Architecture of Agropedia, paper published in IEEE Internet Computing, Vol14, Issue-5 Abstract: Due to a lack of precise and exact terms of reference, the Internet features very little content related to agriculture. Agropedia, one of the world's first agricultural knowledge repositories built from semantic, collaborative, and social networking metaphors, bridges this gap via agricultural knowledge models. Creating vibrant and diverse communities requires careful planning as well as an open, yet flexible, protocol. Agropedia, through its peer-reviewed scientific content contributed by agricultural research institutions and its community-generated interactive folk knowledge, brings together the expert community and the user community.

1. web extra
Collaboration
Architecture of the Agropedia
Platform: Creating Content
and Community through
Collaboration
Nagaraju Pappu, Canopus Consulting
Runa Sarkar, Indian Institute of Management, Kolkata
T.V. Prabhakar, Indian Institute of Technology, Kanpur
Due to a lack of precise and exact terms of reference, there is very little content related to agriculture on the Internet.
Agropedia, one of the world’s first agricultural knowledge repositories built from semantic, collaborative, and social
networking metaphors, bridges this gap via agricultural knowledge models. Creating vibrant and diverse communities
requires careful planning as well as an open, yet flexible, protocol. Agropedia, through its reviewed, scientific
content contributed by agricultural research institutions and its community-generated interactive folk knowledge,
brings together the expert community and the user community. An excerpt of this work appears in IEEE Internet
Computing’s September/October 2010 issue.
M
ost of India’s workforce is tied to the ag- state universities, and research organizations have come to-
ricultural sector, which faces unprec- gether to support and promote knowledge exchanges between
edented challenges. On one hand, eco- different stakeholders in the agriculture domain. Agropedia
nomic growth, the rise of the middle class, is the result of this ongoing effort. While building Agrope-
and population increases have raised de- dia, we recognized that there isn’t much agricultural content
mand for food production by several or- on the Web—even on Wikipedia, of the more than 2 million
ders of magnitude, and on the other, changing climatic pat- articles available, only about 3,000 relate to agriculture. Ag-
terns, depletion of natural resources, overexploitation of ropedia is an attempt to fill this gap. It’s unique in many re-
farmland, and general deforestation have caused an unprec- spects: first, it’s the result of a consortium of institutions and
edented shortfall in agricultural production. Unfortunately, universities that provide edited and reviewed expert content
there’s very little public awareness about these problems. and articles; second, it’s a way for expert content creators and
Recognizing the need to create a comprehensive knowledge ultimate target users (farmers) by allowing many different or-
dissemination platform, a consortium of ICT institutions, ganizations in between to collaborate, participate, and inter-
Unless otherwise stated, bylined articles, as well as product and service descriptions, reflect the author’s or firm’s opinion.
Inclusion does not necessarily constitute endorsement by the IEEE or the IEEE Computer Society.
S E P T E M B E R /OC TO B E R 2 010 © 2010 IEEE I E E E I n ter n et C omp u ti n g w e b e x t r a i

2. web extra
Linking and cross
referencing content Building semantic
indexes
Inserting ontological entities For
as links in the content
Content Content
transformation publishing
Crop Extensions
calendars Content Content to tags
For
acuisition access
Knowledge Discussions
Like Tools
models
Review and Ratings Blogs
Extension edit content Provides Like
materials Called Agrowiki
Interaction
Agropedia content Questions and
Gyandara
Create Called answers
Is Is a
Create Jandara
Explicit Collaboration and
Is
knowldge social networking spaces
Community Community Tacit knowledge
Bridging the gap between
of experts of users
Input and
product markets
Include Include
Extension Call center
education units Extension Agri- operators
Traders
workers scientists
Krishi Vigyan
Kendras
Agriculture From From
research services Farmers Students NGOs
Village knowledge State agriculture Agriculture
centers universities research institutes
Figure 1. Agropedia is a network of communities. These communities range from agricultural universities supplying edited, reviewed
content to village-level extension workers supplying field-level information.
act. To accomplish such collaboration at a large scale, Agrope- in Figure 1. It aspires to be a one-stop shop for any informa-
dia uses knowledge models (a simplified ontology) to serve as tion related to Indian agriculture—an audio-visual encyclo-
a precise vocabulary of communication, which is very similar pedia designed to transform the process of digital content
to the efforts in fields such as medicine but a first of its kind in creation and organization by making it an enchanting educa-
the agriculture domain. tional experience.
Agropedia differs most from the Wikipedia model in its use The two most important dimensions of Agropedia are its
of inherent semantic indexing capabilities and authorized con- content and its community, which are intertwined in many
tent. Wikipedia also lacks the mechanisms for the end user ways. Agropedia’s expert community consists of individuals
community (people interested only in using and reading the or organizations engaged in agricultural research and knowl-
content) to participate in the feedback and content enrichment edge dissemination, such as state and central agricultural uni-
process. Likewise, some of the more common ontology-driven versities, research institutions, extension workers, research
semantic content systems don’t provide for collaboration or stations, and so forth. Its user community primarily consists
community participation. of people at nodal- or village-level government agricultural
This article describes the experience we gained while creat- centers—call center representatives, students, farmers, trad-
ing this platform. An excerpt appears in print, in the Septem- ers, and so on.
ber/October 2010 issue of IEEE Internet Computing. Naturally, Agropedia’s content is also of two types: expert
sourced content and community-contributed interactive con-
Organization and Structure of agropedia tent. The Gyandhara, or expert, content is edited, reviewed,
Agropedia is “all things agriculture,” meant for anyone con- created, and maintained by the participating institutions. Ag-
nected with or interested in the agricultural domain, as shown ropedia also supports the creation and distribution of inter-
ii I E E E I n ter n et C omp u ti n g w e b e x t r a w w w.computer.org / interne t

3. web extra
active content called Janadhara (folk-stream) from anyone in guidance or information to that farmer. Similarly, a user such
the community through wikis, blogs, forums, questions and as an extension worker might want to summarize many ar-
answers, reviews, comments on articles, and content tagging. ticles or papers written by experts, connect such content to-
Agropedia allows content contribution by any member of gether, and synthesize it for common, general usage.
the national agricultural research system institutions in India Effective collaboration assumes absence of hierarchical au-
or anywhere in the world. It includes a wide range of content, thority structures and centralized power centers. One reason
including text, images, and multimedia elements such as au- why several attempts to build such socially significant systems
dio, video, or animations. have failed is because of the naïve assumption that anyone in
Agropedia also provides a flexible authoring environment the chain could produce something for the direct consumption
and tools for content acquisition, processing, and publishing. of the final, target end user. The semantics of collaboration
It consists of social and collaborative networking features such means that we must produce for our nearest neighbor. If ev-
as blogs, forums, wikis, questions and answers, content tag- eryone in the chain works for their nearest neighbor, we end
ging by users, commenting, and rating authors and content. up with a vibrant, participatory community that grows.
The lack of consistent terms of references for the agricul-
Content and Community Creation ture domain is perhaps the reason for the Internet’s dearth of
through Collaboration agricultural content. Precise and exact terms of reference are
Building a platform like Agropedia goes beyond technology a fundamental requirement for goal-oriented communication
and software: the primary challenge is to enable an environ- and interaction. Without such terms, it’s extremely difficult for
ment that allows a community to grow, organize itself, create a member of the community to take something from an expert,
its own content, and interact and collaborate using the underly- enhance it, add value to it, and pass it to someone the next level
ing content repository as the primary vehicle of collaboration. down in the chain. In other words, humanization of knowledge
As Clay Shirky noted, a community is very different from isn’t possible without a shared set of terms of reference.
an audience (http://shirky.com/writings/broadcast_and_com- Large-scale, content-rich systems in specialized domains
munity.html). Audiences can be built, but communities cre- such as medicine have used semantic networks and special-
ate themselves and grow. However, to develop they need an ized ontologies successfully (www.nlm.nih.gov/research/umls/
underpinning of a constitution—a way to govern themselves, documentation.html). For example, the UMLS’s role in the
facilities to create their own languages of communication and creation, use, and propagation of medical articles on the Inter-
interaction, and methods to recognize and reward contribu- net makes them accessible not only by experts but also by an
tions by members. At the same time, when the community be- ordinary user. Agropedia’s knowledge models take a big step
comes too large and too diversified, it loses its focus (http:// in this direction by contributing to a precise and exact agricul-
shirky.com/writings/group_enemy.html). The best way to deal tural vocabulary.
with this is to create a platform that serves not only as a com- IITK and FAO first developed a generic knowledge model
munity network but would also allow formation of networks for crops, which was then used as a baseline model for crop
of communities.1 knowledge models. Figure 2 shows a generic knowledge model
Another challenge to consider is the awareness and capa- and a specific crop ontology.
bility of the agricultural community in India to absorb, as- Knowledge models are used for a wide variety of applica-
similate, and work with a technology-assisted medium. The tions, from content tagging to automatic cross-referencing of
technology can’t become a barrier to participation—instead, it content to relationship discovery. V. Balaji and colleagues2 de-
should enable and encourage it, irrespective of the user’s tech- scribed in detail the process of how the agricultural knowl-
nical proficiency. edge models were created, their importance, and the various
applications built via those knowledge models.
Function and Role of Knowledge Models
The heart of Agropedia is its knowledge models (http://agro- The Function and Role of Folk Knowledge
pedia.iitk.ac.in/?q=content/knowledge-models), which agri- We expect that the interaction space provided through the
cultural scientists and experts from participating institutions Janadhara stream will ultimately make it possible for the com-
created as a set of concept maps (http://cmap.ihmc.us/concept- munity to humanize the “expert” knowledge and make it more
map.html). These knowledge models are Agropedia’s lingua accessible for general, common use. In particular, it can help
franca. In the early stages of development, we quickly real- add practical, field-level examples, case studies, and enhance-
ized that a large-scale content creation effort for use by a di- ments to the main expert content. It’s also possible for users
verse community would require its own language of commu- to link content via their own user-defined tag system, discover
nication. For example, a paper or article written by a scientist content in the repository, use the expert content as a primary
wouldn’t be directly relevant to a farmer—however, it might reference material to illustrate specific issues for farmers, and
be useful to a person working in the agricultural research sta- keep the content alive and the community vibrant.
tion or an extension worker who needs to provide essential Lasting communities make up and transmit their knowl-
SEPTEMBER/OCTOBER 2010 I E E E I n ter n et C omp u ti n g w e b e x t r a iii

4. web extra
Nitrogen
Primary_nutrient is a Phosphorous
Seed_and_sowing Potassium
are Secondary_nutrient
Field_preparation Water_management
Essential_plant_nutrient Micro_nutrient
usesProcess
makeUseOf Organic_manure
Nutrient_management are IPNM makeUseOf Biofertilizer
Production_technology
Fertilizer
Crop hasProductionPractices Crop_weed_competition
Protection_technology causes Grass_weed
makeUseOf Weed are Sedge_weed
isManagedBy Broad_leaf_weed
Cultural_weed_control
Disease
Insect_pest Weed_management
Chemical_weed_control
usesProcess
Biological_weed_control
Mechanical_weed_control
Figure 2. Each crop has its own specific knowledge model. All the crop knowledge models use the generic crop model.
edge, culture, and values using folklore, which is the basic idea intuitive and nonintrusive. Many agricultural scientists, re-
behind the Janadhara. As Ananda Coomaraswamy pointed search workers, and government officers don’t understand the
out, 3 “folk tradition is ‘folk’ only in respect to its transmis- complexities of modern software. Moreover, many of them
sion, not its origin. Folklore and Philosophia Perinnis spring don’t have a high-speed, always-on connection to the Internet.
from a common source.” Therefore, we designed content submission to be extremely
easy and nonintrusive. Any authorized member can submit
Inclusion and User-Centric Design content via email or through the website in any format. A
The Nobel Prize-winning economist Amartya Sen described small back-office IT staff accepts this content and runs the
the economic, social, and cultural value of SwIkriti4 as a cul- content transformation tools. The transformed content is then
ture of openness, tolerance, and inclusion. SwIkriti basically presented to the original author, who can make any necessary
means that everyone, irrespective of his or her capacity, has a modifications, change links, cross-references, and ontological
place, function, and role. This is one of the central community entities, add or modify the tags, and so on. The original con-
building principles behind Agropedia. Here, we describe how tent and all subsequent transformations are preserved so that
we used this simple principle to make crucial design choices. the entire process can be repeated to generate the final content
view at any time.
The Knowledge Model Creation Process
The platform and toolset must be designed such that they don’t The Content Transformation Process
demand a sharp learning curve by the user community (be it The most successful software in the world hides its complex-
composed of content creators or users). While designing and ity—for example, just imagine the complexity that Google
creating the knowledge models, we introduced simple graphical hides behind one simple text box. Successful software design-
tools like concept maps (CMAPs), which are easy and fun to ers intuitively understand that the application and its “fea-
use. In fact, the agricultural scientists weren’t even aware that tures” shouldn’t be conspicuous. The software should present
they were making ontologies. The underlying platform was de- what the user needs and wants—content, community, and col-
signed in such a way that it converts the CMAPS to internal se- laborative environment—not menus, application buttons, help
mantic indexing schemes. We conducted simple workshops and screens, complex search, and navigational layouts. Thus, the
designed a few guidelines5 on what makes good concept maps, Agropedia interface presents only content to users; its func-
which is all that was required to generate the knowledge models. tionality is presented in the form of embedded links and navi-
gation in content elements, much like present-day Web 2.0 ap-
The Content Acquisition Process plications such as LinkedIn, Orkut, and Facebook.
We designed Agropedia’s content acquisition process to be Agropedia’s underlying architecture decouples content au-
iv I E E E I n ter n et C omp u ti n g w e b e x t r a w w w.computer.org / interne t

5. web extra
thoring from content publishing. As mentioned earlier, the
Content as required Simple tools or Transformation System APIs, user
content must be transformed using automated or semiauto- from experts manual process tools user input generated content
mated tools so that it becomes useful for the final end user.
Repository
Editing, language
E
Ed Content
Original
nal End user
Figure 3 shows the content transformation model. Submit- correction
co cross-linking
generated
content
ted content is checked into the main content repository in the Ba met
asic me
Basic metadata, bookmarks
aut
author, sou
our
source,
user’s original format. Automated tools then convert it into Converted to categories
ed t
Navagational links
for ontological Comments
Agropedia canonical format (an XML representation of the
Content processing
nt
standard content
entities
content). Then, the content is parsed and the relevant onto- format—XML/TeX
team (BPO)
User-defined tags
logical entities and relationships are automatically inserted as
Publishing User rating
navigational links. In the final step, the content is cross-linked Author
information
Ca ory
Category
ry
information information
rma
rmation
m
in the repository. date stamp Discussions
System at
Content Access, Community Building, and Web 2.0 Content System Content Content as
ent C
nt
run time
Track
usage backs generated indexes seen by an
The content’s state of readiness, its author’s information, staistics rating Agropedia
whether it’s reviewed or under review, and its status are shown user
as part of the content (similar to Wikipedia). Along with this
information, the user community can also rate the content— Figure 3. The content as acquired goes through several automatic
how many people have accessed the content and its author’s and semiautomatic transformations. The user only see the enriched
standing are all shown as part of the content’s attributes. and cross-linked content.
This model accomplishes many community building objec-
tives: specifically, it lets the community be aware of the most
useful content, and it encourages positive reinforcement and Web servers, front-end caching, CDN functionality
feedback to the authors. Temple engine, UI generation
Application components
Blog, discussion forum, chat, rating, profile management,
Agropedia Technology contact management, messaging
Agropedia is built on open source platforms and is completely Access control Tracking and Content caching Search engine
open source itself. We realized that its main assets aren’t the /user management statistics mechanisms functionality
technology and software but its content and community. User information Usage statistics Content element
Indexes
data store data store data store
Therefore, our primary architectural goal was to design Ag-
Content delivery environment
ropedia to scale to large amounts of content and a very large
and diverse user base. Most importantly, it was crucial that User interfaceto manage Authentication,
transformation workflow access control management
we keep the content’s lifetime high. In general, content out-
Content format Content cross-linking
lasts people and even the tools used to create it. This is why Indexers
transformation and tagging engine
we chose an open source platform so that content isn’t locked SVN-based content Content element Knowledge models
repository data store data store
up in “technology.”
Interfaces for content submission:
Many applications that use vendor-specific storage formats file upload, webDAV, Email. scanner/OCR
end up paying recurring license costs just to access content. Content authoring/transformation environment
Locking content formats to any particular representation or
choosing binary/proprietary formats aren’t useful in the long Figure 4. Agropedia’s layered architecture. The content acquisition,
run. We adopted an open content representation approach transformation, and indexing are separated from the content
that let us use a metarepresentation scheme like Tex, SGML, presentation and user model
and Docbook to preserve semantic structures and typesetting
information. This is equivalent to the content being stored as
a program plus data, which enables us to produce documents can also tag the content and design their own tags to group
conforming to various formats and standards at runtime. content together, meaning Agropedia can support both taxon-
To make Agropedia scale to serve a very large end-user omy-based navigation as well as folksonomy-based navigation.
base, we decoupled the back end, content authoring, editing, Figure 4 shows how the content transformation tools take
and transformation environment from the content access ap- the original content and insert ontological entities and rela-
plications. This allows deployment of the content databases tionships, cross-links to other content, and so on.
on multiple machines and locations using content delivery net- The knowledge models, ontological entities, and relation-
work (CDN) strategies. ships can be queried by using a simple API. We developed pre-
The entities and relationships in the knowledge models sentation plugins and themes as presentation services on top
link up the content and index it under all applicable concepts, of the Drupal Environment, which is an open source content
which serve as basic expert-generated navigational aids. Users management system.
SEPTEMBER/OCTOBER 2010 I E E E I n ter n et C omp u ti n g w e b e x t r a v

6. web extra
A
OPAALS_IITK%201.pdf.
gropedia is a unique effort in the sense that it’s a col- 2. S. Patwar et al., “Towards a Novel Content Organisation in Agriculture
laborative effort between many different institutions Using Semantictechnologies: A Study with Topic Maps as a Tool,” Int’l J.
Metadata, Semantics, and Ontologies, vol. 4, no. 1–2, 2010, pp. 65–71.
and organizations. It’s also unique from a technologi-
3. A.K. Coomaraswamy, “Nirukta = Hermeniea,” Perception of the Vedas,
cal and community-enabling point of view. It took us more V.N. Misra, ed., Manohar Publishers, 2000, Chapter12.
than two years to create the agricultural knowledge mod- 4. A. Sen, “Inequality, Instability and Voice,” Argumentative Indian, Pen-
els and the fundamental vocabulary. Currently, we’re in the guin Books, 2005, Chapter 2.
5. M. Sini et al., “Building Knowledge Models for Agropedia Indica v 1.0
evangelizing stage. The content transformation and automatic Requirements, Guidelines, Suggestions,” Indian Institute of Technology,
cross-linking environment is still under beta. We plan to con- 2008; http://agropedia.iitk.ac.in/?q=content/knowledge-models.
vert the knowledge models into a full-fledged ontology such
that automatic discovery and inferencing applications can be Nagaraju Pappu works as chief technologist at Canopus Consulting,
developed. We plan to use Subversion as the back-end content an enterprise architecture consulting services organization. He’s
repository, which allows multiple people to edit, modify, and also a visiting faculty member at IIT-Kanpur and IIIT-Hyderbad.
check-in the content even in an offline mode. Pappu specializes in large-scale enterprise systems architecture
In Agropedia, the intelligent fusion of cutting-edge comput- and semantic and collaborative environments. Contact him at
ing metaphors and collaborative culture is creating a simple yet pnr@canopusconsulting.com, or via www.canopusconsulting.com.
silent symphony. Its social and economic relevance to a country
like India, which faces major food production and distribution
challenges in the coming decades, simply can’t be overstated. Runa Sarkar is currently a faculty member in the economics group
at the Indian Institute of Management, Calcutta. Her research in-
Acknowledgments terests are digital ecosystems and the environmental sustainabil-
The Agropedia is the result of an ongoing effort under the umbrella ity and social economic impact of ICT on communities. Contact
of the National Agriculture Innovation Project (NAIP) of the Indian her at runa@iimcal.ac.in or via www.iitk.ac.in/ime/runa/.
Council of Agricultural Research (ICAR). IIT-Kanpur is building the
overall technology, with ICRISAT being the primary coordinator and
GBPant Agricultural University and University of Agricultural Scienc- T.V. Prabhakar is a professor of computer science at the Indian
es, Dharward acting as domain partners. Food and Agriculture Orga- Institute of Technology, Kanpur. His research interests are da-
nization (FAO), Rome, participated in building the knowledge models. tabases, software architecture, knowledge modeling, Semantic
We’re particularly grateful to V. Balaji, Johannes Keizer, Margherita Web, and collaborative computing. Contact him at tvp@iitk.ac.in
Sini, Antonella Picarella, and N.T. Yaduraju of these organizations or via www.cse.iitk.ac.in/users/tvp/.
for the help and encouragement they rendered in building Agropedia.
OPAALS, a network of excellence project under FP6 of the European This Web extra accompanies the article, “Agropedia: Human-
Union, also influenced the roadmap for Agropedia through its focus ization of Agricultural Knowledge,” IEEE Internet Comput-
on open knowledge systems. ing, vol. 14, no. 5, 2010, p. 57–59; http://doi.ieeecomputer
society.org/10.1109/MIC.2010.109.
References
1. R. Rajagopalan and R. Sarkar, “Digital Ecosystems: Community Net-
works or Networked Communities?” Proc. 1st Open Philosophies for
Associative Autopoietic Digital Ecosystems (OPAALS) Conf., Tampere Selected CS articles and columns are also available for
University of Technology, 2007; http://opaals.iitk.ac.in/deal/other/ free at http://ComputingNow.computer.org.
Engineering and Applying the Internet
IEEE Internet Computing reports emerging tools,
technologies, and applications implemented through the
Internet to support a worldwide computing environment.
For submission information and author guidelines,
please visit www.computer.org/internet/author.htm
vi I E E E I n ter n et C omp u ti n g w e b e x t r a w w w.computer.org / interne t