Method and system for sourcing items

Abstract

A computer-implemented method and system for sourcing items for a watercraft are disclosed. One or more item requests are received and processed to extract item data relating to requested items. Route

Description

Field of the invention The present invention relates to a method and system for sourcing items for a watercraft. Background to the invention It is known that watercrafts (such as vessels, ships and boats) need to order items whilst on route (e.g. in transit or mid-voyage) to be collected at an intended port of call or destination. Personnel on the watercrafts must provide a list of required items to suppliers at the intended port of call or destination. The list of required items can be provided to the suppliers in various different formats depending on the personnel or the watercraft requesting the items. The watercraft can only pick up the required items when it reaches the intended port of call or destination, which can take time and mean that the watercraft goes without necessary or desired items for quite some time, or cannot depart on its voyage. Currently, watercraft have limited visibility into potential suppliers as they rely on pre-registered suppliers or informal methods. It is in this context that the present inventions have been devised. Summary of the invention In accordance with an aspect of the present invention, there is provided a method of sourcing items for a watercraft. The method may comprise receiving one or more item requests for one or more items. The method may comprise processing the one or more item requests to extract item data. The item data may relate to the one or more items. The method may comprise determining route information of the watercraft. The route information may comprise an intended route of the watercraft. The method may comprise receiving supplier data of one or more potential suppliers. The supplier data may comprise a location of a port supplied by the respective potential supplier. The method may comprise processing the item data, the route information and the supplier data of the one or more potential suppliers to determine one or more candidate ports and / or suppliers of the one or more items. The method may comprise providing an output indicative of the one or more candidate ports and / or suppliers to a user. The method may comprise processing the item data, the route information and the supplier data of the one or more potential suppliers to determine one or more candidate ports of the one or more items. The method may comprise providing an output indicative of the one or more candidate ports to a user. The method may comprise processing the item data, the route information and the supplier data of the one or more potential suppliers to determine one or more candidate suppliers of the one or more items. The method may comprise providing an output indicative of the one or more candidate suppliers to a user. The method may comprise processing the item data, the route information and the supplier data of the one or more potential suppliers to determine one or more candidate ports and suppliers of the one or more items. The method may comprise providing an output indicative of the one or more candidate ports and suppliers to a user. In accordance with another aspect of the present invention, there is provided a system for sourcing items for a watercraft. The system may comprise one or more processors. The one or more processors may be configured to receive one or more item requests for one or more items. The one or more processors may be configured to process the one or more item requests to extract item data. The item data may relate to the one or more items. The one or more processors may be configured to determine route information of the watercraft. The route information may comprise an intended route of the watercraft. The one or more processors may be configured to receive supplier data of one or more potential suppliers. The supplier data may comprise a location of a port supplied by the respective potential supplier. The one or more processors may be configured to process the item data, the route information and the supplier data of the one or more potential suppliers to determine one or more candidate ports and / or suppliers of the one or more items. The one or more processors may be configured to provide an output indicative of the one or more candidate ports and / or suppliers to a user. The one or more processors may be configured to process the item data, the route information and the supplier data of the one or more potential suppliers to determine one or more candidate ports of the one or more items. The one or more processors may be configured to provide an output indicative of the one or more candidate ports to a user. The one or more processors may be configured to process the item data, the route information and the supplier data of the one or more potential suppliers to determine one or more candidate suppliers of the one or more items. The one or more processors may be configured to provide an output indicative of the one or more candidate suppliers to a user. The one or more processors may be configured to process the item data, the route information and the supplier data of the one or more potential suppliers to determine one or more candidate ports and suppliers of the one or more items. The one or more processors may be configured to provide an output indicative of the one or more candidate ports and suppliers to a user. In accordance with another aspect of the present invention, there is provided a computer readable storage medium comprising instructions which, when the program is executed by a computer, cause the computer to carry out the method described herein. Advantageously, by extracting item data from the item requests, the list of required items which is written or put together by the watercraft personnel or a land-based office of a company of the watercraft can be converted into a list of items which can be understood by the suppliers. As there is no standardised format for item requests, it is often the case that suppliers can find it difficult to determine the details of an item request, for example the name of the items in the request, the quantity of each item and any further details of each item, e.g. a colour, brand name or size. The present invention extracts item data from the item requests and uses this to determine the candidate suppliers of the required items. Therefore, suppliers do not need to spend money or time looking through each item in the item requests to determine which item is being requested and whether they have the required items in stock. As a further advantage, the present invention takes into account route information of the watercraft and the location of ports supplied by the respective potential suppliers to determine candidate ports and / or suppliers. The present invention also takes into account the item data when determining who are the candidate suppliers and / or which are the candidate ports. This means that candidate suppliers can be suppliers that have the required items in stock and lie along or near to the route of the watercraft. This means that candidate ports can be ports supplied by suppliers that have the required items in stock and lie along or near to the route of the watercraft. The personnel on the watercraft or staff in a land-based office of a company of the watercraft can then be provided with an output of these suppliers. This is a significant advantage over how sourcing items for watercrafts currently works where personnel only consider using known suppliers at their intended destination or port of call. Typically, the watercraft is a (e.g. cargo or passenger) vessel, ship, boat or submarine. References to the watercraft herein may refer to the personnel of the watercraft. For example, it will be appreciated that the entity making the item request is actually the personnel of the watercraft, though it may be referred to as the item request of the watercraft. Typically, an item request comprises a list of items that are requested (i.e. required) by the watercraft. Typically, an item request is an RFQ (Request for Quotation) The one or more items may be essential items and / or desired items. The one or more items may be components (for example replacement parts) for the watercraft (e.g. for the engine, body or interiors of the watercraft). The one or more items may be items for personnel on the watercraft. The one or more items may be food or drink items. It will be appreciated that other types of items may be requested by the watercraft. Typically, the one or more item requests contain information about the one or more items. This may include: a name of the item, a quantity of the item, a unit of the item, or a property of the item (e.g. colour or brand). The one or item requests may be received from a land-based office of a company of the watercraft (or directly from the watercraft). The one or more item requests may be received by downloading the one or more item requests from an online portal (e.g. a webpage) or accessing a server or memory device storing the one or more item requests. Other ways of receiving the one or more item requests will be envisaged. Typically, the item data comprises information relating to items requested by the watercraft. This may include the name of the items. Typically, the item data comprises structured data. In this way, the item data is established, clearly defined and widely recognised labelled and categorised data. For example, the item data may include an International Ship Suppliers Association (ISSA) code or an International Marine Purchasing Association (IM PA) code. This type of data allows different parties to ensure that they are referring to the same item as it is a standardised way of referring to a given item. The item data may also include other data (which may not be structured data) but which is specific to the item request. For example, a quantity of the item, a unit of the item, or a property of the item (e.g. colour or brand). Typically, the one or more item requests are processed to extract item data by analysing the content of the one or more item requests. It may be that the item data is extracted from the one or more item requests using a machine learning model (e.g. a large language model (LLM)). Throughout the present application, it will be appreciated that where a machine learning model can be used, said model can be trained using existing item requests which are annotated to label different types of item data within the item request. It may be that the one or more item requests comprise unstructured data. It may be that processing the one or more item requests to extract the item data comprises associating the unstructured data of the one or more item requests with the structured data of the item data. It may be that the one or more processors are configured to process the one or more item requests to extract the item data by associating the unstructured data of the one or more item requests with the structured data of the item data. Advantageously, structured data is standardised terminology from a classification or database. This means that there is standardised terminology for each item required by the watercraft. The item data is standardised and can be used by everyone to identify the exact same type of item. Typically, suppliers use structured data in their inventory list and catalogues. Typically, the personnel onboard the watercraft and staff in the land-based office of a company of the watercraft have their own way of referring to items which is usually unstructured data. Since the item requests do not always use the structured data, the suppliers must spend time and money matching the items from the item requests to the structured item data. The present invention removes this time and complexity from the supplier by associating unstructured data with the structured data of the item data. Typically, the item request contains lots of information about the one or more items being requested. Typically, the unstructured data of the item requests refers to data that is not standardised or universally recognised. For example, the one or more item requests may refer to an item by a colloquial name, nickname or shortened name. This may not be the official name of an item as recognised in standard classifications or catalogues. The method may comprise retrieving structured data of the item data. The one or more processors may be configured to retrieve structured data of the item data. This may be achieved by accessing a database of structured data of the item data, for example a catalogue such as the ISSA or I MPA catalogues. The method step of associating the unstructured data of the one or more item requests with the structured data of the item data may comprise using a machine learning model to tag the unstructured data of the one or more item requests to the structured data of the item data. It may be that the one or more item requests comprise structured data. It may be that processing the one or more item requests to extract the item data comprises associating the structured data of the one or more item requests with the structured data of the item data. It may be that the one or more processors are configured to process the one or more item requests to extract the item data by associating the structured data of the one or more item requests with the structured data of the item data. Advantageously, sometimes the item requests do include structured data. In this case, the structured data from the item request can be matched by to structured data of the item data. This provides certainty over which items are requested by the watercraft and whether the supplier can supply the requested items. In some cases, when the one or more item requests comprise structured data, the structured data of the one or more item requests may be matched to structured data of the item data. It may be that the one or more item requests comprise a document. It may be that processing the one or more item requests to extract the item data comprises performing document analysis of the one or more items requests. It may be that the one or more processors are configured to process the one or more item requests to extract the item data by performing document analysis of the one or more items requests. Advantageously, documents are an easy way for watercraft personnel, or staff in a land-based office of a company of the watercraft, to provide an item request. The present invention can analyse the document to extract the item data from the item requests. This allows the exact items requested by the watercraft to be identified so that a supplier for said items can be found. Typically, the document may be a .doc, .docx, .pdf document or a spreadsheet .xlsx document. Typically, the document is written (e.g. typed document). As discussed, the document may have many different formats and layouts but generally include the same types of data, including for example vessel name, upcoming port stops and estimated time of arrival into the port stop, name of the item, quantity, units and a description (or property of the item). The method step of performing document analysis may comprise analysing the content of the document to identify key characteristics of the document including layout, textual content and formatting. It may be that performing document analysis comprises identifying one or more visual cue features of the layout of the document. It may be that the one or more visual cue features of the layout of the document are selected from a group comprising: text length, column layout, row layout, border layout, text formatting, changes in text formatting, spacing (e.g. blank row or columns in spreadsheet data), lines (e.g. cell borders in spreadsheet data), colouring (e.g. of text or cell borders), changes in colouring, and headings (e.g. highlighted text). It may be that the one or more processors are configured to perform document analysis by identifying visual cue features of the layout of the document. Item requests in the form of a document typically have no standardised layout or format. Therefore, when completing document analysis, it can sometimes be difficult to identify which part of the document refers to what type of item data. In turn, this means it can be difficult to identify exactly which items have been requested. Advantageously, by identifying visual cue features in the document, this means that parts of the document which are related different types of item data can be identified based on common visual features of parts of documents which relate to different types of item data. Typically, the one or more visual cue features are indicative of information that can be used to determine where in the document different types of item data are specified. It may be that the one or more visual cue features are indicative of item data. For example, where the one or more visual cue features comprise a row, this may be indicative of item data relating to an item. It may be that the one or more visual cue features are indicative of a type of item data. For example, it may be that underlined text formatting is indicative of a heading which is indicative of column having data relating to a type of item data. It may be that the one or more visual cue features are indicative of separate items, for example where the visual cue feature comprises a column of incrementing numbers. It may be that performing document analysis comprises associating the one or more visual cue features with a type of item data. It may be that the one or more processors are configured to perform document analysis by associating the one or more visual cue features with a type of item data. Advantageously, by associating the visual cue features with a type of item data, the parts of the document which refer to a type of item data can be determined, and the item requests can be processed to extract item data with more accuracy. It may be that the method step of associating the one or more visual cue features with a type of item data is performed using a machine learning model which has been trained to allocate a type of item data to the one or more visual cue features (either individually or as a group). It may be that the one or more visual cues are used to identify where in the item request (i.e. document) a type of item data is defined. It may be that performing document analysis comprises identifying a type of item data indicated by the one or more visual cues. Typically, a group of visual cues may be used to identify where in the item request a type of item data is defined. Advantageously, by using a group of visual cues in this way, the type of item data defined in each part of the item request can be more reliably and easily determined. It may be that performing document analysis comprises performing text recognition on the document to identify structured and / or unstructured data. It may be that processing the one or more item requests to extract the item data comprises associating the structured and / or unstructured data of the one or more item requests with a type of item data. It may be that the one or more processors are configured to perform document analysis by performing text recognition on the document to identify structured and / or unstructured data. It may be that the one or more processors are configured to process the one or more item requests to extract the item data by associating the structured and / or unstructured data of the one or more item requests with a type of item data. Advantageously, text recognition is a reliable way to obtain data from the item request which can then be processed to the extract the item data. If the text recognition identifies structured data, this can be matched to structured data of the item data. If the text recognition identifies unstructured data, this can be associated with structured data of the item data. Typically, the text recognition may be performed by extracting text from the document. However, it will be appreciated that other forms of text recognition may be used (e.g. optical character recognition). It may be that the method step of associating the structured and / or unstructured data with a type of item data is performed using a machine learning model which has been trained to allocate a type of item data to the structured and / or unstructured data depending on the content of said data. As an example, where the item request includes a column of three groups of two numbers, with a space between each group, this may be indicative of an I MPA code. As an example, where the item request includes a column of 7 digit codes, this may be indicative of an ISSA code. In some examples, the item data is provided as an intermediate output. The method may comprise providing an output of the item data after extraction. The one or more processors may be configured to provide an output of the item data after extraction. A user may then be able to check the item data has been correctly identified for the one or more items that have been requested by the watercraft. This user performing the check may be able to override the association of the data in the one or more items requests with the item data (e.g. to correct the item data). The method may comprise receiving a manual override of the association of the data in the one or more items requests with the item data. The one or more processors may be configured to receive a manual override of the association of the data in the one or more items requests with the item data. This allows users to correct any incorrect matches of the data in the one or more item requests to the item data. The user may be able to provide item data that has not been extracted from the one or more items requests. This allows the user to complete any missing information in the item data. The method may comprise receiving item data from a user. The one or more processors may be configured to receive item data from a user. It may be that the method comprises outputting the document (e.g. of the one or more item requests) with annotations indicating candidate extracted information for review by a review user. The one or more processors may be configured to output the document with annotations indicating candidate extracted information for review by a review user. The review user may not be the entity that created the document and instead may be an intermediary between the watercraft and the supplier. The review user may then delete, amend or add item data. The corrections of the review user may be used for model training to improve data extraction. The route information may comprise one or more of: an origin of the route, a schedule of the watercraft, a port timeline, a destination of the route. The route information may comprise an estimated duration of the voyage. The route information may comprise a previous and / or next port of call of the watercraft. It may be that the route information comprises a current location of the watercraft. It may be that the method comprises obtaining live tracking information of the current location of the watercraft. Typically, by having access to the route information of the watercraft, the candidate ports and / or suppliers are more appropriate and tailored to each watercraft making the one or more item requests because the route of the watercraft is considered when determining the one or more candidate ports and / or suppliers. Typically, the location of a port supplied by the respective potential supplier means that supplies are provided from that port (e.g. for collection) by the respective potential supplier. Typically, the supplier data is used to determine a location of each of the potential suppliers. That is, the port supplied by the potential supplier may be a location of the potential supplier for the purposes of processing the supplier data. The supplier data may also include other information such as contact information for the supplier and / or for example an inventory list or catalogue of the supplier. The method step of receiving the supplier data may comprise accessing a live database for each of the potential suppliers. The method step of receiving the supplier data may comprise accessing a predetermined list of the one or more potential suppliers. Typically processing the supplier data comprises processing the location of a port supplied (e.g. delivered to) by the respective potential supplier. It may be that the distance between the location of the port and the supplier that delivers to (i.e. supplies) the port is for example at most 30 nautical miles, such as at most 20 nautical miles, for example at most 10 nautical miles. It may be that the supplier data comprises item availability data of the respective supplier. The item availability data may be a live inventory of each potential supplier. Advantageously, the inclusion of item availability in the supplier data means that the candidate suppliers can be those which have stock of the requested items. Advantageously, the inclusion of item availability in the supplier data means that the candidate ports can be ports supplied by suppliers which have stock of the requested items. Throughout this document, the one or more potential suppliers refers to all suppliers whose information is available. In contrast, the one or more candidate suppliers refers to a list of suppliers which is generated after filtering the one or more potential suppliers to identify which of those suppliers are most appropriate for the watercraft depending on the one or more items that have been requested, the location of port that is supplied by the supplier and the intended route of the watercraft. By candidate ports, we refer to a port that is being considered as a place where the vessel might receive items from the supplier. Typically, the candidate ports are selected taking into account at least one viability criteria relating to how viable it would be for the vessel to collect items at the respective port. Typically, the item data is processed to determine what items have been requested by the watercraft. The item data and the supplier data, when the supplier data includes item availability data, may be processed to determine which of the one or more potential suppliers can supply the one or more items that have been requested available for pick up or which port is supplied by suppliers that can supply the one or more items that have been requested available for pick up. Typically, the route information and the supplier data are processed to determine the one or more candidate ports and / or suppliers by taking into account the intended route of the watercraft and the location of the ports supplied by the potential suppliers relative to the intended route. It may be that ports supplied by the potential suppliers that are located along the intended route of the watercraft may be determined to be the one or more candidate suppliers. It may be that ports supplied by the potential suppliers that are located along the intended route of the watercraft may be determined to be the one or more candidate ports. Typically, the item data, the route information and the supplier data, when the supplier data includes item availability data, may be processed to determine which of the one or more potential suppliers has the one or more items that have been requested available for pick up and have a location which lies along the route of the watercraft. Typically, the item data, the route information and the supplier data, when the supplier data includes item availability data, may be processed to determine which of the one or more potential suppliers has the one or more items that have been requested available for pick up and supply a port which lies along the route of the watercraft. It will be appreciated that the intended route of a watercraft between ports of call is through water, and only includes land at an intended port of call or at the origin / destination of the route. It will also be appreciated that the location of the one or more potential suppliers will be on land. Thus, the potential suppliers and the ports supplied by the potential supplier do not typically lie exactly on the intended route of the watercraft. However, it will be understood that a potential supplier and the ports supplied by the potential supplier can be said to lie along the intended route of the watercraft if the watercraft would sail past the port. For example, a ship sailing directly from Southampton, UK to Tangier, Morocco (via the English Channel, past the Bay of Biscay and along the west coast of Portugal) would sail past Lisbon, Portugal. Therefore, the port of Lisbon, Portugal and a supplier in Lisbon, Portugal would be said to lie along the intended route of the watercraft. It may be that processing the item data, the route information and the supplier data of the one or more potential suppliers to determine the one or more candidate ports and / or suppliers of the one or more items comprises identifying ports and / or potential suppliers with a location within a predetermined distance of any point on the intended route. It may be that the one or more processors are configured to process the item data, the route information and the supplier data of the one or more potential suppliers to determine one or more candidate ports and / or suppliers of the one or more items by identifying ports and / or potential suppliers with a location within a predetermined distance of any point on the intended route. Advantageously, by identifying ports and / or potential suppliers with a location within a predetermined distance of the intended route, the suppliers within a given distance of the route and / or the ports within a given distance of the route are provided to the watercraft or staff in the land-based office of a company of the watercraft as candidate ports and / or suppliers. This means that the watercraft can choose to make a detour from its intended route to stop at a candidate port (e.g. to pick up the requested items from one of the candidate suppliers). It may be that processing the item data, the route information and the supplier data of the one or more potential suppliers to determine the one or more candidate ports and / or suppliers of the one or more items comprises identifying ports and / or potential suppliers with a location within a predetermined distance of any point on the intended route between a destination of the route and the current location of the watercraft. It may be that the one or more processors are configured to process the item data, the route information and the supplier data of the one or more potential suppliers to determine one or more candidate ports and / or suppliers of the one or more items by identifying ports and / or potential suppliers with a location within a predetermined distance of any point on the intended route between a destination of the route and the current location of the watercraft. Advantageously, by identifying ports and / or potential suppliers with a location within a predetermined distance of the intended route, the suppliers within a given distance of the route and ahead of the route of the watercraft and / or the ports within a given distance of the route and ahead of the route of the watercraft are provided to the watercraft or staff in a land-based office of a company of the watercraft as candidate ports and / or suppliers. This means that the watercraft or staff in a land-based office of a company of the watercraft is provided with particularly relevant candidate ports and / or suppliers as not only are the candidate ports and / or suppliers close to the intended route, but they are also only provided with candidate ports and / or suppliers which lie ahead of the intended route of the watercraft so the watercraft can choose to make a detour from its intended route to stop at a candidate port (e.g. to pick up the requested items from one of the candidate suppliers). It may be that the predetermined distance (of any point on the intended route) is for example at most 2000 nautical miles (NM), such as at most 1500 NM, for example at most 1000 NM, such as at most 750 NM, for example at most 500 NM, such as at most 250 NM, for example at most 150 NM, such as at most 100 NM, for example at most 80 NM, such as at most 50 NM, for example at most 30 NM, such as at most 20 NM, for example at most 15 NM, such as at most 12NM, for example at most 10NM. 1 NM is approximately 1852 m. It may be that the method comprises determining the one or more candidate ports and / or suppliers of the one or more items in dependence on predetermined criteria. It may be that the predetermined criteria comprise at least one of: (i) the minimum detour from the intended route that the watercraft would be required to travel to obtain the one or more items from the port and / or the one or more potential suppliers, and (ii) the minimum number of ports and / or potential suppliers of all of the one or more items. It may be that the one or more processors are configured to determine the one or more candidate ports and / or suppliers of the one or more items in dependence on predetermined criteria. Advantageously, by determining the candidate ports and / or suppliers by taking into account predetermined criteria, the relevance of the candidate ports and / or suppliers to watercraft can be tailored depending on particular important aspects of the ports and / or suppliers. For example, when the predetermined criteria comprises the minimum detour from the intended route, the output can show which candidate ports and / or suppliers are closest to the intended route and therefore this minimises the fuel costs and time delay associated with picking up the requested items. When the predetermined criteria comprises the minimum number of ports and / or potential suppliers, the output can show the fewest candidate ports and / or suppliers possible to supply all of the items of the item requests, and therefore this minimises the fuel costs and time delay associated with picking up the requested items. It may be that the method comprises calculating fuel consumption of the watercraft and / or time taken by the watercraft to receive the items from the candidate port and / or supplier. It may be that the method comprises taking into account how close to a port a watercraft will have to be to receive the items, e.g. supplies might be delivered miles from the port. Typically, the predetermined criteria are criteria that are used to filter the one or more potential suppliers to determine the one or more candidate ports and / or suppliers. Typically, the predetermined criteria are criteria that are used to prioritise the one or more potential suppliers to determine the one or more candidate ports and / or suppliers. Typically, the predetermined criteria are criteria that are used to determine a relevance of the one or more potential ports and / or suppliers to the watercraft to determine the one or more candidate ports and / or suppliers. It may be that at least one of the predetermined criteria is a minimum amount of a parameter. The parameter may be the detour from the intended route that would be necessary to pick up the one or more items from the port and / or potential supplier. The parameters may be the number of ports and / or potential suppliers required to fulfil all of the one or more items of the one or more item requests. It may be that the predetermined criteria comprise a minimum fuel consumption that the watercraft would be required to use to obtain the one or more items from the ports and / or the one or more potential suppliers. It may be that the predetermined criteria comprise a carbon footprint that the watercraft would have to obtain the one or more items from ports and / or the one or more potential suppliers. It may be that the predetermined criteria comprise the minimum cost of the detour from the intended route that the watercraft would be required to travel to obtain the one or more items from the ports and / or the one or more potential suppliers. Typically, the one or more items comprises a plurality of items. It may be that processing the item data, the route information and the supplier data of the one or more potential suppliers to determine the one or more candidate ports and / or suppliers of the plurality of items comprises taking into account repositioning of a first subset of the plurality of items from a first port and / or potential supplier to a second port and / or potential supplier, the second port and / or potential supplier having a second subset of the plurality of items. The method comprising determining the second port and / or potential supplier as the candidate port and / or supplier. It may be that the one or more processors are configured to processing the item data, the route information and the supplier data of the one or more potential suppliers to determine the one or more candidate ports and / or suppliers of the plurality of items by taking into account repositioning of a first subset of the plurality of items from a first port and / or potential supplier to a second port and / or potential supplier, the second port and / or potential supplier having a second subset of the plurality of items. The one or more processors may be configured to determine the second port and / or potential supplier as the candidate port and / or supplier. Advantageously, by taking into account that items can be repositioned (e.g. transferred) from one port and / or supplier to another, the necessary detour, fuel consumption / cost and carbon footprint of the watercraft can be reduced. This is particularly useful as it is more practical for repositioning of items to a single location to be done on land so that the watercraft only has to make one port stop, rather than the watercraft making multiple port stops. In some cases, the first potential supplier and the second potential supplier may be connected. For example, the first or second potential supplier may be a sub-supplier of the other. By ‘taking into account’ we refer to the determination of whether the first subset of items can physically be relocated to the second port and / or supplier. It may be that the time taken for the repositioning of the first subset of items is also considered. It may be that the output indicative of the one or more candidate ports and / or suppliers is provided on a visual output device (e.g. a display screen or monitor). It may be that the system comprises an output device. For example, a visual output device such as a display screen or monitor. It will be appreciated that other forms of output devices may be envisaged. The output may be in the form of a map with the location and details of the one or more candidate suppliers indicated thereon. The output may be in the form of a map with a marker to show the location of the one or more candidate ports. It may be that the output comprises information associated with the one or more candidate ports and / or suppliers. It may be the information associated with the one or more candidate ports and / or suppliers comprises at least one of: a price of the one or more items from the candidate port and / or supplier, the detour (e.g. in time or distance) from the intended route that the watercraft would be required to travel to obtain the one or more items from each of the candidate ports and / or suppliers, fuel consumption that the watercraft would be required to use to obtain the one or more items from each of the candidate port and / or supplier and / or the carbon footprint that the watercraft would have to obtain the one or more items from each of the candidate ports and / or suppliers. It may be that the output comprises information associated with the watercraft, for example a live position of the watercraft, the origin / destination of the watercraft and / or the intended route of the watercraft. It may be that the method comprises receiving a user input indicative of a selected port and / or supplier from the one or more candidate ports and / or suppliers. It may be that the method comprises transmitting the item data relating to the one or more items to the supplier that supplies the selected port and / or the selected supplier. It may be that the one or more processors are configured to receive a user input indicative of a selected port and / or supplier from the one or more candidate ports and / or suppliers. It may be that the one or more processors are configured to transmit the item data relating to the one or more items to the supplier that supplies the selected port and / or the selected supplier. Advantageously, the personnel on the watercraft or staff in a land-based office of a company of the watercraft can place an order with their choice of supplier who is closest to the intended route of the watercraft. The supplier can receive the order from the watercraft or the land-based office of a company of the watercraft without needing to look through each item in the item requests from the watercraft to determine which item is being requested and whether they have the required items in stock. It may be that the system comprises an input device. The input device may be for example a computer mouse and / or a keyboard. The system may comprise an input / output device such as a touchscreen. It will be appreciated that other forms of input devices may be envisaged. The user input may be indicative of an order for the one or more items from the selected port and / or supplier being placed. The one or more items may be transmitted as order data to the supplier that supplied the selected port and / or the selected supplier. The order data may comprise the item data. The order data may comprise information about the watercraft. The information about the watercraft may comprise at least one of: identification information of the watercraft, an intended arrival time at the selected port or the closest port to the location of the selected supplier and payment information of the watercraft. The selected supplier may be able to obtain the order data to prepare the order. Typically, the method is a method of sourcing items for a watercraft, meaning that the method may be a method of determining suppliers of items for the watercraft. The method may be a method of obtaining items for a watercraft and may include the method step of obtaining the one or more items from at least one of the one or more candidate ports and / or suppliers. The method may be carried out by one or more hardware processors. The method may be carried out by one or more computing devices. The method may be carried out by a distributed system. It may be that the one of more processors of the system are distributed. That is, the system may be a distributed system. It may be that the system comprises a plurality of modules which are made up of one or more processors. Typically, the system comprises an item request module which receives the one or more item requests. Typically, the system comprises an item data extraction module to extract the item data. The item data extraction module may comprise a data association module. The data association module may associate structured and unstructured data of the one or more item requests with the item data. The item data extraction module may comprise a document analysis module which performs document analysis of the one or more item requests. The document analysis module may include a visual cue feature analyser to analyse the layout of the document to identify one or more visual cue features. The item data extraction module may comprise a text recognition module which performs text recognition on the document. Typically, the system includes a route information module to determine route information. Typically, the system includes a supplier data module which receives supplier data of the one or more potential suppliers. Typically, the system includes a candidate port and / or supplier module which processes the item data, the route information and the supplier data to determine one or more candidate ports and / or suppliers of the one or more items. The system may comprise a combined input / output device. The combined input / output device may be external to the system. In some examples, the input and output devices may be separate. The candidate port and / or supplier module may process the item data, the route information and the supplier data by identifying ports and / or potential suppliers with a location within a predetermined distance of any point on the intended route between a destination of the route and the current location of the watercraft. The candidate port and / or supplier module may determine the candidate ports and / or suppliers of the items in dependence on predetermined criteria. The predetermined criteria may be stored in a memory. The system may comprise a memory. Other components of the system may also access the memory. Typically, the system includes a communications module which receives a user input indicative of a selected supplier from the candidate ports and / or suppliers. The communication module may communicate by wired and / or wireless communication with an external device. Typically, the method comprises accumulating the one or more items. Typically, the method comprises consigning the one or more items to the selected port and / or the port supplied by the selected supplier. Advantageously, the one or more items are provided to the selected port and / or the port supplied by the selected supplier so they can be picked up by the watercraft. Typically, the method comprises travelling to the selected port and / or the port supplied by the selected supplier to obtain the one or more items. Advantageously, the watercraft can collect the one or more items from the selected port and / or the port supplied by the selected supplier. It may be that the method step of receiving the one or more item requests comprises generating the one or more item requests. It may be that the method comprises receiving one or more sensor measurements. It may be that the method comprises generating the one or more item requests in dependence on the one or more sensor measurements. It may be that the one or more processors of the system receive the one or more item requests by being configured to generate the one or more item requests. It may be that the one or more processors are configured to receive one or more sensor measurements. It may be that the one or more processors are configured to generate the one or more item requests in dependence on the one or more sensor measurements. It may be that the system comprises one or more sensors configured to take the one or more sensor measurements. Advantageously, this means that the item request(s) can be generated automatically depending on the sensor measurements. The sensor measurements may be measurements associated with item stock on the watercraft. For example, the sensor measurements may be indicative of: consumption of an item on the watercraft, use of 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 an item on the watercraft, wear and tear of an item on the watercraft. The one or more sensors may be located on the watercraft in at least one: deck stores, engine stores and electrical stores. The one or more sensors may be Internet of Things (loT) devices. The one or more sensors may communicate using the loT with the one or more processors. The sensor may communicate wirelessly within the watercraft. It may be that at least one of the one or more sensors are configured to measure the amount of usage of an item (e.g. to determine when said item may be worn out). The system may comprise an item request generation module to generate item requests based on the one or more sensor measurements. It may be the one or more item requests are generated when a sensor measurement from a sensor is less than a predetermined threshold. The one or more item requests may be generated to order a sufficient number of an item to on board stock of the item up to a predetermined level. It may be that the one or more item requests are generated when a first predetermined time period has passed from when a sensor took a first measurement. Description of the Drawings An example embodiment of the present invention will now be illustrated with reference to the following Figures in which: Figures 1 to 4 are flowcharts of a method according to the invention; Figures 5a and 5b are examples of an item request according to the invention; Figures 6 and 7 are flowcharts of a method according to the invention; Figure 8 is an example of an output according to the invention; Figure 9 is a schematic of a system according to the invention; Figure 10 is a schematic of a system according to the invention; and Figure 11 is a flowchart of a method according to the invention. Detailed Description of an Example Embodiment Figure 1 is a flowchart illustrating a method 100 of the invention. The method 100 is a method of sourcing items for a watercraft. The method 100 comprises receiving 110 one or more item requests for one or more items. The personnel on the watercraft or staff in a land-based office of a company of the watercraft put together a list of the required items and other data to allow the supplier to fulfil the item requests, such as a quantity and any other descriptive information. The item request in this example is the form of document, namely a spreadsheet (e.g. .xlsx, ,xls or .ods file type), as will be discussed in more detail below. The item requests may include all unstructured data or may include a mix of structured and unstructured data. The item requests may be uploaded onto an online portal hosted on a webpage or Application Programming Interface (API). Alternatively, the item requests may be uploaded onto a computer program application (‘app’). The method 100 comprises processing 120 the one or more item requests to extract item data which relates to the items that have been requested by the watercraft. The item data includes structured data. The item data also includes other types of data that is not structured data but is still relevant to the requested items and allows the supplier to fulfil the order correctly. This includes for example item quantity (e.g. 1,10, 100), a unit of quantity (e.g. piece, kg, punnet), a colour, and brand. Other types of information will be envisaged. The method 100 includes determining 130 route information and receiving 140 supplier data. The method 100 includes processing 150 the item data, the route information and the supplier data of the potential suppliers to determine candidate ports and / or suppliers of the one or more items. The method 100 also includes providing 160 an output indicative of the candidate ports and / or suppliers to a user. These method steps will be discussed in more detail below. Figure 2 shows a flowchart of a method 200 according to the invention. The method step 120 can be achieved using the method 200 shown in Figure 2. The method 200 is a method of processing the item request(s) to extract the item data. In method step 210, the structured and / or unstructured data of the item request is associated with a type of item data. For example, if the item request includes a column of codes with 7 digit codes., this is associated with an ISSA code. Likewise, if the item request includes a column of codes with three groups of two numbers with a space between each group, this is associated with an I MPA code. In method step 220, the unstructured data of the item request(s) is associated with the structured data of the item data. For example, an item name of “tomatoes” in the item request is associated with the ISSA or I MPA code for tomatoes as the item data. In method step 230, the structured data of the item request(s) is associated with the structured data of the item data. For example, if the item request includes the ISSA or IMPA code for “tomatoes” then this is associated with the ISSA or IMPA code for tomatoes as the item data. These method steps are achieved by using an LLM which has been trained to identify data in an item request and associate it with types of item data, included structured data of the item data. In some examples, the method 200 may comprise only one of the method steps 210, 220 and 230. Figure 3 illustrates a flowchart of a method 300 according to the invention. The method 300 includes the method step 310 of performing document analysis on the item request. The document analysis is performed using a machine learning language model, such as an LLM, and text recognition. Figure 5a shows an example of an item request 500a. The item request 500a is a spreadsheet used by ‘Watercraft A’ or the company of ‘Watercraft A’ which identified by name 510 on the item request 500a. The name of the watercraft 510 is used as part of order data which is transmitted to a selected supplier, so the selected supplier knows the identity of the watercraft placing the order. The item request 500a includes information that may not be used in the method at all, such as logo 520. The item request 500a includes structured data 540 in the form of an IMPA code. The IMPA code is extracted from the item request 500a as item data. The IMPA code allows the supplier to know exactly which item is being requested. The item request includes unstructured data 550a, 550b, 550c. The unstructured data 550a is the unit of the item. The unstructured data 550b is the RQD (Required Quantity). This data is extracted as item data. This data allows the supplier to know how much of an item has been requested. The unstructured item data 550c is a name of the item. The name of the item can allow cross-referencing with the structured data 540 to check that an item has been correctly identified in the item data. In item request examples where the structured data 540 is not present, the name of the item 550c may be used to determine the structured data, i.e. the IMPA code. The item request 500a also includes ancillary data 530a, which is the date of the item request, and 530B, the units remaining on board (ROB). This information may be included in the item data but may not be essential data. Figure 5b shows an example of an item request 500b. The item request 500b is a spreadsheet used by ‘Watercraft B’ or the company of ‘Watercraft B’ which is identified by name 1510 on the item request 500b. The item request 500b, like the item request 500a, includes structured data 1540 in the form of an IMPA code. The IMPA code is extracted from the item request 500b as item data. The item request 500b includes unstructured data 1550a which includes a description of the item. However, this item description includes the name, quantity and size of the item. This data is extracted as item data so the supplier knows how much of an item has been ordered and can cross reference with the IMPA code to see which exact item has been ordered. As shown in item request 500b, the system and method described herein can work with item requests of various languages. Figure 4 shows a flowchart of a method 400 of performing document analysis. The method 400 includes identifying 410 one or more visual cue features of the layout of the document. The item requests 500a, 500b shows possible visual cue features 560, 570, 580, 1560, 1570 that may be identified. The visual cue feature 560 is a cell at the top of a column of non-empty cells with text in bold. The machine learning model is trained to recognise this visual cue feature 560 as being the header of a column. The visual cue feature 570 is a column of incrementing numbers (except for number 8). The machine learning model is trained to recognise this visual cue feature 570 as being a feature which indicates the entry numbers on a list. The visual cue feature 580 is text in a cell which is a format of three groups of two numbers, with a space between each group. The machine learning model is trained to recognise this visual cue feature 580 as being a feature which indicates a IMPA code. The visual cue feature 1560 is a column of cells filled with a colour. The machine learning model is trained to recognise this visual cue feature 1560 as being a feature which indicates a minimum accepted quantity of an item to be supplied by a supplier. The visual cue feature 1570 is a column of cells with coloured text. The machine learning model is trained to recognise this visual cue feature 1570 as being a feature which indicates a minimum accepted quantity of an item to be supplied by a supplier. The visual cue features 1560, 1570 can also be identified as a change in colouring or formatting, applied to a block, column or row of entries. Other types of visual features will be envisaged, such as length of text in a cell, column layout (e.g. width of the column), row layout (e.g. empty rows), border layout (e.g. where a table starts and ends indicated by borders), text formatting (e.g. bold, italic, underlined), changes in text formatting, spacing (e.g. between columns, between rows, between text within the same cell), lines, colouring, changes in colouring, and headings. The method 400 comprises associating 420 the visual cue features with a type of item data. For example, the visual cue feature 560 is associated with indicating a column of structured data (i.e. IMPA codes) The visual cue feature 570 is associated with indicating item data lies to the right of the column of incrementing numbers. The visual cue feature 580 is associated with structured data (i.e. IMPA codes). The method 400 includes performing 430 performing text recognition on the document to identify structured and / or unstructured data. For example, the text recognition can be used to extract the exact IMPA code 540, the unit 550a and the item name 550c. In some examples, the method 400 may comprise only one of the method steps 410, 420 and 430. Referring back to the method 100 shown in Figure 1, the method 100 includes determining 130 route information. The route information includes an intended route of the watercraft. In this example, the route information also includes a current location of the watercraft. The route information can be received from the watercraft or from a watercraft live tracking service. The method 100 also includes receiving 140 supplier data from potential suppliers. The potential suppliers are suppliers of items which may be able to provide the watercraft with the requested items. The supplier data includes a location of the respective potential suppliers and the item availability data of the respective supplier. The supplier data includes a location of a port supplied by the respective potential supplier. This means that the candidate ports and / or suppliers outputted to the user are ports and / or suppliers which are in a location that lies on the intended route of the watercraft and have the requested items in stock. The method 100 includes processing 150 the item data, the route information and the supplier data of the potential suppliers to determine candidate ports and / or suppliers of the one or more items. The method step 150 involves taking into account the requested items, the intended route of the watercraft, the location of the potential suppliers (i.e. the location of the port supplied by the respective potential supplier) and the availability of each item at the suppliers. Figure 6 shows a flowchart of a method 600 according to the invention. The method step 150 may be achieved by the method 600. The method 600 comprises identifying 610 the ports and / or potential suppliers which are located within a predetermined distance from the intended route. This means that the candidate ports and / or suppliers are those which have a location that is within a predetermined distance of the intended route. The method 620 comprises identifying 620 the ports and / or potential suppliers which are located within a predetermined distance of the destination of the intended route and the current location of the watercraft. This means that the candidate ports and / or suppliers are those which have a location that is within a predetermined distance of the intended route and lie ahead of the watercraft. It may be that the method 600 includes only method step 610. Method step 620 is a particular way of implementing method step 610 in that it identifies ports and / or potential suppliers lying on the intended route of the watercraft but in particular looks for those ports and / or suppliers lying ahead of the watercraft’s current position on the route. Figure 7 shows a flowchart of a method 700 according to the invention. The method step 150 may be achieved by the method 700. The method 700 includes the method step of determining 710 a candidate port and / or supplier or a plurality of candidate ports and / or suppliers of the item(s) in dependence on predetermined criteria. This means that the predetermined criteria are used to filter the potential suppliers to identify candidate ports and / or suppliers which fulfil the requirements of the predetermined criteria. The predetermined criteria are used to determine which candidate ports and / or suppliers are most appropriate for a given watercraft. The predetermined criteria can be used to specify a range of parameters by which to filter the ports and / or potential suppliers to determine candidate ports and / or suppliers. In this example, the first predetermined criterion is the minimum detour from the intended route that the watercraft would be required to travel to obtain the item(s) from the port and / or potential supplier. This could be a minimum detour in terms of time or fuel consumption or fuel cost. The second predetermined criterion is the minimum number of ports and / or potential suppliers required to obtain all of the items. This could entail consideration of one supplier sending a subset of the items to another supplier. Referring back to the flowchart of Figure 1 showing the method 100, the method step 160 includes providing an output indicative of the candidate port(s) and / or supplier(s) to a user. Figure 8 shows an example of an output 800. The output 800 shows a map with an indication of the candidate suppliers 810a, 810b, 810c thereon at their respective port locations. The output 800 also shows the watercraft, e.g. watercraft A, 820 and the route 830 using a dashed line (in this example the route 830 is from Colombo, Sri Lanka to Gibraltar, so the origin and destination are not shown on the output 800. The method 100 comprises the optional method steps 170 and 180 (shown in dashed boxes). A user can indicate which of the candidate suppliers they would like to place an order, or which of the ports they would like to pick up their order, with by providing an input. Using Figure 8 as an example, the selected port may be ‘Alexandria’ in Egypt, or the selected supplier may be Supplier B’ which supplies the port of Alexandria in Egypt. In method step 170, the user input of the selected port and / or supplier is received. In the method step 180, the item data is transmitted to the supplier which supplies the selected port and / or the selected supplier. The item data is part of order data which can include other information such as identifying information of the watercraft. The supplier can then use the item data to arrange for fulfilment of the order for the requested items from the item request. The method 100 comprises the optional method steps 185, 190 and 195 (shown in dashed boxes). The method step 185 comprises accumulating the one or more items. This may be performed by the selected supplier or the supplier that supplies the selected port. The supplier usually accumulates the items in a warehouse on land. The method step 190 comprises consigning 190 the one or more items to the selected port and / or the port supplied by the selected supplier. Using the example from Figure 8, Supplier B (as the selected supplier) accumulates the items at a warehouse in Egypt. Supplier B then consigns (i.e. delivers) the items to the port of Alexandria when the watercraft A is due to arrive. Whilst method steps 185 and 190 are being performed by the supplier, the watercraft travels 195 to the selected port and / or the port supplied by the selected supplier to obtain the one or more items. Using the example of Figure 8, the watercraft A travels through the Red Sea, along the Suez Canal and detours to stop in Alexandria, Egypt to pick up the items from the Supplier B. Figure 9 is a schematic of a system 900 according to the invention. The system 900 comprises a plurality of modules which are made up of one or more processors. Figure 9 shows components of the system 900 and corresponding data flows. The system 900 includes an item request module 910 which receives F05 item requests for items. The item requests are usually in the form of an excel spreadsheet (but can be provided in another document format, such as a pdf or a link from an external system for example through an API), and are uploaded onto a server by a watercraft or staff in a land-based office of a company of the watercraft and accessed on the server or downloaded from the server by the item request module 910. The item requests are sent F10 to be processed by the item data extraction module 920 to extract item data relating to the items. The item data extraction module 920 comprises a data association module 921 which associates structured and unstructured data of the item request(s) with the item data, such as structured data of the item data. The item data extraction module 920 comprises a document analysis module 922 which performs document analysis of the item requests. The document analysis module 922 includes a visual cue feature analyser 922a which analyses the layout of the document to identify one or more visual cue features. The data association module 921 also associates the one or more visual cue features with a type of item data. The item data extraction module 920 comprises a text recognition module 922b which performs text recognition on the document to identify structured and / or unstructured data. The system 900 includes a route information module 930 to determine route information, which includes an intended route of the watercraft and a current location of the watercraft. The route information module determines F15 the route information using data from an external source. In some examples, the route information may be determined from the item request, in which case the item request is transmitted from the item request module 910 to the route information module 930. The system 900 includes a supplier data module 940 which receives F20 supplier data of potential suppliers from an external source, e.g. an external database. The supplier data comprises a location of a port supplied by each potential supplier and item availability data. The system 900 includes a candidate port and / or supplier module 950 which processes the item data, the route information and the supplier data of the potential suppliers to determine one or more candidate ports and / or suppliers of the item(s). The candidate port and / or supplier module 950 receives F25 the item data from the item data extraction module 920. The candidate port and / or supplier module 950 receives F30 the route information from the route information module 930. The candidate port and / or supplier module 950 receives F35 the supplier data from the supplier data module 940. The system 900 candidate port and / or supplier module provides F40 an output to a combined input / output device 960 which may form part of the system 900 or may be external to the system 900. In some examples, the system 900 may have or may communicate with separate input and output devices. The candidate port and / or supplier module 950 processes the item data, the route information and the supplier data by identifying ports and / or potential suppliers with a location within a predetermined distance of any point on the intended route between a destination of the route and the current location of the watercraft. The candidate port and / or supplier module 950 determines the candidate ports and / or suppliers of the items in dependence on predetermined criteria. The predetermined criteria are stored in a memory 980. The candidate port and / or supplier module 950 accesses F55 the predetermined criteria from the memory 980. Other components of the system 900 may also access the memory 980 to read or write to the memory 980. The system 900 includes a communications module 970 which receives F45 a user input indicative of a selected port and / or supplier from the candidate ports and / or suppliers. The system 900 includes a communications module 970 to receive the user input and to transmit F50 the item data relating to the one or more items to the supplier that supplies the selected port or the selected supplier. This may be achieved by wireless communication with an external device belonging to the selected supplier. Figure 10 is a schematic of a system 1000 according to the invention. The system 1000 includes all of the same components as system 900 illustrated in Figure 9. However, system 1000 also includes one or more sensors 1001 positioned at item stores around the watercraft. The sensor measurements from the one or more sensors 1001 are transmitted F01 to the item request generation module 1005 which generates item requests based on the sensor measurements. The item requests are then sent F05 to the item request module 910 as in system 900. The one or more sensors 1001 may be RFID sensors or Bluetooth sensors. The one or more sensors 1001 may be attached to items. The one or more sensors 1001 communicate with wireless communication points, such as WiFi access points, around the watercraft. The items may have identifiers, such as RFID tags or stored MAC addresses or other identification data. The identifiers may be used to determine that an item has been consumed (or used). Figure 11 is a flowchart of a method 1100 according to the invention. The method comprises receiving 1110 one or more sensor measurements and generating 1120 the one or more item requests in dependence on the one or more sensor measurements. In summary, there is provided a method 100 of sourcing items for a watercraft. The method 100 comprises receiving 110 one or more item requests for one or more items; processing 120 the one or more item requests to extract item data relating to the one or more items; determining 130 route information of the watercraft, the route information comprising an intended route of the watercraft; receiving 140 supplier data of one or more potential suppliers, the supplier data comprising a location of a port supplied by the respective potential supplier; processing 150 the item data, the route information and the supplier data of the one or more potential suppliers to determine one or more candidate ports and / or suppliers of the one or more items; and providing 160 an output indicative of the one or more candidate ports and / or suppliers to a user. Throughout the description and claims of this specification, the words “comprise” and “contain” and variations of them mean “including but not limited to”, and they are not intended to and do not exclude other components, integers, or steps. Throughout the description and claims of this specification, the singular encompasses the plural unless the context otherwise requires. In particular, where the indefinite article is used, the specification is to be understood as contemplating plurality as well as singularity, unless the context requires otherwise. Features, integers, characteristics, or groups described in conjunction with a particular aspect, embodiment, or example of the invention are to be understood to be applicable to any other aspect, embodiment or example described herein unless incompatible therewith. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and / or all of the steps of any method or process so disclosed, may be combined in any combination, except combinations where at least some of such features and / or steps are mutually exclusive. The invention is not restricted to the details of any foregoing embodiments. The invention extends to any novel one, or any novel combination, of the features disclosed in this specification (including any accompanying claims, abstract and drawings), or to any novel one, or any novel combination, of the steps of any method or process so disclosed. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

Claims

1. A method of sourcing items for a watercraft, the method comprising: receiving one or more item requests for one or more items; processing the one or more item requests to extract item data relating to the one or more items;determining route information of the watercraft, the route information comprising an intended route of the watercraft;receiving supplier data of one or more potential suppliers, the supplier data comprising a location of a port supplied by the respective potential supplier;processing the item data, the route information and the supplier data of the one or more potential suppliers to determine one or more candidate ports and / or suppliers of the one or more items; andproviding an output indicative of the one or more candidate ports and / or suppliers to a user.

2. The method of claim 1, receiving a user input indicative of a selected port and / or supplier from the one or more candidate ports and / or suppliers, optionally wherein the method comprises transmitting the item data relating to the one or more items to the supplier that supplies the selected port and / or the selected supplier.

3. The method of claim 1 or claim 2, wherein the item data comprises structured data, optionally wherein the one or more item requests comprise unstructured data and wherein processing the one or more item requests to extract the item data comprises associating the unstructured data of the one or more item requests with the structured data of the item data.

4. The method of claim 3, wherein the one or more item requests comprise structured data and wherein processing the one or more item requests to extract the item data comprises associating the structured data of the one or more item requests with the structured data of the item data.

5. The method of any preceding claim, wherein the one or more item requests comprise a document and wherein processing the one or more item requeststo extract the item data comprises performing document analysis of the one or more items requests.

6. The method of claim 5, wherein performing document analysis comprises identifying one or more visual cue features of the layout of the document, optionally wherein the one or more visual cue features of the layout of the document are selected from a group comprising: text length, column layout, row layout, border layout, text formatting, changes in text formatting, spacing, lines, colouring, changes in colouring, and headings.

7. The method of claim 6, wherein performing document analysis comprises associating the one or more visual cue features with a type of item data.

8. The method of claim 5 or any claim dependent thereon, wherein performing document analysis comprises performing text recognition on the document to identify structured and / or unstructured data, optionally wherein processing the one or more item requests to extract the item data comprises associating the structured and / or unstructured data of the one or more item requests with a type of item data.

9. The method of any preceding claim, wherein the supplier data comprises item availability data of the respective supplier.

10. The method of any preceding claim, wherein processing the item data, the routeinformation and the supplier data of the one or more potential suppliers to determine the one or more candidate ports and / or suppliers of the one or more items comprises identifying ports and / or potential suppliers with a location within a predetermined distance of any point on the intended route.

11. The method of any preceding claim, wherein the route information comprises a current location of the watercraft, optionally wherein processing the item data, the route information and the supplier data of the one or more potential suppliers to determine the one or more candidate ports and / or suppliers of the one or more items comprises identifying ports and / or potential suppliers with a location within a predetermined distance of any point on the intended route between a destination of the route and the current location of the watercraft.

12. The method of any preceding claim, comprising determining the one or more candidate ports and / or suppliers of the one or more items in dependence on predetermined criteria, optionally wherein the predetermined criteria comprise at least one of:the minimum detour from the intended route that the watercraft would be required to travel to obtain the one or more items from the port and / or the one or more potential suppliers, andthe minimum number of ports and / or potential suppliers of all of the one or more items.

13. A computer readable storage medium comprising instructions which, when the program is executed by a computer, cause the computer to carry out the method of any of claims 1 to 12.

14. A system for sourcing items for a watercraft, the system comprising one or more processors configured to:receive one or more item requests for one or more items;process the one or more item requests to extract item data relating to the one or more items;determine route information of the watercraft, the route information comprising an intended route of the watercraft;receive supplier data of one or more potential suppliers, the supplier data comprising a location of a port supplied by the respective potential supplier;process the item data, the route information and the supplier data of the one or more potential suppliers to determine one or more candidate ports and / or suppliers of the one or more items; andprovide an output indicative of the one or more candidate ports and / or suppliers to a user.

15. The system of claim 14, wherein the one or more processors are configured to receive a user input indicative of a selected port and / or supplier from the one or more candidate ports and / or suppliers, optionally wherein the one or more processors are configured to transmit the item data relating to the one or more items to the supplier that supplies the selected port and / or the selected supplier.

16. The system of claim 14 or claim 15, wherein the item data comprises structured data, optionally wherein the one or more item requests comprise unstructured data and wherein the one or more processors are configured to process the one or more item requests to extract the item data by associating the unstructured data of the one or more item requests with the structured data of the item data.

17. The system of claim 16, wherein the one or more item requests comprise structured data and wherein the one or more processors are configured to process the one or more item requests to extract the item data by associating the structured data of the one or more item requests with the structured data of the item data.

18. The system of any of claims 14 to 17, wherein the one or more item requests comprise a document and wherein the one or more processors are configured to process the one or more item requests to extract the item data by performing document analysis of the one or more item requests.

19. The system of claim 18, wherein the one or more processors are configured to perform document analysis by identifying one or more visual cue features of the layout of the document, optionally wherein the one or more visual cue features of the layout of the document are selected from a group comprising: text length, column layout, row layout, border layout, text formatting, changes in text formatting, spacing, lines, colouring, changes in colouring, and headings.

20. The system of claim 19, wherein the one or more processors are configured to perform document analysis by associating the one or more visual cue features with a type of item data.

21. The system of claim 18 or any claim dependent thereon, wherein the one or more processors are configured to perform document analysis by performing text recognition on the document to identify structured and / or unstructured data, optionally wherein the one or more processors are configured to process the one or more item requests to extract the item data by associating the structuredand / or unstructured data of the one or more item requests with a type of item data.

22. The system of any of claims 14 to 21, wherein the supplier data comprises item availability data of the respective supplier.

23. The system of any of claims 14 to 22, wherein the one or more processors are configured to process the item data, the route information and the supplier data of the one or more potential suppliers to determine one or more candidate suppliers of the one or more items by identifying ports and / or potential suppliers with a location within a predetermined distance of any point on the intended route.

24. The system of any of claims 14 to 23, wherein the route information comprises a current location of the watercraft, optionally wherein the one or more processors are configured to process the item data, the route information and the supplier data of the one or more potential suppliers to determine one or more candidate ports and / or suppliers of the one or more items by identifying ports and / or potential suppliers with a location within a predetermined distance of any point on the intended route between a destination of the route and the current location of the watercraft.

25. The system of any of claims 14 to 24, wherein the one or more processors are configured to determine the one or more candidate ports and / or suppliers of the one or more items in dependence on predetermined criteria, optionally wherein the predetermined criteria comprise at least one of:the minimum detour from the intended route that the watercraft would be required to travel to obtain the one or more items from the port and / or the one or more potential suppliers, andthe minimum number of ports and / or potential suppliers to obtain all of the one or more items.

26. The method of claim 2 or any claim dependent thereon, comprising accumulating the one or more items and consigning the one or more items to the selected port and / or the port supplied by the selected supplier.1 27. The method of claim 2 or any claim dependent thereon, comprising travelling 2 to the selected port and / or the port supplied by the selected supplier to obtain3 the one or more items.A

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