# Linked Open Government Data: Still a Viable Option for Sharing and Integrating Public Data?
## 6 What Factors Are Holding back the Spread of LOGD?
### LOGD Data Friction
#### 6.2.2 Organizational Dimension  
The Organizational Dimension focuses on the strategic aspects of data management within the structures of government bodies. It underscores the importance of developing integrated and efficient workflows that are capable of navigating and overcoming the bureaucratic and cultural hurdles often encountered in government settings. This dimension also emphasizes the need for directing the attention and enhancing the skills of public servants specifically towards LOGD. The goal is to foster an organizational culture that not only understands the value and potential of LOGD but is also equipped to effectively manage, share, and utilize these data resources in a way that aligns with the broader objectives of the public sector.  
Cultural Change  
Government organizations often face _challenges in adapting_ to new data-sharing practices and technologies, primarily due to their inherent bureaucratic processes and strict regulations. Moreover, as highlighted by [PERSON] et al. [32], semantic web technologiesand protocols pose challenges for government agencies with intricate data requirements and constrained resources. Governments prioritize expanding the volume of open data in various forms rather than solely maximizing LD. As [PERSON] et al. have highlighted [80], there is a crucial need for an integrated approach that combines the use of semantic methods with expert collaboration. This approach aims not only to enhance legal regulation but also to facilitate knowledge building, starting from existing processes and practices. Additionally, ref. [89] discuss a significant issue: the _lack of awareness_ in identifying valuable datasets for reuse. This common challenge impedes the full realization of open data's potential. Public officials need to be adept at recognizing which datasets can be valuable for use and reuse, and which should not be allocated further resources. This discernment requires an in-depth understanding of the possible applications of various datasets and the specific needs of potential users interested in accessing and reusing this data. They also advocate for public institutions to adopt a mindset of being data reusers right from the beginning of the data publication process. In the same vein, [PERSON] et al. [68] identify an _organizational shortcoming_ in the realm of data publishing, where data publishers frequently lack essential contextual information. This deficiency hinders their ability to accurately determine which other entities their data should be linked to. _Operational and process barriers_ are the focus of other authors. According to [PERSON] et al., public sector organizations encounter numerous hurdles in incorporating LD technologies into their routine operations. The bureaucratic nature and intricate legislation typical of public services often result in these bodies adopting new technologies like LD more slowly than private entities. Training consultants for public servants must comprehend these difficulties and their impact on the public sphere, and develop solutions to address them [70]. [PERSON] et al. [33] point out that most literature on publishing LOGD focuses on \"less complex, non-operational datasets\". There is a pressing need for an engineering perspective, along with the identification of practical challenges and considerations of \"organizational limitations\". Similarly, [PERSON] et al. stress the need to thoroughly examine and understand the current processes used in statistical offices and other data-publishing entities. They also highlight the importance of establishing and implementing relevant policies [90].