# Linked Open Government Data: Still a Viable Option for Sharing and Integrating Public Data?
###### Abstract  
Linked Data (LD) principles, when applied to Open Government Data (OGD), aim to make government data accessible and interconnected, unlocking its full potential and facilitating widespread reuse. As a modular and scalable solution to fragmented government data, Linked Open Government Data (LOGD) improve citizens' understanding of government functions while promoting greater data interoperability, ultimately leading to more efficient government processes. However, despite promising developments in the early 2010s, including the release of LOGD datasets by some government agencies, and studies and methodological proposals by numerous scholars, a cursory examination of government websites and portals suggests that interest in this technology has gradually waned. Given the initial expectations surrounding LOGD, this paper goes beyond a superficial analysis and provides a deeper insight into the evolution of interest in LOGD by raising questions about the extent to which the dream of LD has influenced the reality of OGD and whether it remains sustainable. Open Government Data; Linked Data; data friction +
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0000-0001-6691-4600]M.M. Following [PERSON]'s metaphor of \"data friction\" which expresses \"the costs in terms of time, energy and attention required simply to collect, control, store, move, receive and access data\" [19] (p. 84), we can speak of \"OGD friction\" referring to the obstacles, difficulties, or resistance encountered in the access, use, and sharing of OGD. These frictions can \"have both physical and social aspects\" [19]. Regarding the first, OGD quality is essential for effective utilization by users, and it is considered a potential technical factor that can hinder or facilitate its exploitation [20; 21; 22]. In particular, metadata quality is particularly vital because it enables users to search and access dataset descriptions, ultimately enhancing the speed and ease of OGD use [18; 23; 24]. Low levels of open data literacy [25] are a significant social friction, indicating citizens' limited familiarity with the design and use of technology [26], and difficulties in accepting technology [27], a misalignment between user needs and the capabilities of available datasets [26; 28]. To address these challenges and promote the reuse of OGD, several authors have suggested applying Linked Data (LD) principles to OGD [29; 30; 31; 32]. Linked Open Government datasets offer the potential to \"replace isolated data silos with larger, interconnected datasets built on top of the Web architecture\" [33; 34], fostering synergy among disparate data sources [35]. This approach allows users to gain a better understanding of the data's context by exploring related datasets [36; 37]. As proposed by [PERSON] ([[https://www.w3.org/DesignIssues/LinkedData.html](https://www.w3.org/DesignIssues/LinkedData.html)]([https://www.w3.org/DesignIssues/LinkedData.html](https://www.w3.org/DesignIssues/LinkedData.html)) (accessed on 1 February 2024)) in 2010, the principles of LD offer a modular and scalable solution to counteract fragmentation in government data. This method not only enhances citizen awareness about government functions but also improves administrative efficiency. Furthermore, Linked Open Government Data (LOGD) enable access to and retrieval of data from authoritative and reliable sources. This approach can significantly reduce the inconsistencies found in legacy datasets, leading to more accurate and reliable results when querying open databases [38]. Under these auspices, in the early 2010s, a few government agencies began adopting LOGD principles and technologies [6; 39], a movement that was bolsters by academic and research studies [40], prototypes [41; 42; 43], and methodological proposals [32; 44; 45]. However, despite the initially promising expectations, our recent research activities on OGD and LD, involving the analysis of various government portals in different capacities [18; 25; 46], have occasionally identified what seems to be a significant decline in interest in LOGD.