FORM 2
THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENTS RULES, 2003
COMPLETE SPECIFICATION
(See section 10, rule 13)
1. Title of the invention;
NANOFOOD INFORMATICS
2. Applicants)
NAME NATIONALITY ADDRESS
TATA CONSULTANCY Nirmal Building, 9th Floor, Nariman Point,
Indian
SERVICES LIMITED Mumbai-400021, Maharashtra, India
3. Preamble to the description
COMPLETE SPECIFICATION
The following specification particularly describes the invention and the manner in which it
is to be performed.

TECHNICAL FIELD
The present subject matter, in general, relates to the field of nanofood, in
particular, to a system and a computerized method for structuring nanofood information.
BACKGROUND
Nanotechnology has been applied in various industries, such as material
science, solid sate physics, biotechnology, and cell biology. Nanotechnology has started showing promising effects in applications related to farming practices, food processing, food production, and for use of materials in packaging food items. The food items cultivated, produced, processed, packed, etc., using nanotechnology techniques or tools are known as 'nanofood'.
With the advent of technology, nanofood has been acknowledged as a
discipline that may solve a variety of problems in the food industry by enabling increase in productivity and effectiveness of the food products. Accordingly, efforts are being directed towards developments in the field of nanofood for providing better food processing, packaging and logistics, helping in the design of new healthier and tastier food products, and providing better food safety and quality assurance. As this discipline continues to grow rapidly and its contribution towards benefits of the food industry increases, there is an increase in awareness and understanding about this discipline. Consequently, the requirement of information relating to nanofood, its impact on the consumers and the environment, various ethical and regulatory impacts associated with it, and so on has increased. For example, researchers may require this information in research related activities on various nanofood products, manufacturers may require this information in manufacturing related activities on various nanofood products, and consumers may require this information for awareness purposes.
SUMMARY
This summary is provided to introduce concepts related to nanofood
informatics system. These concepts are further described below in the detailed description.

This summary is not intended to identify essential features of the claimed subject matter nor is
it intended for use in determining or limiting the scope of the claimed subject matter.
Methods and systems for structuring available unstructured nanofood
information and representing the same in a machine readable and processable format are described herein. The method is a computerized method comprising receiving information resource parameters corresponding to information resources having unstructured data, in a nanofood informatics system. From such unstructured data, concept instances are extracted. The extracted concept instances are mapped to one or more predefined concepts in a nanofood informatics repository. Further, the nanofood informatics repository may be updated to include new concepts or edit the predefined concepts in the nanofood informatics repository,
BRIEF DESCRIPTION OF THE DRAWINGS
The detailed description is provided with reference to the accompanying
figures. In the figures, the left-most digit(s) of a reference number identifies the figure in
which the reference number first appears. The same numbers are used throughout the
drawings to reference like features and components.
Fig. 1 illustrates an exemplary network environment implementing a nanofood
informatics system, in accordance with an embodiment of the present subject matter.
Fig. 2 illustrates an exemplary nanofood informatics system, according to an
embodiment of the present subject matter.
Fig. 3 illustrates an exemplary method for structuring and updating
information in a repository associated with a nanofood informatics system, according to an
implementation of the present subject matter.
DETAILED DESCRIPTION
The subject matter described herein relates to a system and method for
disseminating information relating to nanofood to researchers, manufactures and other users who wish to seek information relating to nanofood. The system and method described herein provide for structuring of available nanofood information and storing the structured nanofood information in a machine readable format, such that the system can read and process the

information. The stored information may be retrieved by the users in a human readable format. The system and method described herein facilitate updating the system by adding information, for example, adding latest nanofood information, and/or refining information in the system, for example, editing existing nanofood information such that the information in the system is up to date and free from errors.
Conventionally, large amount of information is available on the web pertaining
to well established fields, such as material science and biomedicine. Such available information is scattered throughout the web in form of unstructured data, such as documents, report, publications, and discussions on web forums. The large amount of available unstructured data makes it inaccessible or remotely accessible to various information seekers, Further, browsing through the large amount of unstructured data on the web and extracting relevant information is a time consuming process and requires a lot of manual efforts. Thus, the conventional means of information dissemination are generally ineffective since most of the information in the well established fields is inaccessible to the information seekers, and retrieval of such information is a tedious and time consuming job.
On the other hand, the field of nanofood is still in a nascent stage and the
amount of information relevant to this field is less as compared to other well established fields. However, like other developed discipline the information related to the field of nanofood is also available in the form of unstructured data, such as documents, reports, web pages, and discussion on web forums. Furthermore, the field of nanofood is emerging and information in this field is consistently increasing, it is likely for the field of nanofood to become information rich in future. If the same conventional means of information dissemination continue to be employed in the field of nanofood technology, it is likely to suffer from the shortcomings of the information dissemination in the well established fields. Thus, an effective means of disseminating information pertaining to the field of nanofood technology is needed for widely disseminating information related to nanofood to the information seekers in an easily accessible manner.
To this end, described herein is a nanofood informatics system that addresses
the aforementioned problems. In an implementation, the nanofood informatics system enables capturing information from the existing unstructured data relating to nanofood, such as

documents, reports, web pages, and forums, structuring the information, and representing the
same in a machine readable format, such as Resource Description Framework/Web Ontology
Language (RDF/OWL) schema. Such structured information relating to nanofood may be
disseminated to the users, such as consumers, researchers, and manufacturers, in a human
readable format, such as textual format. In an implementation, the user may query the
nanofood informatics system for retrieving such structured information.
As mentioned previously, the nanofood is an emerging field. Accordingly, the
information related to the field of nanofood is growing in form of new publications, reports, web pages etc. However, the information present in the publications, reports, web pages etc. is usually in an unstructured format. The nanofood informatics system continually scans such publications, reports, and web pages in order to extract the relevant information therefrom. Such extracted information may be stored in the nanofood informatics system, thereby resulting in expansion the nanofood informatics system as a result of which the nanofood informatics system consistently grows and is in sync with the developments occurring in this emerging field. The nanofood informatics system also enables the users to edit the preexisting information in the nanofood informatics system.
In one implementation, the nanofood informatics system comprises a nanofood
informatics system repository, hereinafter referred to as a repository that stores nanofood information in form of concepts relevant to the nanofood domain, wherein each concept is configured to be associated with one or more concept instances. The term 'concept' may be understood as a category related to the field of nanofood, such as nanofood products and nanomaterials. The term 'concept instance' may be understood as a relevant piece of information related to the field of nanofood that may fall under certain concepts/categories in nanofood domain and may be considered as an instance of one of the concepts present in the repository. For example, nanotea is a concept instance that falls under the nanofood product concept/category, and may be considered as an instance of the nanofood product. Further, relationships between the concepts are defined in the nanofood informatics system. This representation of the information in form of concepts and relationships between them facilitates structured representation of the nanofood information. In said implementation, the concepts may further include sub-concepts, i.e., specific categories, which are also associated

with the concepts and the interrelationship among the various concepts and sub-concept are defined. The structured representation of the concepts may be implemented using a machine readable format, such as Resource Description Framework/Web Ontology Language (RDF/OWL) schema.
In an implementation, a knowledge specialist defines relevant concepts related
to nanofood domain in a repository. Such relevant concepts are obtained by parsing available unstructured data, such as documents, reports, web pages, and discussion on web forums, related to nanofood. In one example, parsing can be done by using a suitable natural language parser, and extracting relevant information therefrom. The knowledge specialist analyses the extracted relevant information and identifies relevant concepts based on the analysis. As already mentioned, the knowledge specialist defines such relevant concept in the repository. Further, the knowledge specialist defines relationships between such concepts. The concepts thus defined by the knowledge specialist are used as a reference by various users to structure the existing unstructured data related to the field of nanofood. The concept instances from the existing unstructured data is extracted and mapped to the respective concepts in the repository.
In ah implementation, the nanofood informatics system extracts the concept
instances from the existing unstructured data, such as documents, reports, web pages, and forums and represents said concept instances in a structured and machine readable format within the repository. For example, the nanofood informatics system may map the concept instances to matching predefined concepts in' the repository. If no matching predefined concept is present in the repository for mapping the concept instance therein, then the nanofood informatics" system allows a user to add/create user-identified concepts in the repository, and map the concept instances to the same. The term user-identified 6oncept may include new concepts identified by the user. The nanofood informatics system further allows the user to define one or more user-identified relationships between the concepts in the repository, so that once a user-identified concept is added in the repository, its relationships with the predefined concepts in the repository are also specified. User-identified relationships may be interchangeably referred to as relationships identified/defined by the user. In addition, the nanofood informatics system enables the user to edit the concepts and relationships

present in the repository. The term predefined concepts may refer to all the existing concepts in the repository comprising the concepts defined by the knowledge specialist, the user-identified concepts, and the edited concepts in the repository.
In one implementation, the knowledge specialist monitors the nanofood
informatics system to check the validity of the user-identified and/or edited concepts/relationships. In said implementation, the knowledge specialist also checks whether the concept instances maps to the corresponding matching predefined concept, so as to maintain data accuracy.
The concepts in the repository may have one or more predefined rules
associated therewith, referred to as concept rules, hereinafter. Such concept rules and concepts may have many-to-many relationships with one another, i.e., one or more concepts rules may be associated with one or more concepts. These concept rules execute during the retrieval and/or updating of said concepts. Such concept rules when executed generate recommendations for the users. In an implementation, the concept rules may be configured to generate different recommendations for different types of users, for example, a same concept rule may generate different recommendations for researchers, manufactures and consumers. In said implementation, the nanofood informatics system may be configured with a user recognition mechanism, such as speech recognition, digital signature, biometrics based recognition means, and/or recognition based on a login account and password for recognizing different types of users, such as researchers, manufactures and consumers, and generating recommendations based on the type of user.
In an implementation, if the user attempts to add a user-identified concept in
the repository, the nanofood informatics system identifies the addition of the concept and executes the corresponding concept rule to generate recommendations to add user-identified relationships that associates the user-identified concept with the predefined concepts. Further, if the user attempts to edit a concept in the repository, the nanofood informatics system analyses the edition of the concept and executes the corresponding concept rule to generate recommendations for the user to suggest the user to edit related concepts as well. Furthermore, if a user queries the nanofood informatics system for retrieving information related to a nanofood product, the system interprets the user's query related to the nanofood

product and retrieves the concepts from the repository based on the user's query. The
nanofood informatics system also executes one or more concept rules associated with the
retrieved concepts to generate recommendations. For example, the side effects associated with
that nanofood product may be provided to the user in form of recommendations.
The concept rules, therefore, provide assistance to the user, while
adding/editing a concept, and also alert the user in case of any pertinent information that the user should be aware of. Such concept rules are defined by the knowledge specialist and may be implemented using a suitable rule language, such as Semantic Web Rule Language (SWRL). In an implementation, various users may also add concept rules, wherein said rules are validated by the knowledge specialist for incorporating the same into the nanofood informatics system.
The nanofood informatics system as described herein enables structuring the
available unstructured nanofood information, and storing the same in a machine readable
format, such that the information can be processed by the nanofood informatics system. The
stored information may be disseminated to the users. In an implementation, such stored
information may be retrieved by various users by querying the nanofood informatics system.
The disseminated/retrieved information is in human readable format, such as textual format.
Further, the nanofood informatics system enables updating the information stored therein,
such that the information can be evolved with the advancements in the field of nanofood.
The manner, in which structuring of the nanofood information is performed,
shall be explained in detail with respect to Fig. 1 through Fig. 3. While aspects of systems and methods can be implemented in any number of different computing systems, environments, and/or configurations, the embodiments are described in the context of the following exemplary system architecture(s). It will be understood that the word "connected" is used throughout the description for clarity and can include either a direct connection or an indirect connection.
EXEMPLARY SYSTEMS
Fig. 1 illustrates an exemplary network environment 100 implementing a
nanofood informatics system 102, in accordance with an embodiment of the present subject

matter. In said embodiment, the nanofood informatics system 102 is connected to a plurality of user devices 104-1, 104-2...104-N, collectively referred to as the user devices 104 and individually referred to as a user device 104. The nanofood informatics system 102 and the user devices 104 may be implemented as any of a variety of conventional computing devices, including, for example, servers, a desktop PC, a notebook or portable computer, a workstation, a mainframe computer, a mobile computing device, an entertainment device, and an internet appliance.
The nanofood informatics system 102 is connected to the user devices 104
over a network 106 through one or more communication links. The communication links between the nanofood informatics system 102 and the user devices 104 are enabled through a desired form of communication, for example, via dial-up modem connections, cable links, digital subscriber lines (DSL), wireless or satellite links, or any other suitable form of communication. In one implementation, the network environment 100 can be an enterprise network, including thousands of office personal computers, laptops, various servers, such as blade servers, and other computing devices connected over the network 106. In another implementation, the network environment 100 can be a home network with a limited number of personal computers and laptops connected over the network 106. The network 106 may be a wireless network, a wired network, or a combination thereof. The network 106 can also be an individual network or a collection of many such individual networks, interconnected with each other and functioning as a single large network, e.g., the Internet or an intranet. The network 106 can be implemented as one of the different types of networks, such as intranet, local area network (LAN), wide area network (WAN), the internet, and such. The network 106 may either be a dedicated network or a shared network, which represents an association of the different types of networks that use a variety of protocols, for example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet Protocol (TCP/IP), Wireless Application Protocol (WAP), etc., to communicate with each other. Further, the network 106 may include network devices, such as network switches, hubs, routers, HBAs, for providing a link between the nanofood informatics system 102 and the user devices 104. The network devices within the network 106 may interact with the nanofood informatics system 102 and the user devices 104 through the communication links. The users, such as

researchers, manufactures, and consumers may interact through the user devices 104 with the nanofood informatics system 102 for structuring, updating, and/or retrieving information relating to nanofood.
The nanofood informatics system 102 according to an implementation of the
present subject matter is designed for various levels of users, such as researchers, manufacturers, and consumers for disseminating the information related to the field of nanofood. Unlike the conventional form of data related to nanofood that exists in the unstructured format and is scattered on the web, the nanofood informatics system 102 of the present subject matter explores this unstructured data, extracts relevant information out of it, and represents the same in a structured and machine readable format, such that this structured format of the data is disseminated to the users in a human readable format. In an implementation, the users may query the nanofood informatics system 102 for retrieving such structured data.
The users, such as researchers and manufacturers, may easily access research,
and manufacturing related information from the nanofood informatics system 102 respectively. In addition, the users may add research and manufacturing related information into the nanofood informatics system 102, thereby contributing to the evolution of the nanofood informatics system 102. Further, other users, such as consumers, may easily access information related to various nanofood products available in the market, the manufacturing of such nanofood products, the benefits and side effects associated with the nanofood products, and other pertinent information. The nanofood informatics system 102 of the present subject matter is thus useful in disseminating information in the field of nanofood and serves as a repository with all the relevant information about the field of nanofood technology available in a structured manner.
In one implementation, the nanofood informatics system 102 stores the
information in the form of concepts relating to nanofood domain, and the interrelationships between these concepts. The concepts may further include sub-concepts. The representation of the information as concepts and interrelationships between them facilitates storage of the information in a structured form within the nanofood informatics system 102. As discussed, such a structuring facilitates effective dissemination of information to the users. This

structured arrangement of the concepts may be represented using a suitable machine readable format, such as RDF/OWL schema. The machine readable format referred throughout the specification may be understood as a format that may be interpreted and processed by machines.
In an implementation, the nanofood informatics system 102 comprises a
structuring module 108, and an updation module 110 for structuring and updating information, respectively, in the repository (not shown).
During structuring of the information, the knowledge specialist identifies
relevant concepts by parsing available nanofood related unstructured data, such as documents,
reports, web pages, and discussions on web forums. For the purpose of parsing and extracting
relevant information from the unstructured, the knowledge specialist can use a suitable natural
language parser. The knowledge specialist analyses the extracted relevant information and
defines various relevant concepts in the repository based on the analysis of the extracted
information. The predefined concepts may be, for example, the most generic concepts in the
nanofood domain. The knowledge specialist further defines interrelationships between such
concepts. These concepts in the repository serve as a foundation for capturing and structuring
nanofood information that may be incorporated into the repository. The nanofood information
is captured by extracting concept instances from existing unstructured data.
The concepts instances, for example, may be extracted by exploring nanofood
information resources available on the web. Such information resources may include web
pages, forums etc. relating to the field of nanofood, which carries information/data in an
unstructured format. In an example, the information resources are crawled and parsed to
extract the concept instances. As described previously, the term concept instance may be
understood as a relevant piece of information present in an information resource carrying
unstructured data, which may be an instance of a predefined concept in the repository.
The concept instances thus extracted from the unstructured data are
represented in a structured and machine readable format within the repository by the structuring module 108. In operation, the structuring module 108 associates the concept instances with appropriate predefined concepts in the repository. In order to associate the concept instances with appropriate predefined concepts, the structuring module 108

determines similarity between the extracted concept instances and the predefined concepts in
. the repository. The structuring module 108 as described herein uses various similarity
mapping techniques, such as semantic similarity, lexical similarity and direct string matching
to determine the similarity between the extracted concepts instances and the predefined
concepts in the repository. Based on this determination, the structuring module 108 map the
extracted concept instances to the matching predefined concepts in the repository. As evident,
the matching predefined concepts are predefined concepts in the repository to which the
extracted concept instance, as determined by the similarity mapping techniques, map.
In one implementation, if no appropriate matching concept is found, the
updation module 110 may add/create a user-identified concept in the nanofood informatics system 102 and may map the concept instance to the user-identified concept. Further, user-identified relationships may be added in the nanofood informatics system 102 to define relationship of the user-identified concept with the predefined concepts in the nanofood informatics system 102. In said implementation, the updation module 110 allows the user to edit the predefined/existing concepts and/or relationships in the nanofood informatics system 102.
Since the structuring module 108 maps the concept instances to the matching
concepts from the predefined concepts, the unstructured data is structured accordingly. Such structured data is represented in the machine readable format, such as RDF/OWL schema, within the nanofood informatics system 102. This structured data within the nanofood informatics system 102 is disseminated to the user. In an implementation, the user may retrieve such structured data by querying the nanofood informatics system 102, such as entering a search criterion that may include search keywords and retrieving information matching with the search criterion. The disseminated/retrieved information as described herein is in the human readable format.
The updation module 110 enables adding user-identified concepts and/or
relationships, and editing user-identified concepts and/or relationships. Accordingly, evolution of the nanofood informatics system 102 with the advancement in the nanofood technology, as well as refining of the information present within the nanofood informatics system 102 is facilitated.

In an implementation, during retrieval of the information from the nanofood
informatics system 102, the nanofood informatics system 102 receives the search query, such
as search keywords or strings. Based on the search query, the nanofood informatics system
102 searches within the repository of the nanofood informatics system 102 to identify one or
more matching concepts, i.e., the concepts that match with the search query. The matching
concepts retrieved by the nanofood informatics system 102 include similar concepts and
complementary concepts. The similar concepts may be understood as the concepts that match
with the user input, and the complementary concepts may be understood as the concepts that
are related to the similar concepts through any relationship. The complementary concepts are
retrieved to provide more relevant information to the users. For example, if a user, such as
manufacturer is searching for certain process used for manufacturing a nanofood product, the
nanofood informatics system searches for the process indicated by the user and also
proactively present other relevant information, such as other similar processes, equivalent
ingredients, scientific issues pertinent to certain material preparations, social issues associated
with the process being searched. Such matching concepts, i.e., similar concepts and
complementary concepts may be presented to the user as search results on the graphical user
interface of the user device 104. In an implementation, if there are any concept rules
associated with the matching concepts, the nanofood informatics system 102 executes such
concept rules to display recommendations to the user along with the search results.
Fig. 2 illustrates the nanofood informatics system 102, according to an
embodiment of the present subject matter. The nanofood informatics system 102 includes one or more processor(s) 202, interface(s) 206, and a memory 204. The processor(s) 202 can be a single or multiple processing units. The processor(s) 202 can be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, or any devices that manipulate signals based on operational instructions. Among other capabilities, the processor(s) 202 are configured to fetch and execute computer-readable instructions and data stored in the memory 204.
The interfaces 206 may include a variety of software and hardware interfaces,
for example, interface for peripheral device(s) such as a keyboard, a mouse, an external

memory, a printer, etc. Further, the interfaces 206 may enable the nanofood informatics system 102 to communicate with other computing devices, such as web servers and external databases. The interfaces 206 may facilitate multiple communications within a wide variety of protocols and networks, such as the network, including wired networks, e.g., LAN, cable, etc., and wireless networks, e.g., WLAN, cellular, satellite, etc. For the purpose, the interfaces 206 may include one or more ports for connecting to a number of computing devices, such as the user device(s) 104.
The memory 204 can be implemented using any computer-readable medium
known in the art including, for example, volatile memory (e.g., RAM) and/or non-volatile memory (e.g., flash, etc.). The memory 204 includes module(s) 208, and data 210. The module(s) 208 includes routines, programs, objects, components, data structure, etc., that perform particular task or implement particular abstract data types. In one implementation, the module(s) 208 includes an extraction module 212, a search module 214, and other module(s) 216, in addition to the structuring module 108, and the updation module 110. Other module(s) 216 includes programs that supplement applications implemented by the nanofood informatics system 102.
In one embodiment, the data 210 includes the nanofood informatics system
repository 218 hereinafter referred to as repository 218 and other data 220. However, it will
be apparent, that in other embodiments, the repository 218 may be an external repository
associated with the nanofood informatics system 102. The other data 220 includes data that is
generated as a result of the execution of one or more modules in the other modules 216.
The nanofood informatics system 102 in accordance with an implementation of
the present subject matter enables extracting relevant information from the existing unstructured data, and storing such relevant information in a structured and machine readable format, such as RDF/OWL schema within the nanofood informatics system 102, such that the structured information may be disseminated to the users. The structuring of the unstructured information is initiated by extracting the relevant information from the information resources having the unstructured information. In operation, the extraction module 212 receives the unstructured data from the information resources. In one implementation, the extraction module 212 is configured to receive one or more URLs (Uniform Resource Locator) of the

web pages related to the field of nanofood. In another implementation, the extraction module
212 may also receive one or more user specified parameters, such as terms preceding with
'nano' and sentences containing keywords, such as 'nano'. The extraction module 212 visits
the information resources, for example, those indicated by the URLs, and parses the resources
to identify relevant information present therein. The parsing techniques may include sentence
detection, and other suitable techniques. Such relevant information may be, for example, the
most frequently occurring terms in the information resource, phrases containing the most
frequently occurring terms, and the terms or phrases relevant to the user specified parameters.
As explained earlier, the relevant information thus extracted by the extraction module 212
may be instances of the concepts present in the repository, referred to as concept instances. In
an example, the extraction module 212 also identifies all the hyperlinks and metadata present
in the web pages. In said example, the hyperlinks are added to the list of URLs to visit and the
URLs from the list are recursively visited and parsed to identify more concept instances.
The structuring module 108 receives these concept instances and uses
similarity mapping techniques to determine similarity between the extracted concept instances
and the predefined concepts in the repository 218. The similarity mapping techniques, for
example, may include semantic similarity, lexical similarity and direct string matching, to
determine the similarity between the extracted concepts instances and the predefined concepts
in the repository 218. Based on this determination, the structuring module 108 map the
extracted concept instances to the matching predefined concepts in the repository 218.
For example, if a concept instance called "oil nanocochleate" is extracted by
the extraction module 212, structuring module 108 uses similarity mapping techniques to determine similarity between the extracted concept instance, i.e., "oil nanocochleate" and the predefined concepts in the repository 218. Assuming that the structuring module 108 identifies the predefined concept called "nanomaterial" in the repository 218 as the matching concept based on the similarity mapping techniques, the structuring module 108 maps the concept instance "oil nanocochleate" to the concept "nanomaterial".
In one implementation, the concepts instances extracted by the extraction
module 212 and the matching concepts identified by the structuring module 108 are displayed to the user on a graphical user interface of the user devices 104, whereby mapping of the

concept instances with the matching concepts is validated by the user. If mapping of the concept instances with the matching concepts is validated by the user, the structuring module 108 maps the concepts instances to the matching concepts in the repository 218. If mapping of the concept instances with the retrieved concept is invalidated by the user, the updation module 110 allows the user to add user-identified concepts in the repository 218 for mapping the concept instances therewith. If such user-identified concept is added, the structuring module 108 maps the concept instances to the user-identified concepts. The mapping of concepts instances with the matching concepts among the predefined concepts described through the specification, means storing the concept instances within the matching concepts in the repository 218. In an implementation, mapping of the concept instances with the matching concepts is further validated by a knowledge specialist, for maintaining data accuracy in the nanofood informatics system 102.
The updation module 110 described herein also allows the user to add user-
identified relationships within the repository 218, and edit any concept or relationship within the repository 218. While updating the repository 218 by adding the user-identified concepts or editing concepts, the concept rules associated with the user-identified concepts and the edited concepts, prompt the user to edit its related concepts. Such concept rules provide semantic assistance to the user for keeping the nanofood informatics system 102 updated. For example, if the user adds a user-identified concept in the repository 218, the nanofood informatics system 102 interprets the addition of the concept and executes the corresponding concept rule to generate recommendations to add user-identified relationships that associates the user-identified concept with the predefined concepts is provided to the user. Further, if the user attempts to edit a concept in the repository 218, the nanofood informatics system 102 interprets the editing of the concept and executes the corresponding concept rule to generate recommendations to edit its related concepts are provided to the user. The concept rules may be implemented using a suitable rule language, such as Semantic Web Rule Language (SWRL), and may be stored within the other data 220.
In an implementation, the concept rules may be defined by the knowledge
specialist. However, users may also add one or more concept rules in the nanofood informatics system 102. For example, the users may identify one or more concept rules during

structuring of the nanofood information. In operation, the extraction module 212 parses the unstructured data, and extracts relevant information therefrom. Such relevant information may also include some constraints, such as 'manufacturers using nanosilver must take prior approval from XYZ regulatory', the extraction module 212 interprets such information as a concept rule and presents this information to the user for validation. Based on the user validation, the structuring module 108 stores such information as a concept rule. Since the extracted information is usually in textual format, the structuring module 108 first converts this textual information into the rule language, such as Semantic Web Rule Language (SWRL), and then stores this information as the concept rule, for example, within the other data 220.
In an implementation, the knowledge specialist monitors the nanofood
informatics system 102, and checks the validity of user-identified concepts and relationships, the edited concepts and relationships, and/or one or more concept rules added by the users to maintain data accuracy in the nanofood informatics system 102.
During retrieval of the information from the nanofood informatics system 102,
according to an implementation of the present subject matter, the search module 214 receives the search query, such as search keywords and retrieves matching concepts within the repository 218. As mentioned earlier, the matching concepts include similar as well as complementary concepts.
In one example, nanofood product may be a concept existing in the repository
218, and relationships (defined as concept-relationship-concept) nanofood product-has-product property, and nanofood product-contains-nanomaterial exists in the repository 218. If a search query includes nanofood product, then nanofood product existing in the repository is retrieved as similar concepts, and the product property and nanomaterial are retrieved as complementary concepts because they are related to nanofood product via "has" and "contains" relationship, respectively.
In addition to disseminating the nanofood information to the users, the
nanofood informatics system 102 enables the users to contribute information therein by means of adding the user-identified concepts. Further, the nanofood informatics system 102 also enables users to refine the information contributed by other users by means of editing the

concepts in the nanofood informatics system 102. Hence, the nanofood informatics system
102 acts as a medium for disseminating, retrieving, and refining the information related to
nanofood. In addition, the nanofood informatics system 102 enables users to collectively
formulate various standards related to nanofood domain. Such standards may include creating
a common exchange format for import/export that enables various users to import/export
nanofood information among other informatics system that may be developed in future. Such
common exchange format therefore facilitates interexchange and interoperability of nanofood
information. For example, the common exchange format may be defined in a standard to be a
customized markup language, such as Nanofood Markup Language (NFML).
An example NFML snippet for importing nanofood product
"Banana_Smoothie" with ingredient nanomaterials (NanoGold, IRON III Oxide), associated nanoprocesses, hazards, benefits, special concerns and regulations is as follows. It will be understood that the following snippet is provided only as an example and should not be construed as a limitation. Various other embodiments/ modifications will be apparent to one having ordinary skill in the art.

NanoGold
IRON_III_Oxide
Flavour_Enhancement_Process
Slight chance that the tiny nanoiron particles could bypass normal iron absorption mechanisms and overload the body.
Could help eliminate anaemia deficiency across the globe


Possibility of increase of Iron content in body
EP_RegulationXX/YY
Fig. 3 illustrates an exemplary method 300 for structuring and updating the
information in the repository associated with the nanofood information system, according to an implementation of the present subject matter. The exemplary method 300 may be described in the general context of computer executable instructions. Generally, computer executable instructions can include routines, programs, objects, components, data structures, procedures, modules, functions, etc., that perform particular functions or implement particular abstract data types. The method may also be practiced in a distributed computing environment where functions are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, computer executable instructions may be located in both local and remote computer storage media, including memory storage devices. Some embodiments are also intended to cover both communication network and communication devices configured to perform said steps of the exemplary method.
The order in which method 300 is described is not intended to be construed as
a limitation, and any number of the described method blocks can be combined in any order to implement the method, or an alternative method. Additionally, individual blocks may be deleted from the method without departing from the spirit and scope of the subject matter described herein. Furthermore, the methods can be implemented in any suitable hardware, software, firmware, or combination thereof.
The exemplary method 300 of structuring and updating the information in the
repository associated with a nanofood information system is herein described in context of the

above described nanofood informatics system 102, according to an implementation of the present subject matter. However, such an implementation should not be construed as a limitation and it will be understood the method 300 may be implemented in various similar systems and devices.
The knowledge specialist defines relevant concepts related to nanofood domain
in a repository, such as the repository 218. Further, the knowledge specialist defines interrelationships between them. The concepts may further include sub-concepts. In one example, the knowledge specialist defines the concepts, such as nanofood product, product property, nanomaterial, and material property, and defines relationships between them. The relationships are defined in concept-relationship-concept format, such as, nanofood product-has-product property, nanomaterial-has-material property, and nanofood product-contain s-nanomaterial. In one implementation, concepts within the repository 218 may be represented using a machine readable format, such as RDF/OWL schema. As mentioned earlier, the machine readable format may be understood as the format that may be interpreted and processed by machines.
The concepts defined by the knowledge specialist in the repository is used by
various users, such as researchers, manufacturers, and consumers as a reference for structuring existing unstructured data relating to nanofood domain, and storing the same in the repository, such as the repository 218. The users explore the existing unstructured data, such as documents, reports, web pages, and forums, relating to the nanofood domain. Once the unstructured data is explored, the same may be structured by the nanofood informatics system 102 by referring the predefined concepts in the repository. The method of structuring is initiated at block 302, where one or more information resource parameters are received by the nanofood informatics system, such as nanofood informatics system 102. These information resources parameters are the URLs of the most representative web pages related to nanofood domain. Such web pages usually contains information in form of unstructured data, this unstructured data is used for obtaining the concept instances present thereon at block 304, by crawling and parsing the same. In an exemplary implementation, the extraction module 212 extracts the concept instances by crawling and parsing the unstructured data.

At block 306, a matching concept among the predefined concepts in the
repository is determined by similarity mapping techniques. The matching concept may be
understood as a concept among the predefined concepts within the repository to which the
extracted concept instances can be mapped. In one implementation, the structuring module
108 determines the matching concept among the predefined concepts in the repository 218
based on the similarity mapping techniques to determine the matching concept.
Once the matching concepts from the repository are determined, a check is
conducted at block 308 to determine whether the concept instance maps to any of the matching concepts determined by the similarity mapping techniques. If the concept instances is found to map with the matching concepts the concept instances are associated with the matching concept at block 310. In said exemplary implementation, the structuring module 108 associate the concept instance with the matching concept. The term associating the concept instance with the matching concept may be understood as linking the concept instance to the matching concept with 'is-a-kind-of relationship.
On the other hand, if the concept instances do not map with the matching
concepts determined by the similarity mapping techniques, the concepts in the repository are updated at block 312. In said exemplary implementation, the concepts in the repository 218 are updated by the updation module 110. In one example, the updating step comprises adding a user-identified concept in the repository and associating the concept instance with the user-identified concept. If a user-identified concept is added, the user-identified relationships are also added to relate the user-identified concept with the predefined concepts in the repository. In another example, the update comprises editing a concept in the repository. If a concept is edited in the repository, the concept rules associated with the edited concept prompt the user to also edit is complementary concepts. As described previously, the concept rules are the one or more rules associated with one or more predefined concepts in the repository that executes during the retrieval and/or updating of said predefined concepts. Such concept rules when executed generate recommendations for the users.
In one implementation, the system, such as the nanofood informatics system
102 is monitored by a knowledge specialist that checks the validity and accuracy of the newly

added user-identified concepts, newly added user-identified relationships, edited concepts, and edited relationships.
Such method of structuring existing nanofood related unstructured data, and
storing the same in the nanofood informatics system, facilitates easy accessibility to the
nanofood information. As the existing nanofood unstructured data, which is scattered across
the web require more time and efforts by the users to explore the same. Furthermore, reading
from the existing unstructured and extracting relevant information therefrom also requires
more time and efforts by the users. The nanofood informatics system described herein allow
the users to extract relevant information from the unstructured data, and store the same in a
structured and machine readable format within the repository associated with the nanofood
informatics system, such that the structured data may be processed by the nanofood
informatics system. Such structured information may be disseminated to the users, such as
researchers, manufacturers and consumers. In an implementation, the users may query the
nanofood informatics system for retrieving such structured information therefrom. The
nanofood informatics system presents such structured data in a human readable format to the
users. The method of updating the repository as described herein enables various users to add
new information in the repository, and/or edit existing information in the repository, such that
the repository is updated with the advancements in the field of the nanofood, and is free from
errors. In an example, the users such as researcher and manufactures may add new research,
and manufacturing related information in the repository associated with the nanofood
informatics system respectively. In another example, users such as consumers may add side
effects that they experienced upon consuming various nanofood products.
Thus, exploring such existing unstructured data, extracting relevant
information therefrom, and representing the same in the structured format provides for an effective technique for representation, dissemination and consumption of information related to nanofood. If all the existing unstructured data related to nanofood domain is transformed into the structured data and stored in the nanofood informatics system at this early stage, the dissemination of the nanofood information to the users seeking such information will become easier even with the consistently growing corpus of information.

Although embodiments for nanofood informatics system have been described
in language specific to structural features and/or methods, it is to be understood that the invention is not necessarily limited to the specific features or methods described. Rather, the specific features and methods are disclosed as exemplary implementations for the nanofood informatics systems and methods.

I/We claim:
1. A computerized method comprising:
receiving at least one information resource parameter corresponding to information resources having unstructured data in a nanofood informatics system;
extracting at least one concept instance from information resources; and mapping the at least one concept instance to at least one predefined concept in a nanofood informatics repository for structuring nanofood information.
2. The method as claimed in claim 1, wherein the mapping further comprises determining at least one matching concept based on at least one similarity mapping technique.
3. The method as claimed in claim 1 further comprises updating the predefined concepts in the nanofood informatics repository based at least in part on the mapping.
4. The method as claimed in claim 3, wherein the updating comprises:
creating a user-identified concept; and
generating at least one recommendation for defining a relationship between the user-identified concept and the at least one predefined concept from among the predefined concepts in the nanofood informatics repository.
5. The method as claimed in claim 1 further comprises:
receiving a search query; and
obtaining information from the nanofood informatics repository based on the search query.
6. The method as claimed in claim 5 further comprises updating the concepts in the nanofood informatics repository, in response to the obtaining.
7. The method as claimed in claim 6, wherein the updating the concepts in the nanofood informatics repository comprises:
editing at least one predefined concept; and
generating at least one recommendation for editing at least one complementary concept, based on execution of at least one concept rule associated with the edited concept.
8. A nanofood informatics system (102) comprising:

a processor (202); and
a memory (204) coupled to the processor (202), the memory (204) comprising:
an extraction module (212) configured to extract at least one concept instance from information resources comprising unstructured data; and
a structuring module (108) configured to map the at least one concept instance extracted by the extraction module (212) to at least one predefined concepts among a plurality of predefined concepts in a nanofood informatics repository (218).
9. The nanofood informatics system (102) as claimed in claim 8 further comprises a search module (214) configured to search at least one predefined concept from the nanofood informatics repository (218) based on a search query.
10. The nanofood informatics system (102) as claimed in claim 8 further comprises an updation module (110) configured to:
update the nanofood informatics repository (218) with a user-identified concept; and
modify relationships between the user-identified concept and the predefined concepts.
11. The nanofood informatics system (102) as claimed in claim 10, wherein the updation
module (110) is further configured to update a predefined complementary concept.