IEEE Conference on Technologies for Homeland Security (HST ’12)

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Recently I attended the twelfth annual IEEE Conference on Technologies for Homeland Security (HST ’12), held right here in our neck of the woods, Waltham, Massachusetts. The conference aims to bring together innovators from leading universities, research laboratories, Homeland Security Centers of Excellence, small businesses, system integrators and the end user community to provide a forum to discuss ideas, concepts and experimental results. I gave a poster presentation on our Semantic Technologies for Civil Information Management in Complex Emergencies within the Attack and Disaster Preparation, Recovery, and Response area, as well as gave a paper presentation on our development of A Social Agent Dynamic Honeynet for Attack Modeling within the Cyber Security track. Both presentations generated lively debates and discussions on the challenges of applying technology solutions these problemspaces. 

With regards to our social agent honeynet research, here we were presenting initial findings from an effort to develop an agent based dynamic honeynet that simulates user interactions with social networks for the purposes of developing attack models. You can check out our demo here. Our solution allows security professionals to create networks simulating user activity for companies and government entities through the provision of a set of parameters. Our research pointed to the importance of instantiating a social dimension to our virtual agents, providing the agent with the ability to interact with a variety of social networks. For this purpose, we developed influence models to learn patterns from actual users’ activity on social networks to improve the effectiveness of the social agents.

One of the questions from the audience was why use agents to collect attack data when regular users in the course of interacting with social networks get attacked enough as it is? Our response was that a deception network enables us to feed false information to the adversary as needed, track adversarial movements to learn attack patterns and attributes, and use the information collected during the attempted infiltration for the purposes of building more robust defenses and developing more targeted offensive operations. Additionally, deception networks force our adversaries to expend resources attacking our fake network. Another line of questioning asked if we were wasting people’s time who decided to follow our fake agents since about 50% of the followers of our agents were real and 50% were found to be malicious. This generated a lively debate, whereby someone else in the audience responded with the idea that identifying these people might be useful for preventative defense. Maybe these are people who are more vulnerable and would be more likely to click on spam and that perhaps Twitter or others might want to know this. A further question had to do with how do we know that the users following our agents are malicious? This is fairly straightforward because the users attempted to pass us links that are associated with known bad actors. As a future effort we plan to automatically parse the tweets and see if the embedded links are already in a black list which would trigger alerts. We maintain what we believe to be the world’s largest intelligence database on botnets to cross-reference our malicious entities as well. You can check out that project here.  

There were several ideas that came out of the collaboration at this conference related to our agents. One idea was to use our agents to collect and harvest social media artifacts for the purpose of understanding Arab Spring-like events. Additionally, our agents could potentially interact with users to explore the shaping of opinion, collaborating with users beyond just posting information to Twitter and following other users. We will definitely be exploring these avenues in the near future, so keep your eyes peeled for developments in this space.

One of the most interesting presentations I attended was from Laurin Buchanan of Secure Decisions who was involved in the CAMUS project, Mapping Cyber Assets to Missions and Users. This project was very relevant to our Commander’s Learning Agent (CLEARN) and Cyber Incident Mission Incident Assessment (CIMIA) work, which is an existing capability developed as part of an AFRL SBIR Phase II Enhancement that automatically learns the commander’s mission while bringing contextual knowledge and assigning priorities to resources supporting the commander’s mission in Air Operations planning and execution support. CLEARN/CIMIA monitors the workflow of operations personnel using Joint Operation Planning and Execution System (JOPES), the Air Mobility Command (AMC) Global Decision Support System (GDSS), Consolidated Air Mobility Planning System (CAMPS), and Global Air Transportation Execution System (GATES) to learn the resources necessary for each mission, and recommend workarounds when one or more the resources become unavailable.

Our semantic wiki work also generated interest during the poster session. One presentation that was interesting and tangentially related was SPAN (Smart Phone Ad Hoc Networks) by MITRE, which utilizes mobile ad hoc network technology to provide a resilient backup framework for communication when all other infrastructure is unavailable. I thought it was pretty neat that this was also an open source project. This research was interesting given our work in using mobile devices for data collection in austere environments during operations and exercises in the PACOM AOR in our MARCIMS (Marine Corps Civil Information Management System) project. Pretty cool to see all of the developments in this area.

SemTechBiz 2012

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I attended SemTechBiz 2012 in San Francisco last week. This annual conference on semantic technology, which is in its eight year, does a nice job in balancing the interests of research vs. commercial communities. This year the conference was tilted towards commercial vendor interests after all the vendors do sponsor the event although the product pitches were confined to a clearly identified solutions track. Here are my semantic annotations about this semantic technology conference.

Given our focus on open source platforms, I enjoyed the session on wikis and semantics. In this session, Joel Natividad of Ontodia gave an overview of NYFacets - a crowd knowing solution built with Semantic Mediawiki. Ontodia's site won the NYC BigApps - a contest started by Bloomberg as part of his grand plan to make NYC the capital of the digital world. NYFacets has a semantic data dictionary with 3.5M facts. Ontodia's vision is to socialize data conversations about data, and eventually build NYCpedia. I wondered why public libraries don't take this idea and run with it: Bostonpedia by Boston Public Library, Concordpedia by Concord Public Library and so on.

Stephen Larson gave an overview of NeuroLex - a periodic table of elements for neuroscience built with SMW under the NIF program. They built a master table of neurons and exposed as a SPARQL end point with rows consisting of 270 neuron classes, and columns consisting of 30 properties. NeuroLex demonstrates the value of a shared ontology for neuroscience by representing knowledge in a machine understandable form.

In the session - Wikipedia’s Next Big Thing, Denny Vrandecic, Wikimedia Deutschland gave an overview of Wiki Data project, which addresses the manual maintenance deficiencies of Wikipedia by bringing a number of the Semantic Mediawiki features to its fold. For instance, all info boxes in Wikipedia will become a semantic form stored in a central repository eliminating the need for maintaining the same content duplicated on many pages of Wikipedia. Semantic search capability will also come to Wikipedia to the applause of folks who maintain Wikipedia list of lists, list of lists of lists by replacing these manually maintained huge lists with a single semantic query. One of the novelties of Wikidata that it will be a secondary database of referenced sources for every fact. For instance, if one source says the population is 4.5M while another says 4,449,000, each source will be listed in the database, thus enabling a belief based inference.

It was nice to see several evangelists of linked data from the government sector at the conference. Dennis Wisnosky, and Jonathan Underly of the U.S. Department of Defense gave a nice overview of EIW Enterprise Information Web. It was refreshing to hear that DoD is looking at linked data as a cost reduction driver. Given the Cloud First mandate of the Defense Authorization Act 2012, the importance of semantic technology in the government will accelerate. In another session, Steve Harris of Garlik, now part of Experian gave an overview of Garlik DataPatrol - a semantic store of fraudulent activities for finance. I could not help wonder if someone from the Department of Homeland Defense was in attendance to hear the details of this application. Steve found no need for complex ontologies, reasoning, and NLP in this large scale application, which records about 400M instances of personal information (e.g. Social Security Number mentioned an IRC channel) every day.

Matthew Perry, and Xavier Lopez of Oracle gave an overview of OGC GeoSPARQL Standard, which aims to support representing and querying geospatial data on the Semantic Web. GeoSPARQL defines a vocabulary such as union, intersection, buffer, polygon, line, point for representing geospatial data in RDF, and it defines an extension to the SPARQL query language for processing geospatial data using distance, buffer, convex hull, intersection, union,envelope, and boundary functions.

Linked data being essentially about the plumbing of semantic infrastructure, it is hard to give engaging presentations on this topic. Two presentations bucked this trend. The presentation by Mateja Verlic from the Slovenian startup Zemanta rocked. Zemanta developed a DBpedia extension - LODGrefine for Google Refine under the LOD2 program. Google Refine supports large transformations of open source data sources, and LODGrefine exposes Refine results as a SPARQL endpoint. Mateja managed to give two impressive live demoes in ten minutes. The other rock star presentation was by Bart van Leeuwen - a professional firefighter, on Real-time Emergency Response Using Semantic Web Technology. Everyone in attendance got the gist of how FIREbrary - a linked data library for fire response, can help firefighters in the real world with a presentation sprinkled with live videos of fire emergency responses. It was instructive to see how semantic technology can make a difference in managing extreme events such as a chemical fire as there are no plans by definition for these types of events.

Bringing good user interface design practices to linked data enabled applications was another theme of the conference. Christian Doegl of Uma gave a demo of Semantic Skin, which is a whole wall interactive visualization driven by semantics. Siemens used it to build an identity map of their company. It uses Intel Audience Impression Metrics Suite to detect the age gender, etc. of the person walking in front of the wall for personalization of content driven by semantics. Pretty cool stuff.

MARCIM Semantic Wiki News - May 1, 2012

The following is the second installment of our MARCIM Semantic Wiki Newsletter, sent May 1, 2012 to those involved in the MARCIM technology demonstration. If you are interested in being added to the mailing list for these newsletters, please email Lmooney@milcord.com.  

Semantic Wiki News - May 1, 2012

Hello,

Our participation in Balikatan 2012 exercises within Palawan, Philippines reinforced many lessons learned during Cobra Gold 2012, as well as elucidated fresh insights that have inspired our team's evolution of the Semantic Wiki.  We look forward to keeping the team updated on the exciting progress being made through this MARCIM Semantic Wiki Newsletter. We kept the distribution of the newsletter to individuals directly involved in the project; please let us know if there are others we should include in the mailing list!

The following features have been implemented in the Semantic Wiki since our participation in Balikatan 2012:

Event Calendar

In response to user feedback, we have taken our semantic Event Calendar (detailed in our last newsletter installment) a step further by allowing users to populate this calendar themselves via their mobile devices. Using the "Event" form within the mobile app, users may now enter the time, date, and details about a particular event. This data is automatically ingested into the Wiki, and placed upon a monthly calendar.

As you can see above, Balikatan users added information to these calendars about events such as barangay meetings, CMO operations meetings, VETCAP and MDVCAP outreach, and site dedication ceremonies. For users that choose to populate the calendar with events that are relevant only to their teams, we have created "Team Calendars" (such as the BK12 North Calendarwhich lists all activities being conducted by CA Team North). For operations personnel that desire an aggregate view of events, we've created calendars that contain all events (such as the BK12 Joint Medical Task Force Calendar which lists all MEDCAP and VETCAP related activities, irrespective of which teams are involved in the activity). The dynamic nature of this calendar serves to increase the quality of collaboration among the operational planning team and units in the field.

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Tabbed Site Pages

In the Philippines we observed that users found it difficult to search for site-specific information. This led us to recognize a distinct need to address ontological distinctions in the Wiki; that is, the need to draw sharper distinctions between Site pages, the schools that sites are associated with, ENCAP and MEDCAP activity that occurs at these sites, etc. As you can see from the screenshot for Buena Vista Elementary School, below, we have implemented tabbed site pages which address this issue. By having tabs for relevant data about the site (i.e. ENCAP Progress, ENCAP Description, School Information, and Village/Subdistrict Information), all the information that relates to a single site exists within the same page, so that accessing site-specific information is made increasingly intuitive for users.

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Since Cobra Gold 2012, we've introduced an enhanced tagging scheme for all photographs ingested from the mobile device. Included in this enhanced tagging scheme are coordinates, which allow us to geolocate photographs on a map, as can be seen on the Balikatan 2012 photographs page. This allows users to zoom into an area of interest within the map and view images that have been submitted.

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Internal Timer

During Balikatan exercises we identified a way to place content (such as charts, tables, pictures, or text) on an internal timer within the Wiki so that the content doesn't appear until a defined date. This keeps pages from being cluttered with information that either is not relevant, or doesn't exist, until a particular point in time. For example, the tables on the MDVCAP site pages aggregate and analyze the demographic data collected from MDVCAP patient registration (i.e. see the Cabayugan National High School Patient Registration Data). These tables, which don't have any information until the registration process begins, are now placed on timers so that they appear when registration commences.

We are excited about this solution as it increases the practicality and sustainability of the Wiki, and allows us to feed users semantic reports and other content when we know they'll need them. These timers can be customized down to the very second that the user needs the designated content to appear.

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Multidimensional Dynamic Graphs

Before discussing the innovation in our enhanced dynamic graphs, we'll first delve into some Semantic Query 101. The semantic reports (i.e. tables, charts, calendars, etc.) that you see within the Wiki go beyond simple analysis that can be completed in Excel; they're unique because every time you visit, the reports are created anew for you. They refresh every time you visit the page in which they are embedded. The reports can be automated in this way because every page within the Wiki (i.e. every assessment, every school site, every village) is tagged using a "subject, property, object" semantic annotation format. For example, Bangkok (Subject) has a Population (Property) of 8,300,000 (Value). Because of the way the data is structured, we are able to explore relationships between and among Wiki pages. This allows us to ask the database questions and receive answers (such as, what is the population of Bangkok?).

In constructing more complex reports, we need to conduct searches for properties that are semantic queries in and of themselves. In such reports, the information we need is not tagged within the pages, but by nesting a semantic query as a property value, we can infer knowledge from the other semantic relationships that exist. We used this logic to create the ENCAP progress graph (below) which you can view on the BK12 Engineering Civic Action (ENCAP) Activity page. Behind this graph is a semantic query that is asking the Wiki to deliver the most recent Percent Completion rate entered within the SITREPs for all ENCAP sites. This is a query within a query, as we are delving into the multidimensional semantic relationships that exist, rather than the tags within the page, to deliver this information.

This is a galvanizing development as it demonstrates that our visualizations and reports can be enhanced to drill down into multiple dimensions of the data, querying for relationships nested among other relationships, to derive insight and produce refined visualizations that provide value in operations.

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Usage Statistics

To track usage of the Wiki over time, we have created a MARCIM Semantic Wiki Statistics page. This page dynamically tracks aggregate statistics (i.e. number of views, edits, and assessments), and well as statistics by operation (i.e. how many new user accounts were created for Cobra Gold v. Balikatan? How many photographs were ingested? How many assessments were ingested; and how many of these were medical assessments in either exercise?). The page also contains a dynamic bar chart that tracks user account creation over time, and dynamic pie graphs which detail the number of assessments completed by operation.

Below are some interesting statistics as of May 1, 2012:

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We hope you found the second installment of our Semantic Wiki Newsletter useful, interesting, and relevant. We value your feedback on how we can improve our updates.

Sincerely, The Milcord team

MARCIM Semantic Wiki Newsletter - March 9, 2012

The following is our first MARCIM Semantic Wiki Newsletter, sent March 9, 2012 to those involved in the MARCIM technology demonstration. If you are interested in being added to the mailing list for these newsletters, please email Lmooney@milcord.com.  

Semantic Wiki News - March 9, 2012

Hello,

Annotated content for 946 Thai and Philippine NGOs, dynamic calendars for Balikatan, and automated BMI calculations: these are a few of the changes that have been made to MARCIM Semantic Wiki this week! The Milcord team has been working to address user requirements observed during Cobra Gold 2012 and implement innovative solutions, so that the second deployment of our MARCIM Semantic Wiki within the Philippines will met with increased success. In order to keep the MARCIM team apprised of solutions as they're employed, we hope to begin communicating new updates through this bimonthly newsletter. We kept the distribution of the newsletter to individuals directly involved in the project; please let us know if there are others we should include in the mailing list!

The following updates have been implemented within the Wiki in the past week:

Balikatan Calendar

In an attempt to address reporting requirements identified by users in Thailand, we have created a dynamic calendar labeled with important events for Balikatan 2012. The monthly calendar view is one of many export formats enabled by the Semantic Search capability. The calendar can be accessed here.

As you can see, the calendar posts we've created include dates for deployment and redeployment, opening and closing ceremonies, as well as Medical/Veterinary Outreach, among other events. To add an event to the calendar, a user may click "Add page using form" in the left sidebar, type the name of the event he/she desires to post within the text box that appears, and within the dropdown menu choose the category "Event." The event the user creates will automatically populate to the calendar.

It is our hope that this calendar will support staff reporting functions in Balikatan, and serve to increase the frequency and quality of collaboration among the operational planning team.

What Links Here Template

As part of an ongoing effort to enable automatic associations between annotated non-page entities in the Wiki, we have created a template that allows users to generate a bulleted list of pages that link to any given tag. Let's take an example that was presented to us by a user in Thailand. Many teams working at the MDVCAP sites consistently mentioned "diabetes" as an issue within their SITREPs. Any tags to diabetes created red hyperlinks; however, even if the user created a page for "Diabetes" the page itself would not generate an easily viewable list of pages with mentions to Diabetes. We've addressed this issue by allowing users to embed a template within the free text area of the page in question. By typing {{What Links Here}} within the text of a Wiki page, a list of pages with tags to diabetes will be generated. For further exploration, navigate to the Diabetes page.

After a single user inputs {{What Links Here}} within the free text area of the page, every user thereafter will be able to view a list of pages that link to the tag in question.

BMI Calculations

We have codified a process for dynamically calculating Body Mass Index statistics for every patient that passes through Medical Registration at a MEDCAP Site, in response to feedback from the Environmental Health Officer for Iii Mef. Aggregate BMI statistics now automatically feed into our dynamic tables located within MEDCAP Site pages. To view the new dynamic tables, follow the Cobra Gold Site 1 link.

New Sociocultural Content

In preparation for Balikatan we completed data ingest of all major geographic divisions for the Philippines (to include regions, cities, and municipalities). We have also imported 422 Philippine NGOs, and 524 Thai NGOs to satisfy user requirements. Sociocultural content may be accessed from both the Philippines and Thailand country pages.

In addition, all site information for Balikatan currently resides on the Semantic Wiki. You may view this content within the Balikatan 2012 operation page. Below is a screenshot of the Site page for the Tagbarungis Elementary School, an ENCAP Site in Palawan.

 

Main Page Restructuring

We have integrated feedback from users and MARCIM team members to restructure our Wiki Main Page. We now have content divided by Operation/Exercise, and by Area of Operation - the latter of which is particularly designated for ongoing operations not associated with a specific exercise. Let us know what you think of our new Main Page.


We hope you found our first Semantic Wiki Newsletter contained useful, relevant information. We value your feedback on how we can improve our updates.

Sincerely, The Milcord team

Milcord Participates in Cobra Gold 12 Military Exercises in Thailand

From January-February 2012 Milcord participated in Cobra Gold military exercises in Thailand, demonstrating our MARCIM (US Marine Corps Civil Information Management) Semantic Wiki. This is the second year we have participated in the exercises; last year, Laura Cassani represented Milcord by presenting our sociocultural knowledge base. You can read Laura's post here for background on the exercises, and details about our participation in Cobra Gold 2011. Since then, we’ve developed another knowledge base built upon a Semantic Wiki platform, tailored to support the Civil Information Management needs identified in Thailand.

The MARCIM Semantic Wiki supports real time data collection, visualization, and analysis by automatically ingesting assessments and surveys conducted by Civil Military Operations (CMO) teams submitted via mobile devices, and semantically tagging and generating relationships with the field collected data. During Cobra Gold 2012, the MARCIM Semantic Wiki was placed in the hands of the exercise’s planning and operations team. This team, stationed at the CJCMOTF (Combined Joint Civil Military Operations Task Force) in Korat, Thailand, is responsible for overseeing all CMO activity within the country. I spent three weeks observing, interacting with, and supporting the users, and, based on their feedback, we customized the Wiki so that it could best assist and advance the efforts of CMO personnel. It was incredible to see how the Wiki evolved throughout the exercises from being something that was built on a conceptual level by Milcord to being a living, breathing tool that took shape around user feedback as we worked continuously to tailor the Wiki so that it could confer the utmost benefit to the troops. On a daily basis within the CJCMOTF, the staff used the Wiki to submit their daily reports, analyze demographic information within the area of operations, monitor team activity, and visualize responses to surveys and assessments.

During my time in Thailand, I gained an appreciation for the nature of the data collected during CMO missions; information is collected about the local infrastructure, medical needs of the population, progress being made at engineering sites, as well as sentiments of the Thai people toward the troops. Instead of placing this data onto inaccessible hard drives where it is unlikely to be utilized, the Wiki structures the data and places it into an analyzable form for users, thus presenting the value of the aggregated data to the troops. In addition to helping the troops understand the impact they’re making on the ground, the aggregation and analysis of this data also prevents duplication of effort by CMO teams by alerting them to what has already been achieved within the area of operation, and what activities and projects should be prioritized in the future.

Although our work within the CJCMOTF kept me busy, I was still able to sneak in some sightseeing. I visited the Weekend Market in Bangkok (the largest market in Thailand), toured the Royal Palace and Wat Pho, and visited Khmer ruins within Korat. The entire trip was a culinary escapade, and I quickly developed an appetite for som tam (spicy papaya salad with shrimp) and chai yen (Thai iced tea).

Since our participation in Cobra Gold 2012, we have been invited to participate in a number of other exercises, including Balikatan 2012 exercise in the Philippines, Pacific Partnership 2012 exercise in Southeast Asia and Oceania, and Black Sea Rotational Force 2012 operation in Eastern Europe. We look forward to posting further updates on the evolution of the MARCIM Semantic Wiki as we progressively gain insights from these operations and exercises!

Wiki Surveys for Social Science Research

Surveys and interviews form the central methodology for analyzing and discovering attitudes and opinions in social science research. With the advent of Web, online surveys have become an efficient way for researchers to collect and analyze large amounts of data. The popularity of the online survey tools like SurveyMonkey , Zoomerang, SurveyGizmo , etc. are testament to the productivity enabled by surveys. However, surveys represent a top-down rigid methodology forcing the survey designer to account for all possible answers up front, which is an impossible feat. In contrast, interviews allow the unanticipated information to bubble up bottoms up from the respondents. For instance, Integrity Watch Afghanistan (IWA), Afghan Perceptions and Experiences with Corruption: A National Survey 2010 primary data, involves interviewing randomly selected 6,500 respondents in 32 provinces on over 100 questions that deal with sectors where people experienced corruption; levels of bribes people paid to obtain services; what type of access people had to essential services; who people trusted to combat corruption; and experiences with corruption in the judiciary, police, and land management. However, the interview methodology is expensive and time-consuming as it requires implementation by research companies with expertise in effective research design, and precise management of data collection over several months.

Is there an alternative to surveys and interviews in social science research? Prof. Salganik's team at Princeton came up with a hybrid approach, "wiki surveys", that combines the structure of a survey with the open-endedness of an interview. To date, various organizations have created more than 1000 wiki surveys on the project Web site - All Our Ideas, generating in 45,000 ideas with 2 million votes. Wiki surveys range from the New York City Mayor's Office's engagement with citizens in shaping the city’s long term sustainability plan to the Catholic Relief Services surveying their 4000 employees to find out what makes an ideal relief worker. The figure below shows how the third question in Tactical Conflict Assessment Planning Framework (TCAPF) would be be implemented as a wiki survey:

tcapf wiki survey.jpg

Inspired by extending the kittenwar concept to ideas, the user interface guides the respondent to choose between two random alternatives, while encouraging the respondents to add their ideas into the mix of alternative responses. The additional ideas are added into the survey’s marketplace and voted up or down by the other survey-takers. Prof. Salganik says that “One of the patterns we see consistently is that ideas that are uploaded by users sometimes score better than the best ideas that started it off. Because no matter how hard you try, there are just ideas out there that you don’t know.”

All Our ideas have some basic visualization features to make sense of the wiki survey responses. Here is the visualization for the responses - "What do you think the Digital Public Library of America (DPLA) should be like?":

DPLA Survey Reponse.jpg

It is worth noting that the top scoring 15 ideas starting with DPLA interoperability with Government Printing Office (GPO), Defense Technical Information Center (DTIC), an National Records Archive Administration (NARA) are all uploaded ideas not in the original set of alternatives. A powerful argument for crowd sourcing!

Admittedly, we still need boots on the ground to collect TCAPF data in Afghanistan given the demographics of the people we want to reach. On the other hand, wiki surveys hold great potential in reaching the younger generation fueling the Arab spring and the like.

Tribal Human Terrain of Afghanistan

Under the sponsorship of the OSD Human Social Culture Behavior (HSCB) program, we are developing a semantic wiki for Complex Operations. The envisioned operational impact of our effort is to foster collaboration and sharing of knowledge for whole-of-government approach, and to improve COIN/SSTR operations analysis and execution by focusing on population as center of gravity. The development of such a wiki presents several challenges that include the broad domain area of knowledge complex operations require, a large number of doctrine publications to wikify and semantify, several out of print key references, etc. With these challenges, we saw an opportunity to develop an open source culturepedia for Afghan and Pakistan human terrain as such knowledge is not aggregated and not readily available.

The Complex Operations wiki currently contains more than 1,000 articles on the various tribal dynamics and locational knowledge for the Afghanistan and Pakistan region, outlining tribal meta-knowledge such as the sub-groups, primary locations, traditional alliances, and traditional disputes of various groups to support situational awareness about the human terrain. Here is the wiki page for the covered Afghanistan Organizational Groups. We have created over 150 concept maps (an example shown below) to capture the knowledge about 1,000 ethnic groups, tribes, sub-tribes, clans within Afghanistan and Pakistan region to make this human terrain knowledge readily accessible to the complex operations practitioner.

tribal concept map.png

Our use of a semantic wiki platform enables the representation of the human terrain knowledge as facts and relationships. For instance, the wiki page for the Achakzai tribal group lists the the known facts and relationships about this ethnic group both a human consumable form using semantic forms:

Achakzai Semantic Form.tiff

, and a machine consumable form as semantic RDF relationships:

Achakzai RDF.tiff

By inspecting the semantic form, the reader can deduce that Achakzai is a sub-tribe of Zirak, which is a sub-tribe of the Durrani super-tribe, primarily located in the Chora and Khas Uruzgan districts, and traditionally have disputes with the Nurzai, Panjpai and Kakar tribes. The representation of this knowledge in a semantic wiki has the additional advantage for faceted browsing and answers engine queries. For instance, the semantic wiki can answer questions like "What are the tribes in Kandahar Province and their traditional disputes?" as a table which gets automatically updated every time a new tribe in this province is added to the wiki: Tribes in Kandahar.tiff There are also several groups in Afghanistan that do not organize around tribal kinship ties, including Uzbeks, Tajiks, and Hazaras. In addition to tribal affiliation, social organizations such as solidarity groups - a group of people that acts as a single unit and organizes on the basis of some shared identity, and patronage networks - led by local warlord or khan - play an important role in understanding of the human terrain. Afghan and Pakistan human terrain and situational awareness knowledge base can be extended to include other populations of interest to the community, such as Yemen or Somalia.

Semantic Wikis for Communities of Practice

The term community of practice (CoP) was coined by Jean Lave, a social anthropologist. Its value in learning was popularized by Etienne Wenger, an educational theorist. CoP denotes a group of people who share a passion about a common topic, and deepen their knowledge and expertise in this domain by interacting with each other on an ongoing basis. According to Etienne Wenger, a community of practice defines itself along three dimensions and its characteristics can be captured by:

The domain. A community of practice is is something more than a social network. "It has an identity defined by a shared domain of interest. Membership therefore implies a commitment to the domain, and therefore a shared competence that distinguishes members from other people".

The community. "In pursuing their interest in their domain, members engage in joint activities and discussions, help each other, and share information. They build relationships that enable them to learn from each other".

The practice. "Members of a community of practice are practitioners. They develop a shared repertoire of resources: experiences, stories, tools, ways of addressing recurring problems—in short a shared practice. This takes time and sustained interaction".

In developing and nurturing Communities of Practice, Etienne Wenger talks about the diverse and distributed internal leadership:
• The inspirational leadership provided by thought leaders and recognized experts
• The day-to-day leadership provided by those who organize activities
• The classificatory leadership provided by those who collect and organize information in order to document practices
• The interpersonal leadership provided by those who weave the community's social fabric
• The boundary leadership provided by those who connect the community to other communities
• The institutional leadership provided by those who maintain links with other organizational constituencies, in particular the official hierarchy
• The cutting-edge leadership provided by those who shepherd "out-of-the-box" initiatives.
McDermott goes further and states learning is in the relationships between people:

Learning traditionally gets measured as on the assumption that it is a possession of individuals that can be found inside their heads… Learning is in the relationships between people. Learning is in the conditions that bring people together and organize a point of contact that allows for particular pieces of information to take on a relevance; without the points of contact, without the system of relevancies, there is not learning, and there is little memory. Learning does not belong to individual persons, but to the various conversations of which they are a part.

In the book Seven Principles for Cultivating Communities of Practice, Etienne Wenger, Richard McDermott, and William M. Snyder argue that while communities of practice develop organically, a carefully crafted design can drive their evolution. Here are the seven principles:
1. Design for evolution
2. Open a dialogue between inside and outside perspectives
3. Invite different levels of participation
4. Develop both public and private community spaces
5. Focus on value
6. Combine familiarity and excitement
7. Create a rhythm for the community
There is additional research on what makes online CoP's flourish. Jennifer Preece posits that etiquette, empathy and trust in communities of practice can be developed by understanding people’s needs; representing the community’s purpose clearly; putting minimalist policies in place that can be changed as norms develop; supporting knowledge creation, exchange and storage; supporting communication and socialization online; encouraging empathy by enabling participants to recognize each other and their similarities; supporting trust by ensuring that identity is revealed and past behavior is tracked.
In the paper Learning with Semantic Wikis, Sebastian Schaffert and his colleagues lists the benefits of semantic wikis in the learning process. First, they argue that semantic annotations lead to reflection about knowledge. For instance, the student needs to reflect on the content while reorganizing the wiki material. In fact, the teacher can assess the student's progress by analyzing the change history. Second, semantic Wikis enable the teacher and students to share formal models, and build of a common model collaboratively. Finally, reasoning and inference capabilities of Semantic Web technologies can lead to discovery of knowledge without active user search. In the paper Using a Semantic Wiki in Communities of Practice, Adil El Ghali and his colleagues articulate the advantages of adding semantics to wikis like semantic search and navigation, a more intuitive interface, intelligent awareness, tagging, folksonomy management, linking CoP content to external resources, etc.

The development of Communities of Practice is the charter of Army Knowledge Online. Here is a paper and related presentation that articulates the thrust in DoD. We are in the process of putting these ideas into practice in our Semantic Wiki for Complex Operations project.

Milcord awarded R&D contract under ONR HSCB program to develop Semantic Wiki for Complex Operations Community

Milcord, LLC. - WALTHAM, MA – Milcord LLC announced a multi-year award under DoD’s Human Social Culture Behavior (HSCB) Modeling Program to develop a semantic wiki for the Complex Operations community.  The HYKNOCO (Hybrid Knowledge Management framework for Complex Operations) project is funded by the Office of Naval Research under the HSCB Modeling Program.  Milcord is leading a team consisting of the Naval Postgraduate School, University of Maryland, University of California – Davis, and IAVO. About Milcord: Since 2003 Milcord has been delivering knowledge management technologies and solutions for a range of applications including cyber defense, human and social modeling, geospatial intelligence, and information management. Milcord’s federal customers include Air Force Research Laboratory, Office of Naval Research, Army Research Labs, Army Geospatial Center, Office of Secretary of Defense, Department of Energy, and NASA.  For more information see www.milcord.com.