A rising tide lifts all the boats: AgGateway’s Collaborative Model for Identification in Field Operations

Berne, Dan; Craker, Ben; Ferreyra, R. Andres; Hillyer, Charles C.; Rhea, Stuart T.; Tevis, Joseph; Wilson, James A.; Wilson, Jeremy

Contemporary farming requires the continuous exchange of information between growers and partners such as agronomists, retailers, custom applicators, insurance agents and customers. A critical part of this interoperability is identification, where a name or code (the “identifier”) is used to reference a particular instance of an object. This enables farm management information systems (FMIS) to distinguish between that unique instance and other instances, and to recognize an instance when encountering it again. There are multiple motivations for uniquely identifying resources in production agriculture data exchange. Examples include unambiguously specifying the products being applied (or planned for application) in a particular field operation; unambiguously specifying the location(s) where these products are applied; and enabling an audit trail (the aspiration of having farm-to-fork traceability) for all the processes of interest[BC1] .

Workflows involving identification often break down when a grower (or other actor) imports data into their FMIS from an external source such as a machine-implement control system (MICS) or other FMIS. Incoming data (that may correspond to objects such as farms, fields, and products in the grower’s own FMIS) might contain externally-created identifiers that the grower’s FMIS does not recognize. The user must then manually match these unknown identifiers with known objects in their system. (This process can be supported by spatial overlap checking, string comparison metrics, and so forth). Users do not like this data mapping (also called record linkage, and object identification): it is time-consuming and error-prone, and is ultimately an obstacle to the broader adoption of precision ag technologies, especially given that users increasingly have an expectation of “frictionless data entry.”

A centralized approach to identification might seem like a solution: supply-chain operations increasingly use GTINs (Global Trade Item Numbers), GLNs (Global Location Numbers), and EANs (International Article Numbers), all codes minted by one or more numbering authorities (such as GS1). This makes clear where the identifier originated (henceforth, its “source”) and what its meaning is. This approach seems ill-suited for the current context in field operations, however; a given user might require thousands of identifiers for their farms, fields and documents; those identifiers may be needed in situations of no Internet connectivity, and paying for identifiers may seem counter-intuitive to the end-user. Moreover, agricultural data exchange happens in a context of scant format standardization: different FMIS and MICS systems use a variety of identifier data types, such as integers, GUIDs (Globally Unique Identifiers), URIs (Universal Resource Identifiers), DOIs (Digital object identifiers), and GLNs (Global Location Numbers). This plethora of different identification schemes makes it even harder to interoperate.

AgGateway’s collaborative model for identification is presented as a potential, distributed, solution. It has a technological component and a social component: The technological component is based on the Compound Identifier, a sort of “basket of identifiers” that associates an object with one or more identifier-source pairs, analogous to what is enabled in ISO 11783 Annex E-mediated Linklist files. The social component consists of encouraging the actors in an exchange process to preserve all the identifiers they receive for a given object, and to pass them all along, together with their own identifier (if it exists) to the next actor in the communication process.

Multiple examples are presented detailing the use of compound identifiers to identify different objects within a farm management information system (e.g., grower / farm / field, equipment, documents).

ASABE keywords: information systems; software; identification; record linkage; standards

Submitted.

Andres made first draft, sent to others. Stuart and Ben gave feedback.

Idea / conclusion for paper:

While we may eventually arrive at some centralized method of assigning identity, that is not where we are today. The CompoundIdentifier-based approach accepts the reality that growers, farms, fields, etc. already have multiple identifiers spread across the systems of various stakeholders.

Observations and measurements are the cornerstone of principled decision-making in agricultural field operations. They are the information captured in crop scouting for crop protection, nutrition and harvest; in postharvest grain weight and quality certificates; in soil and manure lab tests; in asset management and telematics (e.g., observing grain bin / dryer conditions); and are also the multiple environmental inputs used to drive irrigation decisions.

The ISO 19156 standard defines a data model for representing various aspects of observations, such as ultimate and sampling features of interest, observed properties, and the procedures used to derive the observation result. However, the standard does not include vocabularies for capturing the myriad specific combinations of these aspects used in agriculture.

AgGateway’s global effort toward interoperability identified value in implementing an ISO 19156 – based model of observations and measurements for agricultural field operations. This work, centered on the PAIL, SPADE and ADAPT projects, emphasizes the explicit capture of the semantics of the various aspects of an observation. The work, performed by a group of industry and academic AgGateway participants spanning four continents, includes three major parts:

First, defining a componentized model of the properties of an observation, based on an extensible set of orthogonal vocabularies, which includes representing valid combinations of components. Second, deploying infrastructure, in the form of a RESTful API, to make the componentized variable definitions freely available to industry and the research community; this includes putting into place an ISO 19135-based process for stakeholders to request the addition of vocabularies or entries therein. Third, incorporating observations and measurements into AgGateway’s ADAPT common object model and format conversion plug-in architecture, thus enabling widespread interoperability.

The diversity of agricultural sources of observations and measurements makes it challenging to implement a system that is both comprehensive and consistent. The work described here enables growers and their advisers to not only gather the data but to integrate them into their decision-making.ASABE keywords: measurement; information systems; data collection; ISO standard; software

• Could include:
• Glossary
• ContextItems
• Representations
• OM codes
• ISO 19135 Governance
• ISO 25964

Helping machines and people agree on what things mean in production agriculture: AgGateway’s Glossary and Semantic Infrastructure

AgGateway is a nonprofit consortium of 240+ companies dedicated to advancing implementation of standards for interoperability in agriculture. Its work originally targeted supply chain processes, but was expanded in 2010 to include production agriculture field operations such as planting, crop protection, crop nutrition, irrigation, and harvest. An important deliverable of AgGateway’s field operations projects (SPADE, PAIL) has been to identify the data variables that support the growers’ field operations processes, document their meaning, and establish the various contexts in which they are used. It subsequently became necessary to create machine-readable variable type registries, controlled vocabularies, and other semantic resources to facilitate interoperability, thus enabling all participants in a data exchange process (or their software, rather) to unambiguously understand the meaning of the data being exchanged. These resources will be made available to users primarily through one or more application programming interfaces (APIs) for use by farm management information systems (FMIS) and other software.

There are so far three fundamental types of variable registries in this semantic infrastructure: a) The Representation System, which describes “universal” variables and their units of measure (e.g., yield as mass per unit area), derived from an internal representation system John Deere donated to the ADAPT project; b) The ContextItem System, which describes geopolitical-content-dependent variables (e.g., EPA numbers, FSA tract Ids) and complements the Representation system; c) Observation Codes, which are a specialized form of representation system built using the ContextItem system’s sophisticated architecture.

This infrastructure will require ongoing additions and maintenance, but the resources’ and APIs’ originating projects (e.g., SPADE, PAIL) have a finite duration. AgGateway’s Standards and Guidelines Committee consequently saw fit to create a Controlled Vocabularies Working Group (CVWG) to provide a permanent home for the semantic resources’ management processes. The overarching intent is to create resources that will be used extensively by the industry. An important precondition for that usage is transparency in governance; as a result, the CVWG derived its governance model from the ISO 19135 standard for register management.

AgGateway has also invested in a human-readable Glossary, hosted at www.agglossary.org and designed to bring together agricultural terminology from different sources (e.g., ASABE) as an educational resource and discussion-support tool. This resource includes a taxonomy for representing the origin and context of each term, and was initially hosted using the MediaWiki platform. The Glossary Team is now working toward upgrading the architecture of the glossary, seeking machine-readabiity and compatibility with the ISO 25964 data model, in pursuit of maximizing the value of the resource to contributors and users of the data, especially for concepts and terms that may be contained within it and not in international efforts such as GACS (the Global Agricultural Concept Scheme); e.g., legal terms and terms derived from ASABE (and other) standards.

ASABE keywords: information systems; software; semantics; infrastructure; API

Submitted.

Andres made first draft, sent to others.

At v4.

Andres intiated; got Charles feedback; now on v3.

Distributed to the rest of the group for input.

Application of the Precision Ag Irrigation Language (PAIL)

Over the past six years, a team of industry professionals and Extension researchers has developed a standard that supports data exchange among irrigation technologies.  The standard is currently in the process of balloting to become an ASABE standard.

The North Plains Groundwater Conservation District (NPGCD) in the Texas panhandle has funded development of an integrated irrigation management system.The motivation for this system stems from the disparate sources of information needed for precise management of irrigation.  The Texas panhandle region has critical water shortages because of declining aquifer levels.  Producers in the region have a reputation as progressive adopters of new technology when those technologies provide real benefit to their operations.  Irrigation management technologies maximize their benefit when used in concert with tools that focus on particular elements of the water management process.  Thusly, technology integration becomes an important of a management system.

The system is “integrated” in that it combines information from multiple sources into a single web application.  The PAIL standard is the key enabling element of this integrated system.  Each of the data sources (weather stations, soil moisture sensors, and pivot control system) sends or receives information in the PAIL format.  The development of NPGCD’s integrated system began in December of 2016 and is undergoing preliminary testing during the 2017 irrigation season.  In this paper, we present an overview of the PAIL standard and basic examples of PAIL’s core documents from each of the data sources used in the NPGCD project.  Additionally, we will present initial results from the development and application of the NPGCD’s system and observations relating to how the PAIL standard reduced cost and complexity for the system’s software.

Keywords: PAIL, irrigation management, data exchange, standards, systems integration

Charles intiated; got Andres feedback; now on v3.

Distributed to the rest of the group for input.

• Shannon
• Marty Matlock
• Brandon? 
• Andres*

• Andres
• Stuart*
• Simon / Nick?

Where did this data come from and how was it made? Introducing a provenance model into ADAPT

The agricultural industry is increasingly interconnected, and the volume of data being exchanged among growers and other actors is rapidly escalating.  It is also becoming critically important to document the provenance of the digital objects being exchanged; i.e., information about the entities, activities, and people involved in producing, delivering, or modifying a piece of data or thing. This provenance data can be used to form assessments about the object of interest’s quality, reliability or trustworthiness, and can be crucially important for mitigating liability.

The World-Wide Web Consortium (W3C) has published a provenance standard, PROV. This standard accommodates agent-centered provenance (e.g., Who created this data set? Who collected or tested this soil sample?), object-centered provenance (by tracing the origins of a document, or parts thereof, to other documents; e.g., What work order motivated this field operation? What set of field observations motivated this recommendation to irrigate?), and process-centered provenance (describing what steps were taken to generate a particular piece of information; e.g., what corrections have been applied to this yield dataset? What geometric and/or radiometric corrections have been applied to this drone-collected remote sensing dataset?)

AgGateway’s field operations projects (SPADE, PAIL, ADAPT) have produced a common object model of agricultural field operations that provides an opportunity for the industry to transcend long-standing interoperability limitations and exchange data in a common format. The existence of this platform provides a valuable opportunity to introduce a provenance framework that can be used to support traceability and principled decision-making in agriculture. This paper describes how the PROV model can be added to ADAPT, and provides specific examples of its application to some fundamental provenance use cases in field operations: documenting change in reference data and variable type registries;  documenting the lifecycle of machine configuration data; documenting relationships among core documents in field operations (i.e., Plan, Observations and Measurements, Recommendations, Work Orders, and Work Records); and supporting traceability.

(May differ from final)

Farmers increasingly find themselves exchanging data with various partners. The reasons for this increase range from ever-increasing regulatory pressure, to the need for increased efficiency in the context of increasing input process and decreasing harvested commodity prices, to the public's concern about food safety and origin.

Unfortunately, the bottom-up way that agricultural data has grown in the past 20 years has led to serious interoperability problems, due partly to the wide variety of proprietary formats, code lists, etc. in use in the industry; partly to the lack of universal use of unique identifiers, and also the profusion of proprietary controlled vocabularies (i.e., code lists) and concepts.

AgGateway is a consortium of 200+ companies seeking to solve these problems in supply-chain and field operations, with an emphasis on collaboration and the implementation of existing standards whenever possible. Initially AgGateway’s work was focused on solving supply chain (manufacturers, distributors) “pain points”, then moved to the retailer, and finally to the grower's field operations.

ADAPT is an open-source project initiated by AgGateway that seeks to put in place infrastructure that can enable the needed interoperability. ADAPT has two primary components:

• A common data/object model, designed to be a superset of the ISO 11783 model and those of participating companies, and
• A plug-in framework. Plug-ins are software libraries (proprietary or open-source, as chosen by their creator) that can interconvert between the common object model and a given format of interest.

Converting formats, however, is not enough to guarantee interoperability: a system of shared meaning is also required. For this reason, ADAPT has been designed with an emphasis on unique identifiers, and the use of data-type registries and other semantic assets that can ensure that all the participants in a data exchange process interpret the data in the same way.

This paper describes business and technical aspects of ADAPT, including its data model, plug-in architecture, licensing and governance, and ongoing AgGateway work on data ownership and privacy.

• DANIEL DANFORD
• R. Andres Ferreyra (Unlicensed)
• Kelly Nelson
• Stuart Rhea (Unlicensed)
• Mark Stelford (Unlicensed)
• Jim Wilson

Modern farming requires increasing amounts of data exchange among hardware and software systems. Precision agriculture technologies were meant to enable growers to have information at their fingertips to keep accurate farm records (and calculate production costs), improve decision-making and promote efficiencies in crop management, enable greater traceability, and so forth. The attainment of these goals has been limited by the plethora of proprietary, incompatible data formats among equipment manufactures and farm management information systems (FMIS), along with a lack of common semantics (meaning) in the industry. Proposed partial solutions exist; e.g., the ISO11783.10 standard XML format is well-known and respected, but it is machinery-specific and does not include business-process details needed by growers’ FMIS.

AgGateway is an industry consortium of 200+ companies in the agricultural industry. In 2013-14, its SPADE project explored the feasibility of the industry developing an open-source format conversion toolkit. This experience led to what is now its ADAPT Committee.

The ADAPT team created a common object model or "Application Data Model" (ADM), a super-set of field operations data models presented by participating companies. The goal: to replace the current, fragile situation, where FMIS must support multiple hardware data formats, and each machinery manufacturer has to interact with multiple software companies, with a single ADM integration mediated by a framework (initially built on .NET Framework 4.5) from which manufacturer-specific plug-ins convert to and from proprietary formats. This enables the FMIS to read/write to a wide variety of systems with little incremental effort, using ADAPT as a form of a digital agriculture Rosetta stone. A special emphasis was placed on developing a data-driven approach to managing geopolitical-context-dependent information, and on delivering shared meanings (semantic resources) through application programming interfaces (APIs). 

Licensing is an important consideration when seeking to promote the wide adoption of a software platform. The ADAPT Committee selected the well-known, and broadly accepted, open-source Eclipse Public License for the ADM, the conversion framework, and community plug-ins. The licensing model for proprietary plug-ins is different from that of the community-supported tools: each plug-in writer can choose whatever licensing and distribution model best fits their business model.

Several machinery manufacturers have already begun writing plug-ins for their hardware; their projects are at different stages of development. There are currently two community-supported plug-ins: one to convert ISO ISO11783-10 XML files; and another to perform lossless serialization and de-serialization of ADM instances. The former serves as a template for machinery companies that use the ISOXML format to customize, and the latter enables FMIS-to-FMIS communication, a critically-important function that the industry has been lacking. Future plans for community-supported plug-ins include one for the Precision Agriculture Irrigation Language (PAIL) format, and another for sustainability metrics.

The ADAPT Committee has a GitHub repository for source code, a transparent governance system, an email list for questions (ADAPT.Feedback@AgGateway.org), and accepts contributions from outside AgGateway. The application’s scope includes self-propelled machines, non-mechanical processes, observations and measurements, and post-harvest traceability. The intention is for it to facilitate the growth of digital agriculture.

• Ben Craker (Unlicensed)
• R. Andres Ferreyra (Unlicensed)
• Shannon Haringx (Unlicensed)
• Todd Howatt
• Joe Tevis
• Jim Wilson

Draft HERE

Contemporary farming requires increasing amounts of data exchange among a myriad of hardware and software products. Growers and other stakeholders need these products to interoperate, but implementation of data exchange standards has been uneven across the industry, especially among software companies.

AgGateway is an industry consortium dedicated to promoting the implementation of standards in digital agriculture. It provides a collaborative environment where the industry can discuss interoperability pain points, identify standards that can address those pain points, and then engage the corresponding standards organizations to collaborate on implementation and/or enhancements.

This paper reviews a set of standards relevant to agricultural field operations and supply chain data exchange, created by organizations such as AEF, AgXML, ASABE, ISO, OAGI, and W3C; it then describes the relevance of these standards to AgGateway’s interoperability projects such as ADAPT, CART, PAIL, PICS, and SPADE, which cover a wide range of processes. The discussed processes involve field operations, such as planting, crop nutrition, crop protection, irrigation, harvest, and post-harvest; and also supply-chain operations pertaining to crop inputs (seed, crop protection and fertilizers) and traceability of harvested commodities.

Abstract submitted

ID #1302

Response 1/29

Due 6/15

• R. Andres Ferreyra (Unlicensed)
• Scott Nieman
• Frank Riddick (Unlicensed)
• Joe Tevis
• Evan Wallace
• Jeremy W Wilson
• Jim Wilson

The Commodity Automation by Rail and Truck (CART) project is a joint development effort of AgGateway's Precision Ag Council and Grain and Feed Council. The project aims to provide grain traceability from field to fork. Doing this involved understanding the business processes and data exchanges required, all the way from farm operations through grain elevators to receiving at a feed manufacturer; exploring solutions through small proof-of-concept (PoC) projects; and enhancing and implementing existing standards, primarily the ISO 11783 standard for farm machinery electronics, and the AgXML standard for grain data exchange. Other existing standards and emerging technologies such as IoT and Blockchain were evaluated against these processes for suitability, and recommendations for enhancements and implementation were provided to the industry. Gaps for future enhancements were identified for future research and follow-up, especially for out-of-band processes including logistics provides and grain movement operations through aging elevators that have minimal human-machine interface integration and process control automation.

Various Proof-of-Concepts (PoC) were conducted in 2014, 2017 and 2018, covering key itinerary legs of the business process, focusing on commodity transfers from source container to target containers, duration of the transfer, and method of the transfer. Bluetooth Low Energy (BLE) beacons were used to pair containers following an Internet of Things (IoT) approach. A set of proposed changes to the ISO 11783-10 standard emerged from the field operations PoCs, and is detailed. Additionally, a set of changes was proposed to the AgXML standard, which will result in a new release (version 5.0) of the same. The latter includes a new IoT message called TransferEvent and a bundling of one or more of these TransferEvents into the existing AgXML CommodityMovement message under an element named RelatedTransferEvents. Representation of the AgXML TransferEvent in JSON format is also presented, and compared to other IoT ingestion methods. The applicability of these standards within each of the processes is defined.

The business benefits using these standards include:
1. Efficiency improvements in the grain receiving process as a result of the receipt of shipment information into the respective business application(s) prior to the physical arrival of the grain,
2. Ability to review weights and grade of a specific shipment prior to arrival, as well has last load (what) and relate container cleaning event (who, when, how).
3. Automatic identification of grain transport containers upon the arrival of the shipment using BLE or RFID identification, with the potential of immediate retrieval of the shipment information.
4. Enabling identification of grain elevator/ processor load out bin into each shipping container (e.g., rail car or semi-trailer), enabling the traceability goals of the Food Safety Modernization Act (FSMA).
5. Elimination of paper documents and file cabinets as warranted.
6. Addresses increasing concern by consumers where their food comes from, either for human and livestock consumption.

Abstract submitted

IS #1319

Response 1/29

Due 6/15

1

ASABE AIM

Spokane, Jul 16-19

CompoundIdentifier / persistent identifier / basket / Sources

• Ben Craker (Unlicensed)
• Charles Hillyer (Unlicensed)
• Stuart Rhea (Unlicensed)
• R. Andres Ferreyra (Unlicensed)*
• Joe Tevis
• Jeremy W Wilson
• Jim Wilson

1 AgGateway 2017 ASABE AIM Abstract - Identifiers.pdf

2

ASABE AIM

Spokane, Jul 16-19

O&M framework, ISO 19156 implementation, codes, RDAPI to deliver them

• Richard Andrus (Unlicensed)
• aberger@agsense.net (Unlicensed)
• Dan Berne (Unlicensed)
• Eugenia Durand
• R. Andres Ferreyra (Unlicensed)*
• Charles Hillyer (Unlicensed)
• Kiyoshi Honda
• Eric Hudish
• Bart Nef (Deactivated)
• Kyohei Ohtsuka
• Stuart Rhea (Unlicensed)
• Jim Wilson

* Corresponding author

2 AgGateway 2017 ASABE AIM Abstract - Observations.pdf

3

Semantic infrastructure & Glossary

Spokane, Jul 16-19

• Could include:

• Glossary

• ContextItems

• Representations

• OM codes

• ISO 19135 Governance

• ISO 25964

• Dennis Daggett (Deactivated)
• R. Andres Ferreyra (Unlicensed)*
• Rachel Garrett (Unlicensed)
• Stuart Rhea (Unlicensed)
• Joe Russo (Unlicensed)
• Jim Wilson

3 AgGateway 2017 ASABE AIM Abstract - Semantic Infrastructure.pdf

4

ASABE PAIL

Spokane, Jul 16-19

PAIL (Fundamentals)

• Diganta Adhikari (Unlicensed)
• Richard Andrus (Unlicensed)
• aberger@agsense.net (Unlicensed)
• Dan Berne (Unlicensed)
• Kurtis Charling (Unlicensed)
• R. Andres Ferreyra (Unlicensed)*
• Charles Hillyer (Unlicensed)
• Bart Nef (Deactivated)
• Joe Russo (Unlicensed)

4 AgGateway 2017 ASABE AIM Abstract - PAIL Fundamentals.pdf

5

ASABE PAIL - Application

Spokane, Jul 16-19

PAIL (Applications)

• Diganta Adhikari (Unlicensed)
• Richard Andrus (Unlicensed)
• aberger@agsense.net (Unlicensed)
• Dan Berne (Unlicensed)
• Kurtis Charling (Unlicensed)
• R. Andres Ferreyra (Unlicensed)
• Charles Hillyer (Unlicensed)*
• Bart Nef (Deactivated)
• Joe Russo (Unlicensed)

5 AgGateway 2017 ASABE AIM Abstract - PAIL Application.pdf

ASABE AIM

Spokane, Jul 16-19

TBD. Idea: Metrics-based sustainability, Field to Market and ADAPT.

• Ed Barnes

• R. Andres Ferreyra (Unlicensed)*

• Shannon Haringx (Unlicensed)

• Marty Matlock

• Brandon Sharp

6 AgGateway 2017 ASABE AIM abstract - Sustainability.pdf

ASABE AIM

Spokane, Jul 16-19

TBD. Idea: PROV implementation in field operations data

• Andres*

• Stuart

• Simon Cox

• Nick Car

7 AgGateway 2017 ASABE AIM abstract - Provenance .pdf

ASABE AIM

Spokane, July 16-19

TBD. Idea: ContextItem management with ISO 19135

Superseded by Semantic Infrastructure paper

ASABE AIM

Spokane, July 16-19

New and improved ADAPT. Emphasis on representation system / unit system?

Leave out of ASABE

ASABE AIM

Spokane, July 16-19

Four ideas pitched to AgGateway-Europe for Agritechnica?

• CompoundIdentifier "basket of Ids"

• Reference data as an API-enabled distributed system

• Enabling principled decision-making: CP recommendation-centric case study

• Full, data-driven support for any geopolitical context

Leave out of ASABE

7th Asian-Australian Conference on Precision Agriculture

New Zealand, Oct. 15-18

TBD; targeted toward communicating the value of a regional AgGateway. Poster and Oral?