Construction of a Type Knowledge Graph Based on the Value Cognitive Turn of Characteristic Villages: An Application in Jixi, Anhui Province, China

Abstract

Currently, Chinese villages are grappling with the issue of regional value collapse within the long-standing ‘urban-rural dual system’ strategy. Characteristic villages, as integral components of the urban–rural hierarchical spatial system and pivotal agents in rural development, wield significant influence in addressing China’s rural crises. The construction practice of characteristic villages showcases the cognitive evolution of ‘element-industry-function-type’. Within the value perception of characteristic villages, these practices reflect fundamental orientations in the interaction between humans and land, emphasizing the symbiotic relationship between production, life, and ecology. In alignment with this value perception, and drawing upon the existing studies on the classification of characteristic village types in Jixi County, this paper establishes a comprehensive type knowledge graph of characteristic villages. The framework of this graph’s expression revolves around ‘spatial elements-spatial combination-spatial organization’. This graph delineates a knowledge progression encompassing ‘information-knowledge-strategy’, characterized by three levels: the factual knowledge graph, conceptual knowledge graph and regular knowledge graph. The type knowledge graph systematically accumulates insights derived from the spatiotemporal transmission path of the village spatial structure. It formulates a structured progression of knowledge as follows: cognition of the village entity information → analysis of the village landscape structure → examination of the village social relationships. This constructed graph translates type-data information into spatial strategy knowledge, serving as a pivotal process in amalgamating characteristic village spatial data with semantic networks, particularly in expressing authenticity inspection and gene transfer.

1. Introduction

1.1. Explanation of Core Concepts

1.

Characteristic villages

The term ‘characteristic’ embodies both the specific attributes a village possesses and the competitiveness it engenders. Its characteristics represent the ‘basic state’, while the competitiveness embodies the ‘potential’. An organization displaying a unique style and structure can enhance the competitiveness in terms of scale, resources, efficiency, and market positioning. Rural characteristic resources encompass natural, human, and economic resources that significantly influence the creation and formation of distinctive rural functions. In the context of villages, characteristics mainly denote the utilization outcomes of various elements resulting from the human–land interaction. As evidenced in a prior work by Ren K, characteristic villages in Jixi exhibit clear trajectories in functional development [1]. These villages display spatial and social structures that lack uniformity. Consequently, they embody a complex organism with multiple interrelated functions and developments, yet possess a discernible dominant functional orientation. In the ongoing process of rural revitalization in China, characteristic villages and towns manifest in various forms, such as traditional villages, historically and culturally renowned villages, ethnic minority characteristic villages, villages renowned for their characteristic landscapes in tourism, and rural revitalization demonstration points. Consequently, from the standpoint of significance and prevalence, characteristic villages and towns represent a widely prevalent social foundation within rural areas of China. Within the context of this article, characteristic villages possess distinct typological attributes, emphasizing key elements and advantageous functions as primary focal points for control and development. These villages are in a continual state of evolution and enhancement, constantly undergoing upgrades and transformations.

2.

Types of knowledge

In the practice of transforming the world, knowledge represents the accumulation of experiences and the cognition acquired by individuals. In this article, ‘knowledge’ signifies an advanced form of scientific theoretical systems, specifically referring to the formation process and spatial patterns of characteristic villages. This knowledge is categorized into specific knowledge, implicit knowledge, and abstract knowledge [2]. Concurrently, characteristic villages exhibit base attributes, interface attributes, and pattern attributes during their formation process. Hence, the correlation of knowledge and characteristic villages adopts a three-layer progressive model termed ‘point triggering-surface correlation-body coupling’ [3]. The knowledge pertaining to characteristic villages amalgamate the ongoing process of knowledge formation and the operational mechanisms inherent in characteristic villages. Within the type knowledge graph lies the laws of value and spatial strategies within the characteristic villages. It elucidates the relationship between the composition and formation processes, encapsulating the distinct mechanistic differences among various types of characteristic villages.

1.2. Relevant Insights from Knowledge Graphs

The concept of a knowledge graph was formally introduced by Google in 2012, primarily aimed at developing an intelligent search engine. Its fundamental technology involves extracting entity information and associated attributes from web pages, constructing structural and semantic relationships among entities based on a semantic network. This technology and its outcomes are applicable to resolving intelligent queries and conducting analyses related to entities. Essentially, a knowledge graph can be visualized as a knowledge network or library structured as a directed graph. The bottom-up construction process of the graph involves an iterative update of knowledge, comprising three main steps: information extraction, knowledge fusion, and knowledge processing and inference. Each of these steps encompasses two crucial facets: attribute extraction and relationship inference.

For the knowledge graph concerning characteristic village types, two essential attributes must be incorporated: direction and weight [4,5]. When extracting village entity information, it is crucial to establish a foundational graph pattern based on the attributes (weights) and relationships (directions) of basic information. During the integration of knowledge about village types, it becomes imperative to achieve the linking of basic information (weight) and the merging of relationships (direction), thereby elucidating the distributional impact of internal resources in characteristic villages. In the process of reasoning about the village type knowledge, it is essential to analyze the value laws (weights) and spatial strategies (directions) embedded in the knowledge. This analysis helps in explaining the underlying logic within complex systems. The knowledge graph of characteristic village types serves as a flexible model with nodes for studying characteristic villages, offering clarity on the relationship between the spatial composition and the formation process. Moreover, it highlights the mechanism differences between various types of characteristic villages.

1.3. Research Significance of the Type Knowledge Graph of Characteristic Villages

The development of characteristic villages plays a pivotal role in advancing rural revitalization efforts. Successful cases of characteristic development contributing to rural revitalization can be observed in various Asian countries, including South Korea and Japan. In both South Korea and Japan, characteristic villages emerged as integral components in the process of rural revitalization. Successful cases in these countries have demonstrated the safeguarding of local characteristic resources, often formulating distinct development strategies based on regional disparities. The fundamental value orientation of characteristic villages and towns, aiming to foster dynamic rural dynamic development, mirrors similar objectives found in China. Studies on ‘characteristic villages’ in Asian countries have largely concentrated on establishing legal frameworks and social participation mechanisms. However, there is a lack of a comprehensive theoretical framework in interpreting the connotation of characteristic village types. European countries, on the other hand, have focused more on exploring the ‘characteristic value’ of historical small towns or ancient villages for protective development, resulting in a relatively limited perspective in type-based research. Presently, the conceptualization, theory, and paradigm surrounding ‘characteristic villages and towns’ within Chinese academia are primarily derived from the experiences of specific types of characteristic villages, such as traditional, historical, and distinctive ones [6,7,8]. However, as the strategic significance of characteristic villages and towns strengthens, the existing theory limitations, such as a relatively narrow field of vision or inadequate interpretation of internal mechanisms, have become more pronounced. Thus, there is a pressing need for a more scientifically grounded basic theory. The strategic importance and the demand for scientific development underscore the necessity and urgency of systematically constructing theoretical frameworks for characteristic villages and towns. In the preservation process of historical small towns, Europe has emphasized the continuation of functional structures intertwined with social relationships. A systematic theory derived from Chinese cases regarding characteristic villages will aid historical small towns in respecting their historical origins and spatial rights.

To deepen the understanding of type knowledge, this article focuses on researching the value cognition of characteristic villages and towns, aiming to guide the schematic analysis of type knowledge through value cognition analysis. Characteristic villages possess significant advantageous functions and exhibit a high resource efficiency. They play a comprehensive role in fostering the development of an urban–rural hierarchical spatial system, ultimately contributing to the resolution of rural crises [9,10]. Therefore, this article posits that the strategic position and historical mission of characteristic villages and towns dictate their future role as a prevailing development model in China’s rural areas. Building upon this premise, the article seeks to elucidate the core value transformation of characteristic villages and towns by analyzing their construction process and functional positioning. In alignment with this trend, based on systematic evaluation and type classification, the article explores how characteristic villages and towns can employ internal order [11,12] and operational pathways [13,14] to reshape landscape patterns and social structures within rural areas [15,16]. This underscores the significance of constructing a type knowledge graph within the article. The resultant type knowledge graph of characteristic villages is poised to effectively aid Asian countries, such as South Korea, in advancing rural revitalization efforts.

The internal order and operational pathways of characteristic villages and towns represent spatial strategies constituting the core content of type knowledge cognition. Past analyses and cognitions of spatial strategies for various characteristic villages and towns, such as traditional villages, historical villages, and industrial towns, often tended to directly focus on industrial strategy identification [17], spatial form extraction [18,19,20], or other empirical traps, lacking in-depth type knowledge. Consequently, this has led to a dearth of regional value dissemination or local element transmission in planning, hampering the guidance of landscape optimization or the reshaping of social structures. When analyzing the types of characteristic villages and towns at the implementation level, it becomes crucial to interpret types from a knowledge progression perspective, encompassing spatial information, meaning shaping, and value dissemination [21,22]. This article attempts to employ the progressive and graphical theory of knowledge graphs [23]. Leveraging the progressive logic inherent in advanced forms of knowledge, coupled with the deconstruction characteristics of schema language [24], the paper utilizes schema language tools in knowledge expression to analyze the spatial strategies of characteristic villages. This research aims to mitigate the biased influence of spatial knowledge and facilitate the spontaneous perception and practical programming of spatial knowledge. The primary focus lies in constructing a type knowledge graph capable of directly guiding the construction and implementation of characteristic villages, which represents the paramount significance of this article.

1.4. Research Status of the Type Knowledge Graph of Characteristic Villages

The study of geographic information graphs for spatial analysis has some limitations, such as rigid data perspectives, reliance on singular graph types, incomplete semantics, and overly macroscopic visual patterns [25,26]. The primary aim of constructing a geographic information graph is to visualize the correlation between geospatial knowledge and expression methods. Therefore, when constructing a spatial information graph for characteristic villages, the intention is not only to visually display the spatial distribution pattern of the villages, but also to delve into the semantic and positional relationships of the geographical space from the perspective of type knowledge.

The objective behind creating a characteristic village graph based on gene information lies in accurately extracting the landscape characteristics of the villages. Presently, due to limited village data availability, current research mainly focuses on qualitative morphological analysis. In leveraging gene information theory, this article endeavors to develop a ‘characteristic village information chain’ during the construction process of the type knowledge graph.

2. Materials: Characteristic Villages in Jixi

Jixi County, situated in the hilly regions of central and southern China, boasts a diverse range of characteristic resources. The development landscape of Jixi villages is intricate, grappling with the dual pressures of cultural preservation and the need for vitality stimulation. To establish a positive synergy between village development and resource utilization, initial research on the types of characteristic villages has been concluded (as depicted in Figure 1). In pursuit of further village development, this article employs theories of spatial information and knowledge graphs to explore a systematic method that can schematize the functional patterns and driving mechanisms inherent in characteristic villages. The aim is to uncover a stable correlation between spatial units and geographical elements, with the ultimate objective of comprehensively examining the authenticity of characteristic villages.

3. Theories and Methods

3.1. The Value Cognition Shift of Characteristic Villages and Towns in China

3.1.1. Analysis of Relevant Practices for the Construction of Characteristic Villages and Towns in China in Recent Years

Firstly, a historical review of construction practices is organized to establish the social and legal foundation for the role of characteristic villages in rural revitalization. Secondly, the primary content of current practices in constructing characteristic villages is summarized to delineate an analysis of their advantages.

1.

Related practices

China initiated the construction of characteristic small towns in 2014. Subsequently, with the support of various national policies, the Chinese government progressively developed three kinds of characteristic human settlement construction practices: characteristic towns (2016), ‘Livable and Industrial’ characteristic villages and towns (2017), and rural complexes (2018). This article primarily scrutinizes the policy backdrop, targeted subjects, operational modes, and practical objectives during the different stages. The goal is to explore the evolutionary direction and participants driving these practices [27].

2.

Functional-oriented transformation for characteristic villages and towns: industry-led development and flexible development models

In 1956, the American economist Rostow introduced the theory of dominant industries. Rostow posited that dominant industries effectively propel the rapid growth of related sectors through technological advancements or innovations, exerting a decisive influence on the development of other industries. The dominant function signifies a distinct advantage. The flexible development of organisms refers to the coexistence of multiple functions in a spatial context, forming a continuous competitive framework. Gradually, certain functions exhibit specialized characteristics and synergize with other functions, representing the core competitiveness of the regional system. In the new rural context, flexible organisms align more closely with the requirements of transformation and development logic. The emergence of characteristic villages is not only due to governmental policy support and promotion, but also the outcome of market competition, endowing these villages with a clear functional orientation. The development path of flexible organisms aims to broaden the influence and scope of the villages themselves, progressing beyond infrastructure to industrial development.

To delineate the differences between these two patterns, an analysis is conducted across seven aspects: development goals, driving forces, factor composition, and the industrial characterization of characteristic villages and towns. This aims to elucidate and reflect upon the practical construction of functional-oriented characteristic living environments (referenced in

Table 1. Village comparison between industry-development leading ones and flexible-development organic ones.

Comparison Item	Villages of Industry-Development Leading	Villages of Flexible-Development Organism
Development goals	Pursuing agglomeration development and economies of scale	Pursuing functional and comprehensive development
Village structure	The structure of the villages presents a vertical relationship: leading industry-dominant and others industry-supporting	The structure of villages presents a parallel relationship: the advantageous functions are parallel with other functions, and multiple functions exhibit a symbiotic state with flexible collaboration
Characteristic connotation	Explicit industrial/material characteristics	Implicit experience/structural features
Driving forces	From top to bottom, government intervention is the main focus	Bottom-up, mainly market and resource driven
Production method of characteristic products	Mass and standardized production on demand	Flexible production that meets the basic functions of villages, reflecting professionalism and precision
Role of government	Strong intervention and direct support for related industries	Inducing intervention with emphasis on infrastructure support
Industry characteristics	There is a subordinate relationship between industries, with less competition and a focus on collaboration	Two relationships between characteristic function and other functions: competition and synergy

).

3.

Summary of the evolution laws of practices

The evolution from ‘Characteristic Small Towns’ and ‘Characteristic Towns’ to ‘Livable and Industrial’ characteristic villages and towns exhibits its merits across three key dimensions. Firstly, the flexibility of carriers for practical activities is progressively increasing, transcending administrative boundaries and demonstrating the robust attributes of demonstrability, maneuverability, and practicality. Secondly, there is a noticeable shift towards functional guidance within practical behaviors, with a higher degree of execution. The evolutionary trend in the construction practice of characteristic human settlements aims to establish integrated organisms centered around efficiency and functions. This pursuit emphasizes enhancing the functional allocation efficiency, prioritizing resource integration, fostering public participation, and facilitating industrial upgrading. The ultimate objective is the establishment of characteristic villages and towns as comprehensive organisms. Thirdly, the procedural manifestation of practical behavior has shifted from a singular dimension to a comprehensive dimension. Within a confined geographical space, the construction of characteristic villages and towns endeavors to offer diverse and differentiated functional services. This approach aims to effectively coordinate production, ecology, and life within these areas.

3.1.2. Key Aspects of the Value Cognition of Characteristic Villages and Towns in China

1.

Cognitive evolution laws of the ‘element-industry-function-type’ presented in practice

The concept of ‘element-industry’ has been pivotal in determining the dominant functions and types of characteristic villages and towns, thereby establishing regional characteristics and core developmental directions. Emphasizing the efficiency of utilizing characteristic resources has been a fundamental principle guiding the recent construction efforts in characteristic human settlements. Post-2018, there has been a surge in the establishment of ‘rural complexes’ across various regions. Diverging from previous characteristic construction that overlooked enhancing rural fundamental functions, the ‘rural complex’ model focuses on achieving ‘residential and occupational coordination’. This approach has created an adaptable and regulated long-term developmental mechanism for characteristic villages and towns, employing a methodology of ‘model classification + all-element construction’. The target of energy efficiency diagnosis in characteristic villages and towns has transitioned from focusing solely on ‘characteristic industries’ to understanding ‘the overall development law of rural regional system’.

2.

Turn in value cognition of characteristic villages and towns

Analyzing the policy and practice evolution (as depicted in Figure A1), particularly examining the national prefix policy of the Chinese government over the past 9 years, reveals the evolving diverse developmental direction expected for characteristic villages and towns. Consequently, the ultimate construction goal for these entities is to establish a universal and fundamental development model, leveraging comprehensive regional resource allocation and empowering characteristic resources. The classification of characteristic villages and towns should not solely depend on the value output capacity of characteristic resources. Instead, the criterion for the type classification should align with the intervention of the characteristic development model in rural revitalization, based on the needs of comprehensive rural development. The shift in value cognition for characteristic villages and towns encompasses the fundamental orientation of the relationship between humans and land, the orientation towards a universal development model, and the orientation towards the organic symbiosis of production–life–ecology.

3.

Value evaluation of characteristic villages: Organic structure

The analysis of the pertinent policies and practices reveals that the constituent elements of characteristic villages share common attributes at the foundational level, with the primary source of the village’s main competitiveness stemming from the dominant function. Consequently, different types of characteristic villages exhibit diverse structures based on their distinct dominant functions. While meeting the requirements of life, production, and ecology, characteristic villages of various series demonstrate varying organic patterns. These patterns encompass different geographical entity organizational structures, landscape patterns, and production-relations patterns (as illustrated in Figure A2). The organizational structure of geographical entities refers to the composition analysis of the village DNA, the village landscape pattern entails the spatial form, composition, and relationship analysis, and the pattern of the production relations primarily involves the embedding path of the characteristic production relations.

3.2. Constructing a Method for the Type Knowledge Graph of Characteristic Villages

3.2.1. The Formation Process of the Type Knowledge Graph

From the construction process and structural level of the knowledge graph, the research approach to developing the type knowledge graph of characteristic villages involves several key steps. It begins by leveraging the relevant basic theories of knowledge graphs to condense and refine the type knowledge associated with the characteristic villages. Subsequently, this refined knowledge is conveyed through schematic language. The type knowledge graph serves not only to showcase the geographic entity information, but also aims to articulate the mechanisms involved in the generation, transmission, and cognition of this information. Consequently, it is imperative to scientifically abstract and thoughtfully select the relevant information aligned with the specific research object. Ultimately, this process leads to the extraction, abstraction, and expression of the essential elements pertinent to the research object in the graphical representation (as depicted in Figure 2).

3.2.2. The Type Knowledge Graph Expression Framework of Characteristic Villages

This paper employs a method that encapsulates the principles governing the display of village characteristics while expanding the graph’s connotation. By integrating the functionality, imagery, quantification, and systematicity, the method aims to unearth the genetic value of characteristic villages through morphology transmission. This enriches the scientific value of both characteristic-village-type theory and graph theory [28].

1.

Framework of the type knowledge graph

The type knowledge graph represents a set of research methodologies and tools intended to depict type-specific information associated with characteristic villages. The graph is organized based on the progression or classification principles of specific indicators. Examining the construction process and the structural level of the geographic knowledge graphs, the research of the type knowledge graph of characteristic villages is rooted in theories of geographic information. It strives to condense and refine the type knowledge [29,30,31,32], culminating in its expression through schema language. The type knowledge graph not only showcases geographical entity information, but also elucidates the mechanism of governing information generation, transmission, and cognition. Thus, depending on the specific research objectives, it is imperative to scientifically abstract and judiciously select the pertinent information related to the research object. The ultimate goal is to extract, abstract, and articulate the essential elements of the research object. Drawing from the semantic logic of schema language and integrating the spatial structure of characteristic villages, this paper establishes a framework for expressing the type knowledge graph. This framework, titled ‘spatial elements-spatial combination-spatial organization’, primarily illustrates the boundary, pattern, structure, development level, development direction, and combination of regional geographic entities. This schema portrays the progressive generation process: characteristic village elements → basic space unit → composite space unit → landscape space unit (as illustrated in Figure 3).

2.

Abstraction of spatial information in characteristic villages

By amalgamating the formation process of the type knowledge graph with general spatial information theory, the evolution of village types is fundamentally regarded as a compilation of temporal and spatial information. Notably, the spatial information carriers of characteristic villages predominantly comprise image-based information rather than conventional quantitative or conceptual data. Consequently, the spatial information of characteristic villages is categorized into three distinct segments:

Realistic Space: This category pertains to the specific functional attributes and states observable within the characteristic villages. It encompasses the tangible and empirical aspects defining the essence of these villages.

Hidden Space: Here, the focus is on the type definition and connotative attributes of characteristic villages. It delves into the underlying characteristics and implicit qualities that contribute to the village’s distinct identity.

Abstract Space: This category encapsulates the spatial laws and spatial planning discerned by the human analysis of the real space. It involves planning calculations, virtual simulations, and the identification of spatial patterns that emerge as a result of scrutinizing real spaces [33].

3.2.3. Key Aspects in Constructing the Type Knowledge Graph of Characteristic Villages

1.

Construction of geographic entities in characteristic villages

Geographic entities denote natural or artificial features existing independently in the world, each uniquely identifiable. The crux of constructing geographic entities lies in discretizing continuous spatial cognition into distinct geographic objects [26]. These entities encompass both basic and extended categories.

Basic Geographic Entities: These refer to identifiable objects easily extracted and amalgamated from basic geographic information data. They include realm entities, political district entities, road entities, railway entities, river entities, housing entities, hospital implementation entities, among others. The extraction and integration of these entities are based on specific data sources and application requirements.

Extended Geographic Entities: These entities, defined and integrated by the geographic entity production and application departments, are derived from semantic paraphrasing and logical structuring in graph construction. Extended entities adhere to specific semantics and logical structures, enhancing the breadth of information provided. Geographic entities possess distinct identification enabling the correlation of geographic entities with pertinent social, economic, and natural resource information.

Village Geographic Entities: Attributes and features. Village geographic entities encompass attribute collections (basic entities) and feature collections (extended entities) within a specific area. Attributes represent factual knowledge, whereas features are the product of human research and analytical knowledge.

In this study, the construction and management of geographic entities within characteristic villages are regulated by regions, boundaries, and nodes, all operating within the same temporal dimension. At the regional level, defining characteristics revolve around dominant functions that typify the area. Entities within defined boundaries share common attributes that unify their characteristics. Nodes represent the spatial characteristics and key features of the area under study.

2.

The theoretical framework of the type knowledge graph of characteristic villages

Integrating the process of categorizing characteristic village types, the knowledge graph does not just depict functional composition types, but also illustrates the various influencers in different types of villages. The logical sequence entails:

(1)

Differences in Geographic Entity Attributes: Various village organisms exhibit distinctions in the attributes of geographic entities, including population, income, industrial development, transportation, cultural heritage, and natural resources.

(2)

Attribute Perceptions Through Village Entities: These attribute differences are partially perceived and gauged by village entities, acting as information subjects [34].

(3)

Recording Attribute Differences: The perceived attribute disparities are recorded through diverse information forms, like entries, statistical reports, and government work reports.

(4)

Classification of Development Directions: Attribute differences, aligned with the connotation and attributes of characteristic villages, are categorized as distinct development directions within the village regional system. This encompasses the natural, ecosystem, economic, social, and cultural systems.

(5)

Reasoning and Knowledge Graph Formation: Reasoning based on the characteristic village type knowledge leads to the creation of various graphs, namely:

(6)

Factual Knowledge Graph (Village Genetic Data Information Graph): Conceptual knowledge graph (village spatial sequence graph spectrum, village arrangement pattern graph, village vertical graph) and regular knowledge graph (village production relations graph) [35,36].

(7)

Information Flow in Type Knowledge Cognition: The above processes constitute the fundamental information flow within the characteristic village type knowledge cognition.

(8)

Extended Information Flow in Cognition: Postimplementation, the implementation graph responds to the characteristic villages, forming the extended information flow within the characteristic village type knowledge cognition.

The theoretical framework of the characteristic village type knowledge graph emerges from the logical sequence outlined above (Figure 4).

3.

Hierarchical reasoning of type knowledge

The construction of graphs serves the purpose of facilitating both the forward- and reverse-reasoning process, moving from data-driven knowledge towards conceptual and standardized knowledge. It aims to graphically represent and compute this progression. The underlying principle of reasoning involves leveraging the relationship between information (concepts) within geographic entities and laws in a knowledge graph. This facilitates logical integration, relationship extraction, and comparative judgment, thereby enabling the induction from specific cases to general laws. Knowledge-level reasoning does not strictly follow a logical progression, but rather constitutes an event-driven, discontinuous analysis with critical implications. This critical thinking perceives geographic entities as intricate networks, comprising multiple participants, including accidental, heterogeneous, and discontinuous events [37].

Regarding the characteristic villages, their type knowledge reasoning showcases a loosely correlated hierarchical structure, represented as follows: factual knowledge about the village; conceptual knowledge encompassing the village layout, vertical band spectrum, and related aspects; regular knowledge concerning the village’s production relationships (refer to Figure 5).

4. Construction of Knowledge Graph of Characteristic Village Types in Jixi

4.1. Factual Knowledge Graph: From Information Knowledge to Cognitive Knowledge

1.

Principle of construction

The graph serves as an abstraction and generalization depicting the compositions of characteristic village settlements and the interrelationships among them. The creation of the factual knowledge figure –text graph primarily follows the paths of attributes splitting within the geographical ontology. By utilizing textual or schematic language, it becomes possible to describe and confine the relationships among the geographic locations, phenomena, events, and features. Ultimately, this process resolves the disparity between geographic phenomena and perceptual understanding. Consequently, the construction of the gene information graph facilitates the transition from ‘information’ to ‘cognition’ (Figure 6).

2.

Explanation and principles of the gene information graph

a.

Explanation

Through a prolonged evolutionary process, characteristic villages engage in interactions with the natural environment, social culture, and historical events, culminating in the formation of a distinct landscape system. This system exhibits regional characteristics in functional structure, production relations, and spatial morphology. Hence, the genes of the village necessitate the extraction from landscape system factors, including comprising driving forces behind the formation, the social relationship dynamics, and spatial attributes. Formation factors and social relations delineate the construction logic and principles of the characteristic landscape system, while the spatial characteristics manifest as the embodiments of construction methods and spatial configurations.

Based on the level of schema expression for the genes, the principal genes, cytoplasmic genes, and dissociation genes of Jixi characteristic villages (Figure 1) are categorized into two types: material genes and nonmaterial genes. Characteristic villages epitomize a stable fusion of material and nonmaterial genes, embodying a complex interweaving of diverse relationships. Material genes encompass tangible groups or monomers of varying scales, closely linked to information carriers and objects for recording information. Spatial genes within material genes are particularly amenable to graphical representation due to their rich informational content stored in spatial scales, structures, and forms. Among the nonmaterial genes, social–cultural genes encapsulate the production relationships and functional values of the village, among other elements. The elucidation of the gene information graph construction is depicted in Figure 7.

b.

Principle of construction

The characteristic village gene serves as the fundamental unit for assembling the characteristic village genetic data graph. It does not only mirror the characteristic resources that constitute the advantageous functions of these villages, but also unveils the interaction patterns between these resources and the villages themselves. The village gene embodies an intersection between biological genetics and human ecology. Drawing inspiration from the construction methodology of biological gene graphs, starting with the spatial landscape of characteristic villages, the establishment of the characteristic village genetic data information graph commences by focusing on the spatial landscape of characteristic villages.

Firstly, the characteristic village spatial landscape is categorized into two types: the physical landscape and the nonmaterial landscape. Secondly, gene identification and extraction take place. Through an analysis of gene attributes, guided by the principle of ‘internal uniqueness, external uniqueness, local uniqueness, overall superiority’ [38], the distinct features of the village genetic data and regional cultural landscapes are pinpointed. Finally, based on the recognition results, the gene shape (meta) is formulated. From the perspective of arranging landscape genes, an information graph featuring a four-level structure of ‘meta-point-corridor-network’ is established. This structure encompasses the surrounding environmental genes of the village, the internal material genes of the village, and the village information genes. By amalgamating various research cases, a genetic data information graph of characteristic villages is constructed.

3.

The spatial unit and composition of the gene information graph

The characteristic village genetic data comprises a gene arrangement structure and gene distribution pattern. In alignment with the fundamental ecological paradigm of ‘patches-corridor-matrix’, this paper introduces a gene-information-profile analysis model for characteristic villages, termed ‘gene element-gene point-gene corridor-gene network’ [39] (Figure A3). Indicators within the gene graph bear similarity to those elucidated in a prior paper [1].

‘Element’ signifies the distinct gene information units within the characteristic villages, encompassing the natural environment, locational conditions, economic structures, etc.

‘Point’ represents the recognition outcome derived from these ‘Elements’.

‘Corridor’ denotes the flow and interaction among various gene information units, inspired by the direction of the function optimization and characteristic development. It integrates and associates the gene units within the characteristic villages, forming an information chain. The ‘corridor’ might manifest as materialized space or merely a pure amalgamation of information.

‘Network’ embodies the spatial pattern of the functional model within characteristic villages, encompassing spatial structural characteristics, distribution rules, and representing a high-level scenario in a multiparty game.

The ‘Corridor’ and ‘network’ delineate the form and paradigm identification within the characteristic villages, serving as the groundwork for constructing conceptual graphs and regularity graphs depicting the type knowledge.

4.2. Conceptual Knowledge Graph: Cognition of the Spatial Structure

1.

Research method and construction framework of the spatial structure graph of characteristic villages

(1)

Overall construction method

The spatial structure graph of the characteristic villages comprises the spatial sequence graph, spatial distribution pattern graph, and spatial vertical graph. These three components are structured based on the spatial relationships among gene fragments. Through horizontal combinations of characteristic village genetic data, a spatial sequence graph for a single characteristic village and a spatial distribution pattern graph for formations of characteristic villages can be developed. Conversely, vertical combinations of genetic data allow the creation of a vertical spatial graph for characteristic village formations. The construction methods of the three spatial structure graphs are as follows:

a.

Single Village: Initially, gene information is identified based on gene function and positional relationships. The positional relationships of the gene fragments under the dominant function are analyzed and the main gene fragments are identified. Subsequently, based on the schema information of the genes, and considering the internal connections between the main gene fragments, the spatial sequence graph for a single characteristic village is constructed. This graph aims to express the village attribute classification and functional categorization.

b.

Village Formations: The types, structures, characteristics, and meanings of main gene fragments across various village types are summarized. The expression goals and methods are unified to construct a horizontal graph depicting the spatial arrangement pattern.

c.

Village Formations (Vertical Perspective): A scientific explanation for the transitions and intersections among the ‘production-life-ecology’ environment within mountainous areas is provided. A comprehensive understanding of the geographical attributes of mountainous ‘production-life-ecology’ is thereby gained, and a spatial vertical graph can be developed for these formations.

(2)

Extraction of spatial structure features from the village genetic data

Similar to a geographic information graph, the characteristic village genetic data graph is established upon a GIS database and is categorized based on the predominant functions of each village. It involves the extraction of an array of combinations comprising graphics, textual data, numerical information, and models [40]. This paper draws upon methodologies used in creating geographical information graphs, traditional village landscape genetic data graphs, and regional cultural heritage landscape gene graphs. It comprehensively employs gene-identification methods encompassing elements, structures, graphics, text, and others to recognize and extract genetic features. Utilizing the recognition outcomes, a feature-extraction method for the structure is employed to visually represent the attribute characteristics of villages. Considering that the culture and industries of characteristic villages are interlinked with the material environment, space, and specific behaviors, this article focuses on selecting gene fragments connoting spatial structures to delve deeper into their sociocultural and economic attributes. Gene recognition and feature extraction involve two aspects:

a.

Singular Aspect: The location and layout of the characteristic villages are influenced by the external geographical environment, characterized by cultivated fields and internal village layouts. Thus, constructing a characteristic village genetic data graph encompasses external geographic environment genes, internal humanistic environmental genes, and structural genes. This leads to the creation of a spatial structure graph reflecting the functional layout of the characteristic villages.

b.

Formations Aspect: Considering the spatial distribution patterns of the characteristic villages, the genetic data of the formations share both commonalities and differences in characteristics. Therefore, the primary content of the formations lies in the spatial distribution pattern of the villages within them.

(3)

Two types (three components) of spatial structure graph for characteristic villages

Regarding the graph construction framework, the spatial structure graph of the characteristic villages can be categorized into two types: horizontal graphs and vertical graphs.

a.

The Spatial Horizontal Sequence Graphs: This graph schematically illustrates constituent elements and primary functions within the village genetic data. Analyzing spatial agglomeration and configurations allows for the condensing of corresponding spatial organizational patterns into the spatial sequence graph.

b.

Spatial Horizontal Distribution Pattern Graph and Spatial Vertical Distribution Graph: These graphs express the functional genetic data for the villages of the same type and fall under the formation of the genetic data graph (pertaining to villages of the same type). Generally, there exists a certain level of fuzzy-information-transmission relationship among the spatial distribution pattern graphs of the same village type. From the perspective of gene fragment attributes, a horizontal graph is referred to as a two-dimensional graph, representing graphable spatial distribution relationships; a vertical graph, on the other hand, is termed a three-dimensional graph, portraying other relationships that cannot be graphed. The graph types are depicted in Figure 8.

2.

Construction and Representation of Jixi characteristic villages Spatial Graphs

(1)

Horizontal graph

The conceptual knowledge graph vividly illustrates the ‘characteristic base elements’ and ‘characteristic framework composition’ of the villages (Figure A4). Simultaneously, comparing the distinct spatial arrangements among the villages of the same type will aid in rural development and rejuvenation by finding a balance and a pivot point. Classifying the spatial vertical graph of various types of characteristic villages will expand the knowledge-exploration boundaries of the village.

(2)

Interpretation of the gene translation process in the horizontal graph

Characteristic villages exhibit diverse spatial plane sequences and arrangement patterns. However, villages in hilly areas tend to display a certain level of regional consistency in their spatial plane structures. Summarizing the plane schematics of different village types leads to the following conclusions (refer to

Table A1. Expression of the gene translation process in the graph of the spatial structure of the characteristic villages in Jixi County.

Translation Process	Representation of Plane Space Structure and Corresponding Pictorial Expression
The combination of mountains, forests, fields, rivers, and settlements	Circle-layered	Side-by-side	Staggered
Landforms and village site selection	Valley type	Terrace type	Flat-land type
Village settlement patterns	Group type	Strip type	Scattered-point type
Village settlement road network	Flat-land–regular road network	Flat-land–spontaneous irregular road network	Mountain-plane zigzag and vertical ascent road network
Combination of streets, lanes, and inner courtyards, and the corresponding scale relationship	Spatial sequence from street → lane → yard	All streets and lanes are all closed, narrow, and long spaces	Streets and lanes: height-to-width ratio greater than 1:1, narrow at the top and wide at the bottom
Combination of buildings	Along the street or water system linear arrangement combination	Cluster combination	Free combination

).

Mountains, forests, fields, rivers, and settlements: Arranged in circular-layered, side-by-side, and staggered patterns.

Landforms and village site selection: Comprising valley, terrace, and flat-land types.

Village settlement patterns: Displaying group, strip, and scattered point types.

Village settlement road network: Encompassing regular and irregular networks in flat land, as well as zigzag and vertical ascent networks in mountainous areas.

Streets, lanes, inner courtyards, and scale relationships: Follow a spatial sequence from street to lane to yard. All streets and lanes are closed, narrow, and elongated spaces with a height-to-width ratio greater than 1:1. The layout narrows at the top and widens at the bottom.

Building combinations: Presenting linear arrangements along streets or water systems, clustered combinations, and free configurations.

(3)

Vertical graph

Jixi, being a mountainous and hilly region, has diverse and complex landforms. Consequently, not all types of characteristic villages conform to a completely unified three-dimensional model. This paper focuses on ‘nodal’ villages that exhibit significant three-dimensional element interactions. It analyzes the spatial three-dimensional model to provide information for the protection, utilization, and construction of characteristic villages.

An analysis of the three-dimensional interaction between Jixi villages and mountains, rivers, farmland, and roads reveal three primary three-dimensional models: valley/river valley type, gentle landform, and basin/platform. Different characteristic villages in Jixi County showcase distinct three-dimensional spatial patterns. Valley/river valley and basin/platform patterns are predominantly found in agricultural, ecological, and landscape characteristic villages, while river beach/plain patterns are concentrated in industrial and agricultural characteristic villages. Compared to the two-dimensional model, the three-dimensional model offers greater stability in village development. It comprehensively demonstrates the spatial interaction among the three features (production, ecology, and life) of characteristic villages (refer to

Table A2. Conceptual knowledge graph: spatial three-dimensional graph.

No.	Graph Expression Name and Results
	Distribution Mode	Classification	Representative Village	Distribution Pattern Diagram
1	One of the compositions of the graph: the vertical graph of the valley/river-type landform space (characteristic villages of agricultural production, settlement landscape, ecological agriculture)	No farmland on both sides of the valley	Xionglu Village/Yangxi Village
		Terraces on both sides of the valley	Jiuhua Village/Jiapeng Village
		Terraces on one side of the valley	Longchuan Village/Zhong Village
		Paddy fields on both sides of the valley	Jinsha Village/Congshan Village
2	The second composition of the graph: the vertical graph of the gentle landform (the characteristic villages of agricultural production, human–natural combined landscape, industrial production, emerging industries)	River beaches	Longchuan Village
		Hilly plains	Hujia Village/Louji Village
3	The third composition of the graph: basin/platform landforms (characteristic villages of agricultural landscape, ecological protection, local and folk custom)	Basin	Yonglai Village
		Platform	Jiapeng Village

).

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Overview of the spatial structure cognition

Upon examining the two-dimensional and three-dimensional graphs, the spatial structure of Jixi village underscores two crucial points. Firstly, the village’s spatial configuration is closely intertwined with its landform. For instance, in relatively flat areas, villages often exhibit a clustered boundary shape while internally displaying a more typical clan etiquette system in terms of the spatial sequence. Secondly, human activities (related to production and daily life) within the village and the natural ecology surrounding the settlement tend to manifest in a harmonious and synergistic state, constrained by topographical conditions. Villages oriented towards small-scale agricultural production typically emphasize farmers’ independent planting, often unifying their produce through merchant purchases. These smaller villages tend to have lower output. Conversely, medium- and large-scale agricultural-production-oriented villages have adopted standardized production methods and actively developed rural cooperative economic organizations. This initiative has led to the formation of a distinctive agricultural product typology within these villages.

4.3. Regular Knowledge Graph: Understanding Characteristic Production Relations

1.

Characteristic production relations and local responses

Under the influence of characteristic production relations, characteristic villages demonstrate exceptionally high-resource-allocation efficiency. This efficiency reflects the development level of village productivity, the composition of production factors, and the advancement of social relations. Productivity and production relations manifest through both material and social production methods. The methods of production, based on the embedded path of characteristic production relations, notably influence the spatial production efficiency of the village entities. Hence, it becomes imperative to elucidate how the spatial structure and behavioral patterns respond to characteristic production relations. This paper seeks to abstract the underlying laws to construct an embedding path graph illustrating the characteristic production relations within the villages.

2.

Spatial production system of characteristic village entities

Characterized by their regional organic nature, characteristic villages possess a quaternary spatial production system comprising four key structures: the production structure, the production resource structure, the production environment structure, and the production development structure [41,42]. The functionalities propelled by characteristic production relationships are realized through the amalgamation of various substructures within the production system. The primary functions of the production space system encompass three elements:

Production Function: Serves as the dominant aspect, influencing production behavior and shaping the production space.

Carrying Function: Forms the foundational aspect, encompassing the possession of production resources and living resources.

Feedback Function: Functions as the backbone, primarily involved in the construction of system values within a regional unit.

3.

Graph of the embedding path of characteristic production relations

(1)

Formation process and layout of spatial structure

Drawing insights from the interplay among the ‘place-structure-action’ within the characteristic villages and towns in Jixi, this paper abstracts and illustrates a graph depicting the local embedded path of the characteristic production relations [43,44]. Local production factors serve as the foundation for the embedded production relations. Under the dynamic influence of the characteristic production relations, behavioral practices interact and exchange with local factors, generating a responsive behavior. The local production shapes the dominant function and corresponding spatial patterns, culminating in specialized outcomes in the spatial structure. This article visualizes the specialized result of the spatial structure, categorizing the local embedded path of the characteristic production relations. The spatial efficiency, controlled by the dominant function, becomes a significant output of the spatial structure specialization. This efficiency encompasses the place effect within the production space, the value feedback from the core space, and the fundamental function of the local space. Hence, the specialized path of the spatial structure signifies the evolution and expression of the original local spatial structure under the influence of the characteristic productivity.

(2)

Graph type

Analyzing the formation mechanisms of different types of characteristic villages in Jixi, and scrutinizing their spatial structures and physical elements, the spatial specialization results reveal three structural forms (reinforced, split, and spread). Additionally, five core behaviors are represented (centralized, discontinuous, deviated, segmented, and eccentric). The interaction between the core behaviors and the village’s spatial structure forms a specialized local spatial organization and situational relationship. Upon categorizing the spatial structure and core behaviors of the various characteristic villages, five embedded paths of characteristic production relationships within Jixi’s characteristic villages emerge: spatial structure reinforced–core behavior centralized, spatial structure spreading–core behavior discontinuous, spatial structure split–core behavior segmented, spatial structure reinforced–core behavior deviated, and spatial structure reinforced–core behavior eccentric (Refer to

Table A3. Type knowledge graph of regularity: embedding path graph of characteristic production relation.

Embedded Path Mode	Expression Name and Schema Analysis of This Series
	Types of Characteristic Villages and the Representatives	Graphic Interpretation of the Spatial Structure and Core Behavior in Representative Villages	Graphic Illustration of the Embedding Path of Characteristic Production Relations in Representative Villages
a Spatial structure, reinforced—core behavior, centralized	Villages with characteristics of agricultural production, Jinsha Village	Spatial specialization process: spatial structure dominated by agricultural functional space (production, sales, storage), and local space (life, landscape) jointly strengthen agricultural production practices and industrial significance. Core behavior type: functional agglomeration behavior.	Embedding path: line embedding dominated by specific functions; the expression factors are linearly distributed in the spatial relationship.
			Spatial layout: the village is based on a stable internal spatial layout.
	Villages with characteristics of settlement landscape, Wangchuan Village	Spatial specialization process: spatial structure dominated by living space; it is integrated with ecology and production; they together strengthen the local value, place meaning, and cultural context. Core behavior type: local agglomeration behavior.	Embedding path: a net-like embedding under the dominance of place and meaning; expression factors are intertwined in space.
			Spatial layout: village does value penetration with the outside through a stable internal spatial layout.
	Villages with characteristics of ecological protection, Jiuhua Village	Spatial specialization process: spatial structure dominated by ecological space and the local space (production, living) form a village ecological shared body, and jointly strengthen the ecological value. Core behavior type: functional agglomeration behavior.	Embedding path: divergent embedding under the dominance of function. The expression factors are weakly related to each other in space.
			Spatial layout: the internal spatial layout of the village has a greater impact on the regional ecological environment. The agglomeration layout of the internal elements is conducive to format a diffusion effect to the outside.
	Villages with characteristics of local and folk customs, Shuma Village	Spatial specialization process: spatial structure led by the social activity space is organically integrated with life and production space, and jointly strengthens and assumes local values and cultural emotions. Core behavior type: local agglomeration behavior.	Embedding path: net-like embedding guided by place meaning. The expression factors are intertwined in space.
			Spatial layout: village does value penetration with the outside through a stable internal spatial layout.
b Spatial structure, spreading—core behavior, discontinuous	Villages with characteristics of industrial production, Xionglu Village	Spatial specialization process: spatial layout dominated by industrial production function space (production, sales, transportation, storage) gradually strengthens the production practice, and finally the entire village presents a linear structure spreading along the traffic line. Core behavior type: functional agglomeration behavior.	Embedding path: line embedding dominated by specific functions; the expression factors are linearly distributed in the spatial relationship.
			Spatial layout: technology penetration, human penetration, and capital penetration exist between the interior and exterior of the village.
	Villages with characteristics of emerging industries, Langkeng Village	Spatial specialization process: spatial layout dominated by electronic commercial production space (production, sales, transportation, express delivery, telecommunications, storage) gradually strengthens the village’s e-commerce production practice, housing, and agriculture are attached spaces, and the entire village presents a cluster-like spatial structure spreading along the traffic line. Core behavior type: functional agglomeration behavior.	Embedding path: line embedding dominated by specific functions; the expression factors are linearly distributed in the spatial relationship.
			Spatial layout: technology penetration, human penetration, capital penetration, and system penetration exist between the interior and exterior of the village. A relatively stable information transmission loop is formed.
c Spatial structure, split—core behavior, segmented	Villages with characteristics of human–natural combined landscape, Longchuan Village	Spatial specialization process: natural material space and man-made social space jointly dominate the village pattern, and form a multilateral spatial structure. There are multiple core spaces inside the village. Core behavior type: local agglomeration behavior.	Embedding path: circle embedding guided by place meaning. The expression factors are interrelated in space.
			Spatial layout: The interior of the village has a relatively stable spatial layout. At the same time, the relationship between the interior and the exterior of the village is also relatively stable. The landscape production is produced by the interaction of the inside and the outside.
d Spatial structure, reinforced—core behavior, deviated	Villages with characteristics of ecological agriculture, Huangtukan Village	Spatial specialization process: natural ecological resources (space) and artificial production technology jointly dominate the functional layout and spatial pattern, and strengthen the village’s ecological agricultural production practice. The village forms a one-dimensional productive spatial structure. Core behavior type: combination of functionality and local agglomeration behavior.	Embedding path: line embedding under the dominance of function. The expression factors are linearly distributed in the spatial relationship.
			Spatial layout: internal production space layout and structure of the village are stable, and external technical intervention is actively accepted.
e Spatial structure, reinforced—core behavior, eccentric	Villages with characteristics of agricultural landscape, Jiapeng Village	Spatial specialization process: one of the important output results of agricultural production is the creation of seasonal landscapes. The seasonal agricultural landscape dominates the identified path of the village’s spatial structure. In order to streamline this landscape formation path, the village’s agricultural landscape production practices are constantly being strengthened. Core behavior type: combination of functionality and local agglomeration behavior.	Embedding path: the circle-layered embedding under the codominance of function and place meaning. The expression factors are arranged interactively and linearly in space.
			Spatial layout: internal production space layout and structure of the village are stable, and external technical intervention and capital is actively accepted.

).

Each type of graph analysis comprises three branches (refer to Table A3):

The Process of Space Specialization: Refers to the interaction between the functional behavior and place, generating practical meaning and place value.

Embedding into the Local Structure: Characteristic production relations are dominated by the specific functions or field meanings of particular places, expressed through local settlements, public behavior, the local environment, characteristic resources, the village spatial structure, and the dominant functional utility.

Impact on Resource Structure: Characteristic production relations influence the resource structure, thereby influencing the spatial layout of the characteristic villages. Driven by resource aggregation, the village’s internal and external environment undergoes dynamic changes. Internal agglomerations of function or value occur within the village, influencing the regional production mode’s internal structure and its impact on the external region.

4.

Forecast of future development based on the embedded path of characteristic production relations

The graph of characteristic production relationships illustrates the reciprocal adaptability between characteristic production and the local structure. By scrutinizing the process of adaptation and the integration of characteristic production methods into spatial structures, social environments, and cultural contexts, it identifies the embedded carrier, trajectory, and capability of characteristic production relations. Simultaneously, through the lens of differentiation boundaries, the analysis of differences in the embedded production relation paths belongs to the examination of disparities in village formations. The primary identification lies in the divergence of responses within Jixi’s characteristic villages’ local spatial structures, specifically variations in the agglomeration behaviors and order.

Moreover, the embedded path reveals the fragility in certain connections, such as interfaces or nodes lacking sufficient compatibility with high-quality resources. These fragile components may give rise to new production methods or multiple production relationships.

Forecasting the future development path of villages based on the embedded path of characteristic production relations involves recognizing that locality serves not only as a unique condition for the generation of characteristic village structure systems and elements, but also as a vital support for local entities to respond to external influences. Embedding methods, like spatial organization, behavioral subjects, industrial practices, and spiritual connotations, constitute multiple dynamic transmission paths, enabling the evolution of physical environments into functional commitments and emotional connections. Consequently, the future development trajectory of characteristic villages rests upon inheriting and reproducing local embedded paths. Strengthening the local embedded path can rectify the superficiality and instrumentalization tendencies when practical behaviors conflict with spatial patterns.

4.4. Practical Application of the Type Knowledge Graph of the Characteristc Villages

1.

Type knowledge Graph expression paradigm and application value

This article establishes a knowledge graph expression framework for characteristic villages, encompassing a progressive generation process: patterning characteristic village elements → basic spatial units → composite spatial units → landscape spatial units. Employing a single village as the fundamental analysis unit, it explicates the spatial structure and production relationships of different characteristic village types based on gene information in Jixi. The type knowledge graph amalgamates knowledge from the graphing path of the characteristic village elements and the spatiotemporal transmission path of the village spatial structures, forming a structured knowledge progression sequence: the village entity information cognition → the village landscape structure analysis → the village social relationship analysis. Employing both planar and three-dimensional expression methods, this article constructs a graph to comprehensively delineate the formation mechanism and typical features of characteristic villages, shaping a standardized paradigm of the type knowledge. In future rural revitalization endeavors in Jixi County, Huizhou, and other Asian rural areas, ensuring the long-term sustainable development of villages requires adherence to the functional hierarchy in graph expression, exploring the unique spatial structure and embedded production relationship paths of the characteristic villages.

2.

Utilization level and main entities

The knowledge graph of the characteristic village types offers advantages in imagery, specificity, standardization, and practicality. It integrates the ‘digital, theoretical, and formal’ aspects effectively, guiding the subsequent planning of villages. Among the primary entities of local residents, government, and investors, both government bodies and investors can execute spatial development using flat-spatial-form graphs and vertical-spatial-pattern graphs. Simultaneously, residents can organize their production behaviors based on the production relationship graph. For instance, investors and governments can devise tourism routes grounded in the spatial structures and behaviors within the villages.

5. Conclusions and Discussion

5.1. The Formation Process of the Type Knowledge Graph Based on ‘Information-Knowledge-Strategy’

Leveraging the computer extension theory—an approach rooted in utilizing computer technology and network theory to tackle procedural problems—this study embarked on the decision-making process to construct the type knowledge graph. Primarily drawing from the formal system of ‘information-knowledge-strategy’ within extension theory, this article delineates the construction logic of the type knowledge graph. It unifies the gene information, spatial structure, and production relations into a cohesive extension system, comprising three types of knowledge graphs (refer to Figure 9).

5.2. Graph Construction and Expression Based on System Requirements from Characteristic Villages

1.

The need for authenticity inspection in the development of characteristic villages

The encroachment of industrial civilization upon villages, particularly those in close proximity to cities, is causing the gradual erosion of traditional rural patterns. Many villages face the threat of depopulation or assimilation into a standardized framework. Fortunately, despite the swift pace of globalization and modernization, villages retain intrinsic elements and locales that resist standardization. Some villages are built through self-organization or collaboration with other entities. The primary function of the ‘characteristic villages’ type knowledge graph lies in analyzing the deep-rooted internal connections between these villages and urban areas. By dissecting stable and hereditary spatial patterns and environmental resources, characteristic villages can transcend the structural limitations imposed by industrial elements’ agglomeration, thus fostering sustainable development.

In response to this imperative, this paper employs the formation mechanism and process analysis of characteristic villages as a guide and constructs the type knowledge graph. It offers three types of schematic knowledge—facts, concepts, and laws—to facilitate the further construction and development of villages. This comprehensive approach completes the entire process of reviewing the authenticity of characteristic villages.

2.

Transmissive needs of geographic system genetic data in characteristic villages

The dominant functions, material elements, spatial sequences, and organizational structure within the characteristic village regional system exhibit traits such as unconsciousness, self-consistency, integrity, and stability. These traits collectively constitute the transmissibility of the characteristic village genetic data. Despite the evolving relationship between urban and rural areas, the functional and spatial structures of characteristic villages encounter growing challenges. However, altering the functional and social relationships within the village genetic data proves to be arduous. Hence, through a progressive analysis of the mechanism and knowledge within the characteristic village’s regional system, the stable and transmissible complex relationship is translated into a schema. The type knowledge graph serves as a medium to express both the phenomenon and structure, thereby enabling the conveyance of hidden laws and mechanisms inherent within the village’s regional system.

5.3. Possibility of Knowledge of Characteristic Villages ‘Embedding’ into Localities

Village planning encompasses objects, processes, and outcomes that comprise temporal and spatial information. This compilation bears the responsibility of connecting with the external system, i.e., the local environment. The ‘type knowledge’ associated with characteristic villages serves as a normative criterion impacting the reciprocal interaction between village construction and regional development. This knowledge encompasses three crucial aspects: meaning creation, language expression, and composition analysis.

Regarding meaning-making, the construction of the knowledge graph elucidates the relationship between villages and localities, serving as an effective conduit to establish the rationality of characteristic villages. In terms of language expression, the fundamental attributes and socioeconomic structure constitute components within the paradigm of the knowledge graph, adhering to the ‘bottom-up’ approach in graph drawing.

Analyzing the composition, characteristic villages, as a form of rational behavior, are bound by the local structure. Hence, the ‘embedded’ type knowledge graph illustrates the interactive relationship between local knowledge and the structure of characteristic villages. This perspective suggests that the spatial (behavioral) structure of characteristic villages and the local knowledge structure are confined within the same behavioral ‘field’.

5.4. Limitation of the Approach

While this article successfully extracts the type knowledge graph of the characteristic villages and offers guidance for future spatial development measures based on their functional characteristics and spatial structures, the implementation of this method remains incomplete. Many practical applications are still at the stage of protecting a select few villages. In the current landscape of rural development, villages exhibit dynamic tendencies, particularly fueled by the surge in rural tourism driven by urban capital. Consequently, the rural development trajectory is occasionally dictated by incidental practices.

Despite proposing rural areas function as organisms, this paper lacks consideration of the dynamic flow relationship between rural historical resources and urban resources during the graph-construction process. Therefore, the subsequent phase of research needs to enhance the efficacy of the graph framework by integrating perspectives on urban–rural development integration.