is now implementing SOS （Sensor Observation Services） and WPS （Web Map Processing）. The geographic information available results of an extensive work of data harmonisation adapted to INSPIRE Directive （D 2007/2/EC, the European Parliament and Council, March 14, 2007）. It integrates basic cartography, socio-economic, territorial and environmental indicators.

On the Complexities of Federating Research Data Infrastructures

Federated Research Data Infrastructures aim to provide seamless access to research data along with services to facilitate the researchers in performing their data management tasks.During our research on Open Science(OS),we have built cross-disciplinary federated infrastructures for different types of(open)digital resources:Open Data(OD),Open Educational Resources(OER),and open access documents.In each case,our approach targeted only the resource“metadata”.Based on this experience,we identified some challenges that we had to overcome again and again:lack of(i)harvesters,(ii)common metadata models and(iii)metadata mapping tools.In this paper,we report on the challenges we faced in the federated infrastructure projects we were involved with.We structure the report based on the three challenges listed above.

Building geospatial infrastructure

Many visions for geospatial technology have been advanced over the past half century.Initially researchers saw the handling of geospatial data as the major problem to be overcome.The vision of geographic information systems arose as an early international consensus.Later visions included spatial data infrastructure,Digital Earth,and a nervous system for the planet.With accelerating advances in information technology,a new vision is needed that reflects today’s focus on open and multimodal access,sharing,engagement,the Web,Big Data,artificial intelligence,and data science.We elaborate on the concept of geospatial infrastructure,and argue that it is essential if geospatial technology is to contribute to the solution of problems facing humanity.

Making Data and Workflows Findable for Machines

Research data currently face a huge increase of data objects with an increasing variety of types(data types,formats)and variety of workflows by which objects need to be managed across their lifecycle by data infrastructures.Researchers desire to shorten the workflows from data generation to analysis and publication,and the full workflow needs to become transparent to multiple stakeholders,including research administrators and funders.This poses challenges for research infrastructures and user-oriented data services in terms of not only making data and workflows findable,accessible,interoperable and reusable,but also doing so in a way that leverages machine support for better efficiency.One primary need to be addressed is that of findability,and achieving better findability has benefits for other aspects of data and workflow management.In this article,we describe how machine capabilities can be extended to make workflows more findable,in particular by leveraging the Digital Object Architecture,common object operations and machine learning techniques.

Stakeholder analysis of the governance framework of a national SDI dataset-whose needs are met in the buildings and address register of the Netherlands?

National spatial data infrastructures are key to achieving the Digital Earth vision.In many cases,national datasets are integrated from local datasets created and maintained by municipalities.Examples are address,building and topographic information.Integration of local datasets may result in a dataset satisfying the needs of users of national datasets,but is it productive for those who create and maintain the data?This article presents a stakeholder analysis of the Basisregistratie Adressen en Gebouwen(BAG),a collection of base information about addresses and buildings in the Netherlands.The information is captured and maintained by municipalities and integrated into a national base register by Kadaster,the Cadastre,Land Registry and Mapping Agency of the Netherlands.The stakeholder analysis identifies organisations involved in the BAG governance framework,describes their interests,rights,ownerships and responsibilities in the BAG,and maps the relationships between them.Analysis results indicate that Kadaster and the municipalities have the highest relative importance in the governance framework of the BAG.The study reveals challenges of setting up a governance framework that maintains the delicate balance between the interests of all stakeholders.The results provide guidance for SDI role players setting up governance frameworks for national or global datasets.

From Persistent Identifiers to Digital Objects to Make Data Science More Efficient

Data-intensive science is reality in large scientific organizations such as the Max Planck Society,but due to the inefficiency of our data practices when it comes to integrating data from different sources,many projects cannot be carried out and many researchers are excluded.Since about 80%of the time in data-intensive projects is wasted according to surveys we need to conclude that we are not fit for the challenges that will come with the billions of smart devices producing continuous streams of data-our methods do not scale.Therefore experts worldwide are looking for strategies and methods that have a potential for the future.The first steps have been made since there is now a wide agreement from the Research Data Alliance to the FAIR principles that data should be associated with persistent identifiers(PID)and metadata(MD).In fact after 20 years of experience we can claim that there are trustworthy PID systems already in broad use.It is argued,however,that assigning PIDs is just the first step.If we agree to assign PIDs and also use the PID to store important relationships such as pointing to locations where the bit sequences or different metadata can be accessed,we are close to defining Digital Objects(DOs)which could indeed indicate a solution to solve some of the basic problems in data management and processing.In addition to standardizing the way we assign PIDs,metadata and other state information we could also define a Digital Object Access Protocol as a universal exchange protocol for DOs stored in repositories using different data models and data organizations.We could also associate a type with each DO and a set of operations allowed working on its content which would facilitate the way to automatic processing which has been identified as the major step for scalability in data science and data industry.A globally connected group of experts is now working on establishing testbeds for a DO-based data infrastructure.

Pervasive geo-security - a lightweight triple-A approach to securing distributed geo-service infrastructures

Security has recently become a major concern in distributed geo-infrastructures for spatial data provision.Thus,a lightweight approach for securing distributed low-power environments such as geo-sensor networks is needed.The first part of this article presents a survey of current security mechanisms for authentication and authorisation.Based on this survey,a lightweight and scalable token-based security infrastructure was developed,which is tailored for use in distributed geo-web service infrastructures.The developed security framework comprises dedicated components for authentication,rule-based authorisation and optimised storage and administration of access rules.For validation purposes,a prototypical implementation of the approach has been created.

DAPR-tree: a distributed spatial data indexing scheme with data access patterns to support Digital Earth initiatives

This paper proposes a novel data indexing scheme,the distributed access pattern R-tree(DAPR-tree),for spatial data retrieval in a distributed computing environment.As compared to traditional distributed indexing schemes,the DAPR-tree introduces the data access patterns during the indexing utilization stage so that a more balanced indexing structure can be provided for spatial applications(e.g.Digital Earth data warehouse).In this new indexing scheme,(a)an indexing penalty matrix is proposed by considering the balance of data number,topology and access load between different indexing nodes;(b)an‘access possibility’element is integrated to a classic‘Master-Client’structure for a distributed indexing environment;and(c)indexing algorithm for the DAPR-tree is provided for index implementations.By using a duplication of official GEOSS Clearinghouse system as a case study,the DAPR-tree was evaluated in a number of scenarios.The results show that our indexing schemes generally outperform(around 9%)traditional distributed indices with the utilization of data access patterns.Finally,we discuss the applicability of the DARP-tree and document DARP-tree shortcomings to encourage researchers pursuing related topics in Big Data indexing for Digital Earth and other geospatial initiatives.