Open National CORS Data Ecosystems: A Cross-Jurisdictional Comparison

Interdisciplinary Description of Complex Systems 20(2), 78-95, 2022 OPEN NATIONAL CORS DATA ECOSYSTEMS: A CROSS-JURISDICTIONAL COMPARISON* Warakan Supinajaroen**, Bastiaan van Loenen and Willem Korthals Altes 1 Delft University of Technology Delft, Netherlands 1 DOI: 10.7906/10.7906/indecs.20.2.2 Regular article Received: 14 January 2022. Accepted: 20 April 2022. ABSTRACT Developments toward Open Government Data (OGD) also affect the data from National Continuously Operating Reference Station (NCORS), an infrastructure supporting standard and precise positioning in spatial activities. The application of OD policies on NCORS data (OD-NCORS) varies per country. This article explores the approaches and impact of OD-NCORS in three European countries: Germany, the Netherlands and Sweden. Understanding the differences in the implementations may benefit other countries in their strategies to implement OD for their NCORS. It may also provide insights for organisations considering OD for other data. The research found that the key factors affecting OD-NCORS implementation are the national governing nature and the existence of commercial CORS networks. There is no single approach for OD-NCORS implementation that fits every national context. KEY WORDS open data, data ecosystem, CORS, GNSS, Germany, Netherlands, Sweden CLASSIFICATION JEL: C89 *This is the extended version of the abstract published in: Vujić, M. and Šalamon, D., eds.: Book of abstracts of the National Open Data Conference. University of Zagreb, Faculty of Traffic and Transport Sciences,*Zagreb, 2021. **Corresponding author, : ; +31618189376; - Open national CORS data ecosystems: a cross jurisdictional comparison INTRODUCTION Many public datasets in many countries are made available as Open Government Data (OGD). Also, the data from National Continuously Operating Reference Station networks (NCORS) are provided as OGD in many countries. NCORS networks collect and process data from the Global Navigation Satellite Systems (GNSS) to provide precise positioning data to support spatially related activities. NCORS governing entities have applied different approaches to ensure the stability and functionality of their NCORS under the OD landscape. The countries’ experiences and lessons should benefit many other countries facing similar OD-NCORS implementation challenges. This article explores the approaches, impacts and results of OD implementation on NCORS ecosystems in three members of the European Union (EU): the Netherlands, Sweden, and Germany. After the introduction, an overview of NCORS from a data perspective is elaborated together with an NCORS data ecosystem conception. After that, the concept is applied to explore the cases. The findings are discussed in the next part. Lastly, based on the exploration, this article provides considerations for stakeholders in implementing OD on NCORS in other countries and the implementation of OD on other datasets. WHAT IS NCORS CORS is a collective term for ground stations that observe signals from GNSS such as Global Positioning System (GPS), Global Navigation Satellite System (GLONASS), BeiDou and Galileo. In general, CORS can refer to a station or a network of ground stations. The latter one is called a CORS network. CORS can be categorised into three hierarchical levels: global, national and local networks [1]. At national levels, many national governments have established CORS as an infrastructure [2-4] to support several positioning activities. The CORS networks operated by the national governments can be considered National CORS networks or NCORS. In many countries, there are commercial CORS (CCORS) networks. The functions of NCORS are first to support positioning standardisation through access to the national spatial reference frame, the fundamental function of NCORS data is to allow access to the geodetic reference frame [5-7]. Secondly, NCORS support positioning accuracy through correction services. Thirdly, NCORS serves also national time synchronisation [8]. NCORS has become a requirement for many development initiatives. For smart city initiatives, the precise positioning data from CORS can support the location services such as traffic management, autonomous vehicles and emergency services [9, 10]. NCORS supports digital cadastral [2, 3] as part of E-government initiatives [4]. Precision Agriculture (PA) applies spatial technologies [11] as “right treatment in the right place at the right time” [12]. The PA functions such as precision soil preparation, seeding, crop management, precision harvesting, and data analysis and evaluation benefit from NCORS data [11, 13, 14]. A DATA PERSPECTIVE OF NCORS The function of NCORS is to provide data that improve the accuracy of and standardise other positioning data. NCORS data serve as a national geospatial data framework – the data that other spatial data are built upon [15]. NCORS data serve the correction services for GNSS positioning. With these two functions, users can collect, process, and distribute the high precision spatial data that are interoperable with other spatial data in the national reference frame. The flows of NCORS data in serving the two functions are provided both in real-time data through Real-Time Kinematic (RTK), Differential GNSS (DGNSS) and Precise Point Positioning (PPP) services. For archive data, NCORS data is provided, such as RINEX. 79 W. Supinajaroen, B. van Loenen and W. Korthals Altes AN NCORS DATA ECOSYSTEM An ecosystem refers to an integrated system composed of a biotic community, its environment, and its dynamic interactions [16]; these components could not be separated or viewed in isolation [17]. The elements in an ecosystem coexist and influence each other. External forces also affect an ecosystem, such as climate changes and natural disasters that influence the components in the ecosystem. The ecosystem concept was applied to explain, understand, model and replicate the factors or elements and their relations in many academic and practical fields. Data science scholars have defined several data ecosystem conceptions [16-20]. Data ecosystems are the networks of socio-technical components to collaborate on creating, managing, and sustainable data-sharing initiatives [19]. A data ecosystem is a frame of the relations of the actors, which can be individuals or entities and technical components to reach the common data goals [20]. In OD, the completion of an OD ecosystem must be (1) user-driven – to satisfy different types of users, (2) circular – to allow the stakeholders in satisfying and contributing to the data value chain, (3) inclusive – to stimulate the participation from non-government actors, and (4) skill-based – to provide OD and relevant knowledge to people [21]. From these conceptions, a data ecosystem refers to the data existence and the interacted elements with a function(s) to facilitate the flow of the data. In this article, an NCORS data ecosystem is defi (...truncated)