Grand sites refer to representative sites from various archeological cultures, dynasties or various historical ethnic regimes, which are usually very large in area and have important historical, scientific, artistic, and cultural values [1
]. Grand sites are important witnesses of the 5000-years of Chinese civilization, which are of great significance to study the origin and development of Chinese civilization. The grand sites in China are characterized by a long history, wide distribution, large quantity, complex types, and a large scale [4
]. Grand sites are facing a series of threats such as natural disasters, urban and rural construction, agricultural production, large-scale infrastructure construction, etc. [5
], which places the conservation of grand sites under great pressure. The conservation and use of grand sites is generally divided into archeology, conservation planning, exhibition and use, monitoring, and so on. Archeology is crucial to the conservation of grand sites [1
], because the data of archeological investigation and excavations represent the basis for conservation and use.
During archeological investigation and excavation, the geospatial data and descriptive information of particular stratum, ruins and relics will be recorded in detail and sorted. Due to many factors such as strenuous research tasks and the complexity of data processing, less than half of the available data is published within two years after the archeological excavation [6
]. With the powerful capabilities of data acquisition, processing, storage, analysis, and visualization, GIS provides effective support to the processing, database building and use of archeological data. In addition, GIS has already been used as an important tool in archeological research, such as settlement analysis and prediction modeling [7
]. Although GIS has shown obvious advantages in archeological prospection, excavation and other related research regarding data management, spatial analysis, and visualization, it lacks necessary control of data quality and standardization [9
]. Most of archeological GIS systems are deficient in system interoperability and data sharing, because of stand-alone deployment, the lack of online access, and the lack of measures for data security and disaster recovery [14
]. As more and more archeological excavations are undergoing, archeological data are accumulated in large quantities and cannot be processed in time. Therefore, archeological datasets are getting bigger and more complex, which are impossible for traditional GIS to process, store and analyze. A framework of archeological information system should be established from the perspective of archeologists, which is corresponding to what archeologists do in their daily work [15
Archeological data of grand sites, which have obvious characteristics obtained from spatio-temporal big data, are essentially geo-spatial big data [16
]. As key technology of the new generation of GIS, the deep integration of spatio-temporal big data and archeology will have a far-reaching impact on the conservation of grand sites and archeology, specifically manifested in the following four aspects: (a) From the view of archeological concepts and data analysis, the archeological spatio-temporal framework can integrate the structured and unstructured data as a whole, to better visualize, interpret, and understand the past history of human beings. (b) The archeological excavation reports are inevitably led by the subjectivity of archeologists, hence the reports don’t fully reflect the real situation of the grand site. The above limitation of archeology and its influences could be reduced to a certain extent by using spatio-temporal big data [17
]. (c) With the application of a new generation of information technologies (such as advanced surveying and mapping technologies, big data, Internet of Things, cloud computing) in archeology, the volume and varieties of archeological data has seen a dramatic rise, thus the data processing and mining will be more complicated. Spatio-temporal big data offers a new technology and methodology for data acquisition, processing, storage, organization, analysis, and representation. (d) Archeology is a discipline characterized by interdisciplinary research. The spatio-temporal big data of grand site will offer a new way for archeologists to get in touch with scholars of other disciplines and the public, promoting interdisciplinary research, communication, and collaboration. Spatio-temporal big data can radically transform archeological practice, fostering new research questions, novel data visualization techniques, and new competences. It will also give archeology an enhanced ability to investigate and address those significant questions [18
Great progress has been made in digital archeology and the digital publication of archeological data [19
]. Digital photogrammetry is used to carry out survey and mapping of archeological entities in fieldwork [23
]. The laser scanning and photogrammetric reconstruction was used to make three-dimensional models of ruins (temples, monuments, etc.), which were published online [20
]. The digitization and digital publication of archeological data have received great attention, while the data aggregation and fusion are very important [26
]. Bayesian Neural Network (BNN) was used to establish fusion model of remote sensing data so as to improve the accuracy of archeological information identification [27
]. Almost all the archeological data can be digitized, and platforms for spatial analysis and collaborative work were established to promote data sharing and web browsing, using WebGIS, etc. [28
]. Projects of data aggregation and cultural heritage management were implemented, which aims to improve the capacities of conservation and promote data sharing [23
]. Standardization is the important task of these projects. It is also necessary to avoid making the data complicated and lengthy [31
]. The technologies mentioned above has been proved to be valid and effective in data acquisition in archeology. Meanwhile, they will also generate a large amount of data, whose aggregation, fusion, and representation are very useful to reuse.
In the study of the origin of civilization, it is necessary to collect, process, and integrate archeological data of multiple sites. At the same time, it requires data sharing among scholars. Considering the distinguished features of Chinese grand sites, which often include rammed soil walls, further research on standards and specifications, as well as archeological data aggregation and sharing is required. In this paper, the challenges of archeological data aggregation and sharing was first discussed based on the analysis of the archeological research process, data flow, and the properties of archeological data of grand sites. Then, spatial scales of archeological research, and the classification and coding of archeological data of grand sites in Neolithic Age was proposed, in order to facilitate data acquisition, processing, and representation. The spatio-temporal framework of archeological data of grand sites was also proposed, for the sake of data fusion and spatio-temporal analysis, etc. Finally, the archeological information cloud platform of grand sites based on spatio-temporal big data was designed and built, which was applied to the Origin of Chinese Civilization Project. The methods and platform proposed in this study will promote the aggregation and sharing of archeological data and improve the work efficiency of interdisciplinary research. It will also enhance the scientificity and accuracy of the identification of site value and the interpretation of the past.
4. Construction of Archeological Information Cloud Platform for Grand Sites
4.1. Archeological Spatio-Temporal Data of Grand Sites
The archeological spatio-temporal database of grand sites mainly includes fundamental geographic data covering the site and nearby, data generated by archeological excavation and investigation, environmental information data, three-dimensional model data, etc.
Fundamental geographic database. The fundamental geographic data include four categories—digital elevation model, topographic map, satellite images and aerial images. The scales of vector data covering the grand site and nearby is 1:250,000 and 1:10,000, as well as 1:500 of core area of grand site. The raster data include ETM with resolution of 30 m, SPOT images with resolution of 2.5 m, QuickBird images with resolution of 0.6 m, and aerial images with 0.1 m, which covered different periods.
Archeological database. Under a unified spatio-temopral framework, a spatio-temporal database of grand sites is created, which is mainly about data of sites, ruins, relics and spatial associations among them. Specifically, the database includes site boundaries, site functional areas, site plans, site description information, data of ruins and relics, and so on.
Environmental information database. The environmental information database includes the environmental data of the site and nearby areas, such as the water system, residential area, vegetation and landform, etc.
Three-dimensional model library. Based on the data of archeological excavation (sites, ruins and relics), three-dimensional models are constructed under the guidance of archeologists. The archeologists, who carried out the excavations, have a good understanding of archeological excavation data and literature data. After years of studies, they know what the ruins were, how they were built, how they were used, and so on. With three-dimensional models and the interpretation of the sites given by archeologists, the past of the site can be restored in the virtual environment.
4.2. Architecture of Archeological Information Cloud Platform for Grand Sites
By using centralized management and intelligent scheduling of computing resources, cloud computing conveniently and dynamically provides users on-demand with services such as computing, storage, application software, and data through the network [42
]. Based on the above characteristics and advantages of cloud computing, the archeological information cloud platform for grand sites is conducive to the formulation and implementation of unified archeological data standards and specifications. The platform can provide better system security and data security strategies, more convenient software services and data services, and technically provide online data access for multidisciplinary researchers and the public. Besides, the archeological information cloud platform allows archeological institutions to focus on research and reduce investment in hardware facilities, application software, data and platforms, etc. The platform can improve the overall information level of the archeology industry. Figure 4
is the logical architecture diagram of the archeological information cloud platform for grand sites. The architecture is divided into four layers—infrastructure layer, data layer, platform layer, and application layer.
According to the content, process and complexity of archeological research, the archeological information cloud platform for grand sites must meet the following three needs. First, it can conduct data acquisition, editing, management, inquiry, statistics, mapping, and output of archeological data. Second, it has the ability to carry out spatial analysis on archeological data to transform data into information, and then information into knowledge. It provides quantitative analysis and auxiliary decision support for archeological research. Third, grand sites can be displayed dynamically and multi-dimensionally. Through multi-scale dynamic display of the site, ruins and relic data, the spatial form and settlement environment of the grand site can be visually displayed, and the key ruins can be restored in three dimensions through modeling.
4.3. Archeological Information Cloud Platform Deployed on Demand
The archeological information cloud platform for grand sites can be logically divided into different archeological information platforms on demand. Based on the various types of cultural heritage administrative departments, the archeological information cloud platform can be logically divided into different platforms through the control of data authority and function authority. The platform can be divided into the national archeological information platform for grand sites, the provincial (municipality directly under the central government) archeological information platform for grand sites, and the municipal and county archeological information platform for grand sites, etc. The platforms meet the management requirements of the administrative departments of cultural heritage at all levels (Figure 5
Many sites in a certain region need to be researched for some kinds of archeological studies, such as the studies of the origin of civilization in the Yellow River basin, the origin of civilization in the middle and lower reaches of the Yangtze River basin, and the formation and development of Erlitou culture, etc. Therefore, an archeological information platform is needed to aggregate data of different grand sites in the same platform, so as to support the interdisciplinary study. For this kind of archeological study, the above-mentioned archeological information cloud platform can play a very important role. It can be logically divided into different regional archeological information system on demand, for example, the Yangtze River basin archeological information platform. There is no need to build a new archeological information system from scratch, which saves lots of time and investment funding, and fully reflects the flexibility of the cloud platform.
With the application of technologies in the archeology and conservation of grand sites, such as digital photogrammetry, three-dimensional laser scanning, GIS, remote sensing and so on, the question of how to integrate the data of multiple sites and multiple spatial scales to promote archeological data sharing still needs further research. The methods proposed in this paper are mainly to promote the standardization of grand site archeological data acquisition, processing, database building and use, which will facilitate the aggregation and sharing of archeological data. In the situation of digital archeology, it is mostly technicians from other professional fields, not archeologists, who collect data in the fieldwork and later process data in-lab, making use of digital technologies. Therefore, it is particularly important to establish standard specifications from the perspective of archeology and technology [18
Classification and coding provide one of the most important standards for archeological data acquisition and processing, and are the basis of data sharing and data quality inspection [41
]. Through classification and coding, it is easy to know which class the data should be classified into. This will simplify archeological data acquisition and processing, and promote standardization. It is fundamental to direct data acquisition, processing and warehousing in the field of archeological excavation, reducing intermediate links and improving data processing efficiency. Technologies such as digital photogrammetry and laser scanning are used to carry out data acquisition in the fieldwork, but these raw data require a lot of subsequent indoor processing [23
]. Information must be extracted from the raw data according to archeological requirements. Under these circumstances, the extracted information will be classified and stored into different feature classes according to the classification and coding, which potentially improves the data quality and promotes data reuse. Spatial scale is the basis for archeological data acquisition and data representation, which indicates what data should be collected and facilitates the determination of data scale and resolution under different archeological research scales. Correspondingly, during visualization, related data will be extracted from the database according to the displayed spatial scale. As shown in Figure 9
, the data, data scale, and data resolution of each scale are different. For example, for the same tomb, when the plane of the grave area is displayed, the tomb is represented as a point. When the layout of the tomb is studied, it is represented as a polygon. To sum up, the classification and coding and spatial scales play a vital role in archeological data acquisition, processing, aggregation, and reuse.
Archeological data have significant spatio-temporal characteristics. The spatio-temporal framework of archeological data is the foundation of archeological data aggregation and data organization, which is also the basis of spatio-temporal analysis of the formation of grand sites and the evolution of civilization. As shown in Figure 10
, with a unified space-time benchmark, the evolution of archeological culture in China from 7000 BC–2000 BC is displayed, which intuitively tells the public and scholars the evolution process of archeological cultures in China. The excavation time, data collection time and corresponding archeological cultural period of the archeological entities were recorded during data acquisition and processing. Using these times and the spatial association among sites, ruins, relics and strata, we can trace the archeological excavation process back in the information space, although archeological excavation is irreversible in field.
Archeological information cloud platform is flexible, dynamic and on-demand regarding resource allocation, with better system security and data security strategies. With a large number of historic sites, China has five levels of cultural heritage administration departments from top to bottom. There is at least one archeological research institution in every province. If all these administration departments and institutions build information platforms individually, it will require a huge investment and a heavy workload. In a sense, it is also a huge waste. Through the control of data authority and function authority, a new archeological information platform can be logically and quickly generated to meet different management and research needs. Thus, the investment on informatization would be greatly reduced. More importantly, an archeological information cloud platform is conducive to the implementation of unified data standards and data sharing, providing a more convenient way of completing data online processing and online publishing, greatly shortening the time for the publication of archeological data, and providing archeological research results. The safety and convenience of the platform would be attractive for scholars to use the platform. If the platform is used by more and more scholars to gather data, study and communicate, it will become a public platform for researchers, data owners, the public, and administrators to participate in the conservation of grand sites. If this occurs, then the platform will promote archeological data sharing and interdisciplinary research.
The methods and platform in this paper are very valid and efficient in the Erlitou site and Taosi site. There are hundreds of thousands of sites in China, and the types and periods of these sites are different. The paper only proposed the classification and coding of grand sites from 3500 BC–1500 BC in the Neolithic Age, and its validity for other sites needs to be verified. The feasibility and necessity of the archeological information cloud platform was investigated, and a platform was designed and developed for Exploring the Origin of Chinese Civilization Project. As for how the platform can be popularized and applied to all archeological institutions and administration departments in the country, the current study does not demonstrate who should be in charge of the establishment and operation of the platform and the development of the corresponding management mechanism. These areas will be studied in future work.
The paper has given an account of the challenges of archeological data acquisition and aggregation. The dissertation has investigated the spatial scales of archeology, and seven spatial scales and the corresponding data are presented. The classification and coding of archeological data of grand sites from 3500 BC–1500 BC was also proposed, so as to simplify the data processing, improve data quality, and promote data sharing. From the perspective of archeologists and big data, a spatial-temporal framework of archeological data was established. Corresponding to this framework, an archeological cloud platform of grand sites was developed. Taking the Erlitou site and Taosi site as examples, the methods proposed in this study is verified to be valid. The origin of civilization is a common research topic for human beings. As a result of the nature of interdisciplinary collaboration, the research on the origin of civilization needs archeological data of many grand sites and the results of archeological studies. Due to the archeological features of the grand sites mentioned earlier in this paper, archeological data are of great importance to archeological research. The purpose of the current study was to provide a standard specification and information platform for data acquisition, processing, aggregation and fusion for archeological data of different grand sites or different periods, and finally promote the sharing of archeological data, which gives full play to greater value and produces more benefits [48
This study has shown that the classification and coding, spatial scales and spatial-temporal framework can effectively collect, process, aggregate, fuse, and organize multi-source heterogeneous data of different grand sites or different periods. Basic information, such as data categories and geometry types, can be obtained through the code, which facilitates data retrieval and quality inspection in the information system. The platform offers multi-scale and multi-dimensional representation of archeological data of grand sites, according to the customs of archeologists. The correlation and spatial relationship of sites, ruins and relics can also be displayed intuitively. With the advancement of data opening and sharing, an archeological “data ocean” will eventually be formed [16
]. The archeological information cloud platform can provide services to archeological institutions, such as data acquisition, processing, storage, representation and spatial analysis, etc. Besides, it also offers lots of support to various types of interdisciplinary research, such as data, collaborative work, visualization, analysis tools, and so on. The third general investigation of immovable cultural heritages has shown that there were 193,282 sites with varying types, sizes, and historical periods in China. In addition to Erlitou and Taosi, there are more than 30 other grand sites studied in project of the Origin of Chinese Civilization, including the Liangzhu site. With the application of internet plus, big data, cloud computing, Internet of Things, and other technologies in the archeology and conservation of grand sites, the varieties and quantity of archeological data will continue to grow rapidly. The results of the current study are of great significance to the conservation of grand sites, especially for those under threat.
Almost every profound transformation in archeology is closely related to the penetration of natural science into archeology [49
]. The application of spatio-temporal big data and cloud computing in archeology will provide a new paradigm for archeology [18
]. Data opening and sharing is a new trend, which increasingly affects archeology as well. Archeologists should embrace cloud computing and big data with a more positive attitude. Together with administration agencies and experts from other disciplines, archeologists can actively explore the corresponding management mechanism, data privacy, data intellectual property, data ethics, a data resource catalog, and other standards and norms for archeological data opening and sharing. In this case, the change will promote orderly and safe sharing of archeological data, and the value of archeological data will increase. Furthermore, it will promote the sustainable development of conservation and use of grand sites through sharing.