DYNAMIC MULTIDIMENSIONAL ONLINE DATABASE FOR THE COMPLETE MAPPING OF AN ECOSYSTEM

The present invention relates to a method for making a dynamic database.

The present invention also relates to a dynamic database, a search method in the dynamic database and a search platform.

Furthermore, the present invention relates to respective computer programs for making the dynamic database and for the search method.

In other words, the present invention relates to the field of the development of advanced database systems to be used in the B2B projects in the different sectors of the economy, more specifically in the search for architectures for web platforms for Business Directory that guarantee to have increasingly timely and reliable information.

These are therefore productivity tools used increasingly frequently for industrial researches of competitive products and processes or for the identification of potential suppliers or customers in the manufacturing sector through online Business Directory platforms that guarantee to provide information with the maximum technical detail in order to be able to efficiently identify online all the bodies that meet the requests.

The industrial system appears increasingly interested both in enhancing its network of partners and in developing knowledge and innovation networks to consolidate its structure and thus be able to certify the existence of its own network of qualified partners able to guarantee the reliability and the efficiency of the supply chain within its ecosystem.

The term “ecosystem” will be understood herein as a system comprising products, services, bodies and the like of the same relevant sector, for example one among the “textile”, “clothing”, “mechanical”, “drugs”, “tourism”, “automotive”, “food” and similar sectors. In every economic sector there is an incessant growth of web-based applications intended for the B2B and B2C markets through which users are able to interact with a variety of proposals and therefore to make choices.

Information today is the most important asset for every economic sector: for this reason, the largest search engine operators (e.g. Google, Bing, Yahoo, Ask, AOL, Baidu and similar) continuously carry out a search activity through automatic “crawling” of the Web in order to identify all new contents, web pages, images and videos and catalogue the relative information that can be displayed as results for the searches of their users.

The focal point of all this activity is the provision of increasingly rich, precise and reliable information through online searchable archives.

All the main known Business Directory platforms, in the main search activity (query), operate in a similar way by initially presenting a series of filters to identify the macro-sector, the specific sector according to predetermined categories and therefore the geographical area on which to start the search in their databases, and as a result they present a list of companies with a series of general information, often with the contact details.

The B2B platforms and directories are generally based on the system of “keywords” that are initially chosen by each subscriber to characterize the specificity thereof. In general, each user, at an initial profiling step, is asked to indicate the sector in which they operate and to choose a category and some products or services offered. These choices constitute the basic information and the initial keywords for the technical profiling of the subscriber and serve to improve the visibility (SEO) in search engines.

In addition, the keywords entered by the user are used by the internal algorithms, together with the terms used to describe the company activities, to compose a series of index tables used by the platform in the query step.

The results of the searches on these platforms are a function of the match found by the algorithm of the platform between the search term entered and the data contained in the database through the index tables. These are two different modes: the one of the keywords entered during the profiling step by the subscriber in a platform responds to their own direct need to communicate their specific activity; the one generated automatically by the search engines is based on more complex algorithms that can only be partially managed by the user.

The solutions offered by the market today in the field of the B2B Business Directories all highlight a high criticality due to the obsolescence of the original architecture model of the general master database of subscribers, simply enriched by a more or less numerous series of tables/indexes relative to the keywords set by the customer (generally in a limited number and linked to the package purchased) and to the result of search engine algorithms, aimed at being able to always extract in any case lists of subscribers in the face of any set search.

The solutions available today appear as an evolution of the now obsolete online yellow pages with the list of companies that, perhaps, have only some of the characteristics sought.

In addition, there are strict limits to the number of keywords that a user can freely create for their own needs, if allowed by the platforms. If each keyword entered ex-novo has to create a new index table, it is clear that this multiplication could cause slowdowns.

The keywords entered by the subscriber, where provided, simply have a relative optimization function for the positioning of the web resource in the search engines and in the operation of the proprietary algorithm itself, thus reducing itself to a tool for highlighting the website.

The keywords entered by the user often appear unreliable as similar keywords may have conflicting meanings for the different users or different keywords may refer to the same product.

For example, today it is not possible to carry out articulated searches on a greater number of keywords, for example to find companies able to respond with an offer corresponding to the keywords of the search, as there is no alignment of the meanings of the keywords conceived in a coherent way.

The global vision of the ecosystem within which the search is being performed on the platform and therefore of the meaning of the keywords set by the individual users as characteristic elements of their activity are also completely absent.

With the currently available systems it is very difficult, if not completely impossible, to carry out complex searches if it is required that several features are present at the same time, or some as an alternative to others or that some are present and others are completely absent.

In addition, the lack of uniformity and shareability of the meanings of the different keywords entered and used for the searches appears to be particularly serious and penalising: this aspect often entails the lack of significance of the results.

It therefore follows that the power of the web has not yet been fully used in the development of adequate solutions for the architecture of the Business Directory platforms capable of representing the complex of the available information in a biunivocal manner.

The technical task of the present invention is therefore to make available a method for making a dynamic database, a dynamic database, a search method in a dynamic database, a search platform and respective computer programs of the realization method and of the search method which are able to overcome the prior-art drawbacks which have emerged.

The object of the present invention is therefore to make available a method for making a dynamic database, a dynamic database, a search method in a dynamic database, a search platform and respective computer programs of the realization method and of the search method that are able to guarantee more effective solutions to the increasingly stringent need to have timely and reliable information.

A further object of the present invention is to propose a method for making a dynamic database, a dynamic database, a search method in a dynamic database, a search platform and respective computer programs of the realization method and of the search method that can guarantee each member (or body) belonging to a certain ecosystem (or system) to be able to specify with the maximum technical detail all the characteristics of their offer or request (products or services) so as to make it possible to identify online all the bodies that respond exactly to those requested.

A further object of the present invention is also to make available a method for making a dynamic database, a dynamic database, a search method in a dynamic database, a search platform and respective computer programs of the realization method and of the search method that are able to guarantee the online management of large amounts of coherent and shared information through simple and collaborative systems, adapted to allow targeted, immediate, reliable and trustworthy links among companies also to respond promptly to the challenge and opportunities of the markets.

Another object of the present invention is to make available a method for making a dynamic database, a dynamic database, a search method in a dynamic database, a search platform and respective computer programs of the realization method and of the search method that are able to overcome the generic data base market founded on the realization of data bases of companies conceived only as supplier showcases, replacing it with one based on the technical, technological, process and experiential characteristics of the fundamental aspects of each individual ecosystem and on the sharing of specialized know-how in the definition of the characteristics of the individual subsystems.

The stated technical task and specified objects are substantially achieved by a method for making a dynamic database, a dynamic database, a search method in a dynamic database, a search platform and respective computer programs of the realization method and of the search method comprising the technical features set forth in one or more of the claims. The dependent claims correspond to possible embodiments of the invention. In particular, the technical task and the specified objects are substantially achieved by a method for making a dynamic database comprising the steps of defining a system identifying a relevant sector, wherein said system comprises products, services, bodies and the like belonging to said relevant sector, defining a first type of elements of the system comprising elements identifying bodies operating in the relevant sector and defining a second type of elements of the system comprising elements identifying products and/or services dispensable or enjoyable by the bodies operating in the relevant sector.

The method also envisages identifying a plurality of subsystems interconnected to one another and comprising respective elements of the first and second type and for generating, for each subsystem, a linearised hierarchical tree structure, in particular implemented by means of a linearised taxonomy tree, comprising the elements of the second type.

The method also envisages defining a dependency relation between the elements of the first type and each linearised hierarchical tree structure, in particular implemented by means of a taxonomy tree.

In particular, any information relative to a specific event or situation that is intended to be examined is obtained only by analysing and correlating a multiplicity of data, which can often be obtained from a plurality of sources in specific databases. Therefore, to obtain the necessary information in a given search, it is often necessary to resort to recursive operations of extraction of data from a plurality of archives functionally correlated to each other only for that specific search.

In fact, the value of the content of the data of each individual record in any database is determined only by its possibility of being “extracted” and related to other data of other records so that it can constitute a useful piece of “information” for a potential user.

It is therefore very important to possibility of easily relating the different databases pertaining to or falling within the same Ecosystem, where Ecosystem means here an economic system whose population or elements interact with each other with functional, operational or economic links; with this meaning the “textile”, “clothing”, “mechanical”, “drugs”, “tourism”, “automotive”, “food” and similar ecosystems can be indicated.

The operators of each Ecosystem within the scope of their activity need to maintain continuous and up-to-date relations with each other on different common aspects of their sector (technical, information, production, commercial, investments, services, training and the like) and often, in order to expand these relations, they are forced to carry out searches on the Web with almost always frustrating results as at present there are no solutions able to provide coherent solutions within the same Ecosystem.

According to one aspect of the present invention, the system (or ecosystem) is articulated into multiple subsystems at multiple levels that represent different “perspectives” of the same system. Each subsystem is to be considered in relation to the others of the same system or subsystem.

According to one aspect of the present invention, each hierarchical structure, in particular implemented by means of a taxonomy tree, contains the technical characteristics, the products, the production specificity and constitutes the central core of the system. The hierarchical structure, in particular implemented by means of the taxonomy tree, has been designed to ensure the orderly development of the elements.

According to one aspect of the present invention, the dependency relations consist of tables (binary matrices) generated in a profiling step for each subsystem that relate the elements of the first and second type, allowing an immediate mapping of the entire ecosystem.

According to one aspect of the present invention each ecosystem in its complexity is photographed in the binary matrices and thus all relation information is immediately accessible online without further query activity.

Furthermore, the stated technical task and specified objects are substantially achieved by a searchable dynamic database generated (i.e. realized) by a realization method according to one or more of the features described in the present invention. The database comprises a first type of elements identifying bodies operating in the relevant sectors, a second type of elements identifying products and/or services dispensable or enjoyable by the bodies operating in the relevant sectors.

For each relevant sector, the second type of elements is ordered according to a hierarchical structure, in particular implemented by means of a taxonomy tree model.

The database also comprises dependency relations between the elements of the first type with each hierarchical structure, in particular implemented by means of a taxonomy tree.

Furthermore, the stated technical task and specified objects are substantially achieved by a search method in a database comprising one or more of the characteristics described in the present invention, comprising the steps of selecting a taxonomy tree of a specific subsystem, including and/or excluding specific elements of the second type present in the taxonomy tree and retracing, in function of the dependency relations, specific elements of the second type.

Furthermore, the stated technical task and specified objects are substantially achieved by a search platform comprising a user interface, a database comprising one or more technical features described in the present invention, a control unit configured to perform one or more of the steps of the search method, according to one or more of the technical features described in the present invention, in function of an interaction of a user with the user interface.

Advantageously, through the platform it is also possible to view which elements are absent in the specific ecosystem. In this way, to a user who wants to enter (at the market/business level) a specific sector of interest, it will be immediately clear which products and/or services are absent.

Furthermore, the stated technical task and specified objects are substantially achieved by a computer program including instructions to run the steps of the method for making the database described in the present invention, and a computer program including instructions to run the steps of the search method described in the present invention and to be launched on the platform including one or more of the features described in the present invention.

In one embodiment each computer program is stored in the archive of the user interface device.

In one embodiment, each computer program is stored remotely. In this embodiment, the program is a “SAAS (Software As A Service)” computer program, that is, configured to be implemented only in the presence of an internet connection.

Further features and advantages of the present invention will become more apparent from the indicative and thus non-limiting description of an embodiment of a method for making a dynamic database, a dynamic database, a search method in a dynamic database, a search platform and respective computer programs of the realization method and of the search method.

Such a description will be set out below with reference to the accompanying drawings, which are provided solely for illustrative and therefore non-limiting purposes, in which: figures 1 -3 are schematic representations of different steps of the method for making a database which is the subject-matter of the present invention. figure 4 shows a taxonomy tree on three levels. figure 5 shows a taxonomy tree on three levels with dynamic insertion of additional elements. figure 6 shows the linearised vector of the taxonomy tree of figure 5. figure 7 shows an example of a taxonomy tree of 64 elements of a LAYER A, on 7 levels. figure 8 shows the tree of fig. 7 of 64 elements after linearisation. figure 9 shows the resulting matrix of the relations between the LAYER A of figure 7 and a LAYER B of 100 elements. The present invention relates to a method for making a dynamic database.

The realization method envisages defining a system 1 identifying a relevant sector. The term “system” refers to an ecosystem of products, services, bodies and the like belonging to a sector, for example the textile sector.

The method envisages defining a first type of elements 2 of the system 1 comprising elements identifying bodies operating in the relevant sector.

The method also envisages defining a second type of elements 3 of the system 1 comprising elements identifying products and/or services dispensable or enjoyable by the bodies operating in the relevant sector.

In other words, the method envisages defining the first type of elements 2 and the second type of elements 3 in an aforementioned ecosystem of products, for example one among the “textile”, “clothing”, “mechanical”, “drugs”, “tourism”, “automotive”, “food” and similar sectors.

From a point of view of realization of the method, it is not necessary for the first type of elements 2 to be defined before the second type of elements 3.

In other words, each system 1 can be viewed on at least two overlapping levels.

A first level called “PRODUCT” consists of the second type of elements 3, that is, the activities, processes, products, technologies used and others.

A second level called “OPERATOR” consists of the first type of elements 2, that is, the companies, economic operators, personnel and the like, active in the same ecosystem and who make use of the elements of the “PRODUCT” level for their activity.

The elements of each PRODUCT subsystem are identified with the individual activities, production processes, products, services that best identify in the user community the individual processing steps or the individual products with the respective typifying characteristics.

In other words, the first type of elements 2 that comprises the elements identifying bodies operating in the relevant sector contains, in other words, all the elements that can be defined in some way as “stakeholders” and therefore operational within the ecosystem in question (e.g.: companies, artisans, professionals, associations, suppliers, customers, importers, national exporters, foreign exporters and the like). Thus, the first type of elements 2 defines a subset of the system 1 .

In other words, the second type of elements 3, which comprises elements identifying products and/or services dispensable or enjoyable by the bodies operating in the relevant sector, contains all the elements that can be defined in some way as “passive”, technical and qualitative of the ecosystem in question (e.g.: products, technologies, plants, processing, know-how, specialised skills, raw materials, semi-finished products, final products, accessories, special services and the like) regardless of the operators who normally use them.

The method also envisages identifying a plurality of subsystems 4 interconnected to one another, each subsystem comprising respective elements of the first 2 and of the second type 3.

In other words, each ecosystem, based on specific needs, can be articulated into subsystems 4 that have an adequate degree of homogeneity in order to guarantee their consistency, while maintaining the possibility of relation with the other subsystems 4.

Therefore, each system 1 can be viewed in two levels (or layers) relative to the elements of the first type 2 and to the elements of the second type 3 and articulated into a plurality of subsystems 4 relative to a specific topic of the reference sector.

According to this model, it follows that an element n of the population of a subsystem X of the layer P (PRODUCT) of an ecosystem Y is perfectly uniquely identified through a code Rvxn.

For example, for the “Drugs” ecosystem, the “Antibiotics” system can be identified and the elements of the first 2 and second type 3 can comprise bodies or products relative to “antibiotics”, “commercial drugs” and “pathologies”.

The method also envisages generating, for each subsystem 4, a hierarchical tree structure, in particular implemented by means of a linearised taxonomy tree 5, comprising the elements of the second type 3.

Preferably, the step of generating the hierarchical linearised tree structure, in particular implemented by means of the taxonomy tree 5, is performed by assigning a hierarchy of the elements of the second type 3.

Preferably, the step of generating the hierarchical linearised tree structure, in particular implemented by means of the taxonomy tree 5, is performed by storing a generation index of each element of the second type. As will also be reported below, the hierarchical structure implemented by means of a taxonomy tree 5 is linearised by transposition of all the elements of the taxonomy tree on a linear vector. In general, the data to be used in any data base so as to have an adequate significance of information and not give rise to misunderstandings must be able to be linked in a hierarchical tree structure capable of correctly defining the meaning thereof.

Each data must be able to be connected to another one hierarchically at a lower level to which it can be given full meaning.

For example, the elementary data “cup” assumes different meanings if hierarchically connected in a taxonomy of a food ecosystem (cured meats), rather than in the automotive one (oil sump) or mechanical processing (deep drawing).

Hence the need for a hierarchical data architecture through, for example, the system of the taxonomy trees articulated into a plurality of hierarchical levels able to attribute to each element its paternity from which the information content derives.

Figure 4 attached shows a taxonomy tree on three levels in which: o Prod2 = first child of Prodi o Prod3 = second child of Prodi o > o Prodi 1 = third child of Prod4

And so it can be written that: o Prod2 = f(1 , Prodi ) o Prod3 = f(2, Prodi ) o Prodi 1 = f(3,Prod4)

More generally ProdX = f(Y,ProdZ)

In a dynamic taxonomy tree structure, it could be obtained that at later times leaves or branches are added with sequential numbering but distribution on the various levels (see example shown in the attached fig. 5)

In this case, the added elements Prodi 2, Prodi 3, Prodi 4, Prodi 5 and Prodi 6 (different colours) always acquire a meaning based on their placement in the taxonomy tree even if they were added later.

Therefore, given the articulation and the complexity of the technical specifications of each ecosystem, the individual elements constituting each subset can be validly represented as “nodes” and “leaves” of a specific taxonomy tree 5, specifically linearised with a suitable algorithm capable of preserving the hierarchy thereof of the levels.

While the two-dimensional representation of the taxonomy tree always allows a direct interpretation of the meanings thereof as the hierarchical connections are visible, the transposition of the elements of a taxonomy tree into a linear vector entails the need to use a special linearisation algorithm that allows each element inserted in the vector to be associated with the respective positioning parameters in the tree.

This aspect becomes particularly important in a dynamic structure of the taxonomy tree that must provide for a growth over time of both the leaf elements and of the levels.

The linearisation algorithm therefore allows to retain detailed information on the positioning of each element in its taxonomy tree (paternity, level, degree of offspring) even in the later steps of the development of the tree.

The vector of the data resulting from the linearisation is then associated with a table that details the hierarchical situation thereof for each element.

In this way, a taxonomy tree on multiple levels and dynamically developed over time is fully represented with a simple linear vector with increasing size.

Figure 6 attached shows the linearised vector of the previous taxonomy tree, where the colours of the subsequent additions are shown.

In a generic subsystem 4 of the second type of elements 3 belonging to a system 1 whose individual elements can be correctly defined, they can be represented as “leaves” according to a taxonomy tree model: each “leaf” of the tree (which represents an individual element of the ecosystem) can be uniquely identified in the taxonomic classification by the “node” from which it is generated and by the progressive order number thereof relative to the same node 6 (first leaf 3a, second leaf 3b, third leaf 3c and so on). It should be noted that each node 6 in turn derives from a “leaf” originated from a previous node according to a progression of levels and of generations.

In the case of a generic ecosystem, each individual element can be perfectly and biunivocally represented by a “leaf” of the corresponding taxonomy tree 5.

An ad hoc algorithm has been developed to ensure the management of the tree taxonomies for the various subsystems 4 and a correct display of all the elements of the tree 5 in the different levels. In the initial start-up step, some parameters (number of levels provided, maximum number of elements provided for each level) necessary to establish the exact placement of each element in the tree representation 5 are defined for each subsystem 4.

Each element 3 is therefore stored with the “genealogical” indications thereof (paternity, degree of offspring, number of any children, relevant level, taxonomic order number).

For each “leaf” it is therefore possible to indicate the progressive number of creation of the respective leaf since the “germination” of the leaves is dynamic and unpredictable as in the real case of a system 1 , the development, the definition and the insertion of further individual elements of the second type 3 (products, services, characteristics,...) takes place without a predictable chronology and generally in subsequent steps and therefore the development and the description of the relative taxonomy tree 5 is necessarily dynamic, having to provide for the possibility of a simultaneous and misaligned development of the individual nodes and leaves.

The indexes of the generated “leaves” are created and kept dynamically up to date, connecting by means of special algorithms the progressive numberings and the corresponding taxonomic classifications of the relative tree, so as to eliminate the potential risk of possible misalignments and redundancies.

In this way, the dynamic linearisation of the taxonomy tree 5 is obtained, so that it can be represented by a vector composed of n integer values [1 ,2,3,4, 5,..., n] equal to the number of the “leaf” elements, thus maintaining the “genealogical” certainty and therefore the meaning of the respective elements.

The method also envisages defining a dependency relation between the elements of the first type 2 and each taxonomy tree 5.

The step of defining the relation of the elements of a subsystem 4 is performed via a binary matrix wherein the rows, in particular defined by a first linear vector, are formed by the elements of the first type 2 and the columns, in particular defined by a second linear vector, are defined by the elements of the second type 3.

The technical effect is an immediate mapping of the system 1 .

According to the invention, the step of defining the relation of the elements 2, 3 of the subsystem 4 performed via the binary matrix envisages: assigning in the binary matrix a value 1 to a match between an element of the first type 2 with an element of the second type 3, assigning in the binary matrix a value 0 to a mismatch between an element of the first type 2 with an element of the second type 3.

Each relation is therefore fully representable and identified by a binary matrix whose rows consist of relation vectors referring to the individual elements of the first type 2 of the relation, while the binary columns in turn refer to the corresponding elements of the second type 3 of the relative linearised taxonomy tree 5.

In this way, through a special algorithm, each element of the first type 2 expresses its “choices” of the different subsystems 4 of its interest by acting directly on the relative taxonomy trees 5. These choices are linearised and converted into vectors with length equal to the number of elements of the second type 3.

By iterating this profiling process for all the elements of the first type 2, a number of binary vectors with the same length are obtained that together make up the binary matrix with a very high degree of compactness and consistency of meaning.

In general, in the construction of the matrix, the data of the LAYER A and LAYER B must be available in the form of linear vectors that constitute the two dimensions of the matrix.

If the data of a LAYER are organized in the form of a taxonomy tree, they must first be linearised by means of the relative algorithm

The result is therefore a matrix M where

M = MATRIX {A,B]

For example:

LAYER A - DATABASE built around the technical domain of the considered ecosystem (metallurgy, physics, aerospace, automotive,) with all the relative known data “technology, processes, products, know-how, ...” and represented by a taxonomy tree

LAYER B - DATABASE built around all the stakeholders of the same ecosystem, built simply as progressive master data and therefore without the need for linearisation.

Figure 7 shows an example of a taxonomy tree of 64 elements of LAYER A on 7 levels. Figure 8 shows the 64-element tree after linearisation

The LAYER B consists of a DATA SET of 100 stakeholders from P01 to P100 (identified in the relative master data)

The resulting matrix of the relations between the LAYER A and the LAYER B is shown in figure 9 The significant relations are highlighted in the matrix of figure 9 by a black ON BIT (1 ) at the relative intersection between two elements, one for each layer involved.

The dynamics of the relation matrix is based on the corresponding dynamics of the two Data Bases (LAYER A and LAYER B) used. For example, considering the relation matrix M between the two LAYERS A and B of an ecosystem, by way of example the following applications can be assumed in different ecosystems.

In a further example of detail, an operator/user belonging to a specific technical sector (for example that of footwear) is shown, who intends to make themselves visible within the database, when registering in the database they will select in figure 1 one or more specific subsets 4 identifying, in general, the product or service. For example, the operator will select the subsets 4 relative to the “shoes” and to the “sandals” and, in the specific taxonomy trees 5 (such as, for example, the one of figure 3), they will indicate the elements of the second type 3 (i.e. the types of processing, material used, the models of the shoes/sandals and other similar products), for example the elements 3a, 3b and 3c.

In this way, a new element of the first type 2 will be added to the database (as, for example, schematically represented in figure 2) that will belong to specific subsets 4 and will be associated with specific elements of the second type 3 or with specific taxonomy trees 5.

Advantageously, through the complete and dynamic mapping of the different subsystems 4 of each system 1 , supported by the linearised tree taxonomy 5, it is allowed the creation and the management in real time of integrated and complete as well as dynamic, reliable systems enriched by an almost infinite amount of coherent information available for immediate online queries. In detail, the mapping system of the invention allows to relate the elements of two different Databases relative to the same ecosystem in order to immediately highlight all the interrelations (real or potential) between the individual elements of each database, thus helping to give full visibility and representativeness of the different aspects (layers) of the Ecosystem.

It is therefore a MAPPING aimed at identifying all the characteristics of an ecosystem with the maximum possible degree of detail; it is described according to the invention, therefore, a MAPPING and not only the generation of a database

According to the invention, two successive steps are performed: a. First of all, the MAPPING of the ecosystem is required b. then a QUERY I SEARCH can be run

MAPPING means taking a photograph of the entire ecosystem with the degree of precision I detail (pixels) necessary for the subsequent, predictable analyses or searches - (see example figure below)

For example, the MAPPING of a generic ecosystem can be 100 X 64 elements equal to 0.8 kB.

The realization of a MAPPING of an entire ecosystem takes place according to the following steps: a. Definition: First of all, it is necessary to define the contours of the ecosystem with the main characteristics thereof and possibly subdivide it into several subsystems with an adequate degree of significance b. Development: Identification of the main types (layers) of the parts/stakeholders of the ecosystem (or of each subsystem) that have substantial coherence between them. See below some examples of different ecosystems with the detail of the possible connected databases: i. manufacturing (textile, automotive, mechanical, health...): technologies, products, processes, skills, customer companies, suppliers, workers, ii. pharma: active ingredients, medicines, pathologies, drugs, companies iii. territorial systems: hospitality, catering, logistics, transport, cultural heritage iv. complex constructions: technologies, bridges/viaducts, critical components, suppliers v. human resources: skills, experiences, education, agencies, companies c. Architecture: each layer consists of a dynamic Database structure, organized according to its specific type either linearly (pure sequential) or through a hierarchical taxonomy tree structure capable of guaranteeing the consistency and the retention of the data and of the relative information d. Relationship: create a binary matrix of relation between the pairs of layers of the ecosystem, in order to highlight with the required degree of detail the interrelations between the elements of each layer (Linearised databases). e. Population: the population of each layer can be achieved progressively and dynamically both manually by the users and automatically through Al (Artificial Intelligence) algorithms.

Some examples follow: a. As part of a project MOUNTAINS INNOVATION ECOSYSTEMS and Research Topic “resilience of the production and supply systems in the mountain environments”, a binary Mapping matrix of the ecosystem was developed comprising all the main stakeholders of the territory in order to allow the online availability of accurate information and immediate contacts among all the members of the network; b. For an innovative project on the ecosystem “large civil infrastructures of a territory (viaducts, skyscrapers, real estate complexes)” it was proposed to use a Mapping of the entire ecosystem containing all the technological characteristics, components used, construction companies, for a rapid identification of the potential criticalities and programming of maintenance interventions.

TECHNICAL EFFECTS guaranteed by the system of the invention that exploits the binary matrix architecture are:

DATA COMPRESSION: The structure of the RELATION TABLE between two layers of the ecosystem made with a Binary Matrix allows a very high compression of the data since each piece of information relative to the relation existing between the elements of the layers A and B is represented by the content (0;1 ) of the single bit of the position (x;y).

With this data architecture, assuming, for example, an ecosystem with a layer A of 64 elements and a layer B of a thousand elements, an extremely compact matrix of relations M would be obtained occupying only 8 KB.

• HIGH SPEED SEARCH: This significant reduction in size compared to a traditional relational database architecture (reduction often greater than 10X) allows the entire relation matrix to be loaded directly into the memory in order to be able to carry out any kind of processing, searches and filterings directly in the memory, thus considerably increasing the speed of these operations.

In the case of searches on ecosystems with very large sizes of the Layer A or Layer B, the resulting relation matrix can be broken down into several standard-sized sub-matrices 64x1000 (chunk) of 8KB each to allow only the elements essential for the search to be loaded into the memory, further increasing the performance of the system.

MULTIPLICITY OF THE RELATIONS: The architecture of the system makes it possible to relate all the different structural Layers of the ecosystem, thus allowing a plurality and a much more immediate and easier completeness of analysis than the traditional systems focused exclusively on the use of generic keywords. SEARCH WITH SPECIAL FILTERINGS - The use of the Binary Matrix for the representation of the existing relations among the components of the two Layers under examination allows to carry out searches applying all the Boolean operators also in cascade to carry out filterings of great precision in order to identify the elements of the Layer B that have exactly the characteristics required with respect to the elements of the Layer A.

This type of Search with special filterings is completely impossible in the current search systems of the traditional platforms.

For example: it is possible to perform a search to identify all the elements of the layer B that with respect to the elements of the Layer A:

• strictly have the characteristics Ax, Ay, Az and

• simultaneously do not have the characteristics Ai, Aj, Aw and

• have at least x% of the characteristics Af, Ag, Am

The present invention further relates to a searchable dynamic database generated by means of a realization method as described above.

The database comprising a first type of elements 2 identifying bodies operating in the relevant sectors and a second type of elements 3 identifying products and/or services dispensable or enjoyable by the bodies operating in the relevant sectors. For each relevant sector, the second type of elements 3 is ordered according to a taxonomy tree model.

The database also comprises the dependency relations between the elements of the first type 2 with each taxonomy tree 5.

In the searchable dynamic database, the relevant sector comprises one among the “textile”, “clothing”, “mechanical”, “drugs”, “tourism”, “automotive”, “food” and similar sectors.

In the searchable dynamic database, the first type of elements 2 identifying the bodies operating in the relevant sector, comprises companies, economic operators, personnel and the like, while the second type of elements 3 identifying products and/or services dispensable or enjoyable by said bodies operating in the relevant sector, comprises activities, processes, products, technologies used and others.

Advantageously, this database architecture allows a great compactness of data defined by the binary matrices and composed of ordered ennuples of binary octets compacted into strings that can be processed through special management algorithms with Boolean operators.

In addition, the database is able to be continuously updated dynamically with cooperation also from the users.

The present invention further relates to a search method for searching a database as described above.

The method comprises the steps of selecting a taxonomy tree 5 of a specific subsystem 4 and of including and/or excluding specific elements of the second type 3 of the taxonomy tree 5.

The method also comprises a step of retracing, in function of the dependency relations, specific elements of the first type 2. In particular, in function of the elements of the second type 3 selected, the method is able to accurately retrace all the elements of the first type 2 operating in the subsystems of interest 4.

According to the invention, the step of retracing specific elements of the first type 2 is performed via the binary matrix, by detecting a presence of a specific element of the first type 2 if in the binary matrix there is a value 1 (black colour) at a match between the specific element of the first type 2 and an included element of the second type 3.

According to the invention, the step of retracing specific elements of the first type 2 is performed via the binary matrix, by detecting an absence of a specific element of the first type 2 if in the binary matrix there is a value 0 (white colour) at a match between the specific element of the first type 2 and an excluded element of the second type 3.

For each query, a user activates their search directly online on the taxonomy tree 5 of the subsystem 4 of their interest, specifying inclusions and possible exclusions by checking the corresponding boxes in such a way as to allow the system to identify all the operators whose offer is consistent with all the multiple requirements of their search.

For example, in the case of an application for a supply chain, the reported operator is able to provide all the products, services, with the characteristics identified in the search.

These choices are then converted into a specific binary vector (whose fields are only “0” or “1 ”) with the same length as the vector representing the linearised taxonomy tree 5 where each “chosen” position corresponds to a “1” otherwise a “0” remains.

Based on these choices, the vector thus generated is used for an instantaneous comparison in the memory with all the corresponding elements (rows) of the binary matrix by means of a special algorithm that exploits the potential of the Boolean operations (AND, OR, NOT, XOR).

This matrix is read only once at the beginning of the search and, given the high compactness thereof, leads to a significant reduction in access and processing times.

Advantageously, the search times are significantly reduced compared to the traditional SQL systems which, even when they had a similar amount of basic information (keywords), should have needed much longer times having to resort to multiple accesses to the database records also through UNION or JOIN operators and external index tables.

The present invention further relates to a search platform comprising a user interface, a database as described above and a control unit configured to run one or more of the steps of the search method described above in function of an interaction of a user with the user interface.

In other words, the search platform allows a user, who intends to find elements of the first type 2 of interest, to have an easy-to-use interface so as to include and/or exclude specific elements of the second type 3.

The present invention further relates to a computer program including instructions to run the steps of the above-described embodiment method.

The present invention further relates to a computer program including instructions to run the steps of the above-described embodiment method. In other words, the above programs are integrated and/or installed in special devices provided with processors and/or control units capable of running the steps of the respective methods in order to generate the database and/or to use the search platform.

Advantageously, the present invention is capable of overcoming the drawbacks which have emerged from the prior art.

Advantageously, the present invention allows a complete and dynamic mapping of the different elements that make up the system 1 .

Advantageously, the present invention allows a very high processing speed, caused by the structure with binary matrices which are readable as single binary records and directly processable as complex matrices.

Advantageously, the present invention allows not having to operate with multiple accesses to the external memories with laborious SQL and JOIN procedures.

Advantageously, the present invention allows a wide variety of search criteria to be created during the query step, based on the flexibility of the Boolean operators (AND, OR, NOT, XOR) that can be used directly by the user to choose the parameters to be used for their searches.

Advantageously, the solution proposed by the present invention is based on the creation for each individual Ecosystem (system 1 ) of a dynamic multidimensional database (MDB) with two or more dimensions (layers) that are like “different views” of the same system in relation to each other: the first layer (LO, base layer or PRODUCT) contains the technical characteristics, the products, the production specificity: it is defined by means of a tree taxonomy to guarantee the progressive orderly development thereof; the second layer (L1 ) (OPERATOR layer) comprises elements identifying the bodies operating in the ecosystem (companies, economic operators, suppliers,...); any subsequent layers (L2, L3,...) comprise further distinctive elements of the specific ecosystem (technology used, pathologies,...). In this way, through the search (query) on a single multidimensional database, it is possible to immediately identify the existing relations among all the data of the different layers (subsystems) related to the same ecosystem, with an enormous saving of time and resources. By way of example, the following layers could be assumed for the database of a generic Ecosystem:

1 . LO Base Layer = Ateco codes, improved in depth of detail;

2. L1 Operator Layer 1 = customers;

3. L2 Operator Layer 2 = suppliers; 4. L3 Technical Layer = technology used;

All the two-to-two ratios between the elements of the individual Layers (LO, L1 , L2, L3) can then be viewed online to cope with any type of analysis or research in the sector.

The relational nature among the different subsystems as well as the dynamic aspect of this relation are therefore evident as each subsystem is by its nature dynamic and therefore the corresponding software envisages the continuous updating of the database.