collaborationinnovationInnovation Management

The Best Innovation Management Software Captures the Context of Ideas

Most innovation management software (a.k.a. innovation software) is focused on generating and curating ideas. Ideas are explicit. They’ve been articulated, inside your head at the very least. Implicit knowledge, the context of an idea, is where many big opportunities reside.

Revealing Hidden Context Creates an Opportunity in Public Health

A global health research foundation is trying to eliminate dengue fever. One team is experimenting with a bacteria, Wolbachia, that sterilizes mosquitos. Another team is researching the effectiveness of administering oral contraceptives for dengue to mosquitos.

Those are two explicit solutions, two ideas. Implicit in those ideas is a hidden but essential fact. Those solutions use the same delivery system.

Once those teams discovered what their projects had in common, they could collaborate by sharing information and experiment with joint implementation.

knowledge iceberg explicit tacit


Methodology is a Highly Transferable Form of Context

A climate scientist may be analyzing time-series data about global temperatures. The subject is temperatures. The methodology is time-series data analysis. Knowing that, the climate scientist can look to other fields that have advanced techniques for analyzing time-series data, e.g. finance or logistics, that might have complementary differences.

A geneticist was using a specialized data visualization to study brain disease. A religious studies professor was able to visualize ancient islamic text in similar visualization. DNA is letters, just like words. When the two researchers got together, they were able to exchange insight that led to further funding for the religious studies professor.

Mining Context is What Software Can do Well

Us humans can only maintain our focus on so many things at once. With data visualizationmetadatasocial network analysis, and the science of team science, innovation management software can reveal implicit knowledge that leads us to adjacent solutions.

The best innovation management software captures the context of an idea, i.e. the metadata. By making context visible, smart people can intermingle ideas and find ways to amplify the efficacy of their resources. They capture not just the ideas on their minds but the solution space in between.

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‘Translators’ as Contributors in Collaborative Teams

This post was authored by Alicia Knoedler of Exaptive and is reposted from

For 20 years, I have worked with researchers in academic settings to help them design, develop and obtain resources to support the research they do. Over those 20 years, I have cultivated relationships and developed partnerships to the benefit of these researchers, sometimes brokering relationships and other times developing partnerships on behalf of others. I am not advancing my own research or research interests. Instead, I am developing my own understanding of what others do with their research and communicating that understanding to other audiences. Knowledge transfer of this sort is somewhat common in academia, and in other sectors such as industry or non-profit organizations, this form of communication might also be referred to as marketing, storytelling, and/or knowledge mobilization.

translation in research development

In this post, I am identifying a nuance to this type of communication concept in research: translation. This term can apply to many different situations but is applicable to academia and research settings as an intellectual practice of learning information, weaving it with other information and context, and being able to communicate this “converted” content to a new and relevant audience that will readily understand the converted content but might not have understood the original learned information.

The Importance of Context

As a psychologist, observing, noticing, and relating are key components to studying and understanding behavior – and to telling stories. You don’t have to be a psychologist to develop these skills but it helps to have fundamental curiosity about behavior to be motivated to be constantly observing, noticing, and relating. Long ago, my research focused on how we remember things and the context that influences one’s ability to remember and remember accurately. I don’t actively research memory and context anymore, but context is still the most fascinating concept to me related to information processing, thinking, learning, knowledge transfer, and innovating.

standard dictionary definition describes context as “the circumstances that form the setting for an event, statement, or idea, and in terms of which it can be fully understood and assessed.” The word is derived from the Latin term contextus, con for “together” plus texere which is “to weave.” It is this aspect of context and the process of weaving things together that I am interested in applying to activities I and others commonly practice today: translating information and bridging knowledge gaps.

The Act of Translation

Translators are skilled at the sort of translation communication described above. Translators are not just taking information and repeating it elsewhere or connecting people to the information. They are enhancing and adapting the information with the context included. They consider the audience receiving the information and guide their understanding. Weaving and integrating content and context changes the perception of the understanding of the original information, which often allows that information to become applicable elsewhere. The translator notices how the information has relevance in a different context, which enables the translator to make connections, analogies, relevance and see applications that wouldn’t have been possible using the untranslated information.

The skills involved in translation communication can be learned but must be practiced. The skills of observation, noticing and relating are critical. Considering the audience, perspectives other than your own, and context are essential to translation. It is also important to be able to draw relevant connections and be comfortable with experimenting with loose connections. Taking risks and seeking relevance far beyond the most obvious or intended context is where the most interesting translations take place. It is likely that you know of people who are skilled translators. In discussions, they are easily recognizable because they hear what everyone else is hearing, but they have a keen sense of being able to explain the content differently and adapt it, especially if other listeners are having a tough time comprehending the original content.

Translating information that originates from a different source can be a challenge. Credit for the original information/idea remains with the owner of that information/idea. The translator isn’t seeking to own the origins of information or ideas. S/he is interested in mobilizing information to new situations. Translators share.They don’t usually own. And in fact, this is one of the challenges to being a translator.Translators have their own ideas and their contributions are most powerful when they apply their skills to helping other people’s ideas find relevance outside of the original idea. Translators are quick to give credit to the ideas’ original owners. But they aren’t just the messengers of other people’s ideas. Their ability to weave and integrate content and context is their unique contribution to enhancing the original idea and helping it broaden its relevance.

When I have shared this notion of a translator, especially in the context of research teams in academic settings in which ideas are protected and coveted, the notion of a translator is met with skepticism but mostly from individuals who are not translators. When I share the notion of translation with people who are doing it, they immediately recognize their skills and behaviors and often have a sense of validation that someone else perceives these skills and behaviors to be valuable.

The Difference Between a TranslatorFacilitator and a Knowledge Broker

Let’s imagine the following common scenario in academia.

We are in a team meeting.

An idea is presented and the “owner” of the idea has a particular way of presenting the idea. The way in which that idea is described could immediately resonate with the team members, especially if everyone has similar backgrounds and common knowledge about the content and ideas being discussed. But it also could be the case that some team members might not have similar training, backgrounds, or knowledge as the owner of the idea, and these members may not immediately connect with the idea. It is entirely possible that the meeting will continue and a gap will start to form between the members who understand the idea and those who do not.

translation in research development

In some team meetings, there may be individuals who participate with the express purpose of helping team members connect to one another and ideas. For example, a facilitator may participate on a team to create conditions in team meetings so that others feel welcome to provide their perspective on the ideas, and the facilitator ensures that the discussion is inclusive and equitable. The facilitator makes sure that the discussions can continue and that ideas are allowed to evolve or at least understanding around the idea can evolve. However, the facilitator doesn’t necessarily translate content around the ideas to make ideas more accessible. Instead, the facilitator’s role is typically to provide inclusive conditions so that the meeting can be productive around specified meeting goals.

In this same team meeting context, a knowledge broker might take the idea being presented, repeat it, invite other people to contribute to the discussion, relate concepts to one another, and possibly suggest the inclusion of other individuals and perspectives at future meetings. To borrow from Wikipedia: “A knowledge broker is an intermediary (an organization or a person), that aims to develop relationships and networks with, among, and between producers and users of knowledge by providing linkages, knowledge sources, and in some cases knowledge itself, (e.g. technical know-how, market insights, research evidence) to organizations in its network.” The knowledge broker’s role is to advance understanding and connect to the ideas being presented and to notice gaps or the potential for additional content and ideas to become part of the discussion. The role of the knowledge broker is to connect, rather than change or adapt the way the ideas are described and/or perceived.

translator as part of a research team discussion absorbs and adapts the original idea, the context in which it was presented, the tone of the meeting and reactions to the idea, different perspectives discussed around the idea, and additional behavioral cues from the participants and integrates all of this information and observations into a new perspective on the idea and how best it may be delivered for the remainder of the meeting or following the meeting. Having absorbed and integrated the content and context, the translator can now notice how and when this new perspective on the idea might be relevant to other ideas, in other contexts, other perspectives and the translator is capable of presenting this new version of the idea in a new context and/or to a new audience without the presence of the original owner.

There is definitely some nuance to these definitions and these roles. I am not intending to suggest that one role, facilitator, knowledge broker or translator, is better or more relevant than another role. They can be implemented in different situations for different outcomes. But what I do want to emphasize is the depth of integration and transformation of the information that a translator can apply to content and that this is a valuable contribution, especially to bridge knowledge gaps, broaden participation among team members, and enrich understanding and comprehension in a collaborative environment.

What is missing from this blog is an assimilation and translation of published work relevant to this idea of translation. I promise a future post summarizing and translating this research, because I think the translator role is critical to collaboration and an often overlooked contributor. I welcome your thoughts, reactions, and suggestions to advance the notion and value of translation and translators.

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The Best Innovation Management Software is Data-Driven, not Just Idea-Driven

Innovation relies on new perspective. We’ve found there are two ways to get that: collaboration and data. Either one can free our attention from the daily productivity push and spur an innovation.

That’s why the best innovation management software needs to utilize data, not just ideas.

Data Leads to New Perspective and Innovation

Researchers at a public health NGO are trying to eradicate dengue fever. They are investigating the possibility of spraying insecticides to kill mosquitoes. So one of them sits down at their organization’s knowledge-management application and does a search about prior research.

The software understood they were looking for mosquito-spraying research, but it knew enough to suggest they look into a different project focused on oral contraceptives. They can now collaborate and pursue parallel solutions.

The researchers had an idea, spraying for mosquitoes to stop dengue fever. The common data elements of mosquitoes and dengue led to new perspective on potential solutions.

Innovation Management is More Than Idea Management

Most innovation management software treat the two as synonymous (as does a google search, as a result). The do well at collecting, culling, and pushing ideas forward. It’s a pipeline, designed to show productivity based on a new idea.

Innovation, however, requires lateral movement, inspired by new perspective. Data illuminates context, detail, unknown unknowns, history, and implicit assumptions. So smart people find useful overlaps and new ideas.


Findable, Accessible, Interoperable, Reusable (FAIR)

Data is an essential stepping-stone for innovation. That means knowledge management is an essential part of innovation management software. Ideally data are findable, accessible, interoperable, and reusable, a.k.a. FAIR.



FAIR data standards, however, are not always feasible for data inside an organization, let alone for sharing them outside. Especially when it comes to healthcare, finance, or other highly proprietary verticals, knowledge management strategies can be tuned to sharing select data to create new perspective, without having to be 100% FAIR.

Anonymized data may be a viable alternative for making connections that lead to innovation. Even just metadata can do the job. A physician and an astronomer famously (well, not that famously) discovered that MRI software could be used to look at nebulae, just by understanding the type of data they each worked with.

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Innovation Management Software for Interdisciplinary Communities

It’s hard to create effective interdisciplinary teams or facilitate useful interdisciplinary exchanges. Research grants are increasingly calling for interdisciplinary collaboration as a requirement for funding. Interdisciplinary endeavors are popping up in academic settings and research foundations. Interdisciplinarity is a necessity for solving complex problems. But executing interdisciplinary collaboration is easier said than done.

Grand Challenges summit at the United Nations in Ethiopia 2019
The view from the Grand Challenges Summit at the UN facility in Ethiopia, where the Gates Foundation and the African-Academy of Sciences hosted an interdisciplinary conference on Africa’s biggest public health challenges.

Data science and data visualization can help, by identifying fruitful common ground between people with different expertise. Software can systematize effective interdisciplinary collaboration.

When it Goes Wrong and When it Goes Right

A researcher at a neuroscience institute described to us how the institute convened experts from numerous fields, but they barely talk. They speak different technical languages, have different methods and goals, and don’t know where to start.

We facilitated a discussion between a geneticist analyzing biomarkers for brain disease and a religious studies professor doing analytics on ancient islamic text. They were using a similar data visualization to analyze vastly different data. Once connected and informed about what they shared, a short discussion generated a lot of insight about each other and themselves, insight which formed part of a grant for the religious studies professor to continue his work with text analytics.

Complementary Differences are the Key

The positive impact of the interaction depended on identifying common ground. Complementary differences are the foundation of innovative interactions. Co-workers have complementary differences when they bring new expertise that can offer useful new perspective, but they have enough in common that they can communicate effectively with each other.

We created a 20-30 minute exercise that demonstrates the potential of finding complementary differences. It uses paper, pens, and sticky-notes. If you want to experiment with the idea of complementary differences in your organization or prove the concept to others, this exercise is a brief but immersive way to do it.

Complementary Differences as a Matter of Course

Paper and pen will not scale well, however. Software can process more data and subtler data about a community. It can offer data-driven insight into how to form teams and with whom to exchange perspective, and it can process data about how collaborations go and use it to improve.

You can walk through some of the tools and visualizations we use to facilitate interdisciplinary collaboration.


If you have a spreadsheet of data, we also offer a free visualization tool for understanding the overlap in your interdisciplinary community.

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collaborationinnovationInnovation Management

Mapping Expertise and Illuminating Dark Assets

by Alanna Riederer

At some point in your life, you’ve found yourself describing a project you’ve worked on to a friend. They interject, “I’ve done something similar to this before,” and go on to describe a field or skill you didn’t know they were familiar with. You’ve just uncovered some dark assets about your friend: a set of skills or knowledge that were only discovered due to an accidental trigger.

This can be problematic when it comes to group projects, whether you’re working with an existing team or you’re putting one together. The people and tools available to you are limited to those you are aware of or those cataloged in scattered directories and lists across the internet. There are far more dark assets than known assets.

In order to build and branch teams more effectively and innovatively, we need two things: a map and a compass. We build a map so that we can see the dark assets. We equip ourselves with a compass to guide us towards relevant assets.

We like to use a network diagram as our map.

Screen Shot 2019-05-07 at 7.46.30 AM

We use these networks to map people and resources. People could be resources, but we tend to distinguish people from inanimate assets, like publications or technologies.

We dub these people and resources “entities.” Every entity has “attributes” that describe it. For instance, people have interests, skills, passions, publications, and projects associated with them. A publication has a date, an author list, an abstract, and key terms. As I list these out, imagine how connections would form in the network between entities across shared attributes.

In the network below, you can see some shared connections on technology, for-profit, javascript, music, and sustainability and unique perspectives of Education, Social Good, cello, art, and AI.

In addition to the map, we need the equivalent of a compass – finer tools to navigate this environment. These tools illuminate the entities that bring the most complementary skills to our team composition.

  • Suggestion algorithms allow us to find teammates that add complementary differences to our team.  This is helpful for deciding which entities we should focus on in our map.
  • Artifact-recording tools allow us to document and track ideas inside documents and see how they connect.
  • Termscapes are a richer map for navigating the content that our community generates or studies. They are generated by analyzing unstructured text about a collection of entities and arranging those entities into a landscape of their terms.

Using these tools allows us to remove the accidental nature of discovering important resources. What tools do you use or wish you had to approach this problem?

The images in this post are screenshots from Data+Creativity City, an application that captures connections between members of the Data+Creativity Meetup. If you’re a member, come join the City and see how you’re connected!

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Innovative Technology Needed to Improve Crisis Response

article by and images from Dr. Victor Soji Ladele

Humanitarian crises in general are affecting more people, for longer. One in every 70 people around the world is caught up in crisis and urgently needs humanitarian assistance. Food insecurity is rising, with the number of people experiencing crisis-level food insecurity or worse increasing from 80 million to 124 million people between 2015 to 2017. The number of forcibly displaced people rose from 59.5 million in 2014 to 68.5 million in 2017. Natural disasters and climate change continue to affect 350 million people on average each year and cause billions of dollars of damage. Pandemics — large disease outbreaks that affect several countries — are rising as a global threat and pose major health, social, and economic risks. (Source: United Nations Coordinated Support to People Affected by Disaster And Conflict)

Approaching the border between Liberia and Guinea.

My recent experience on the frontlines of a large-scale Ebola outbreak and many years of health emergency response, confirm that health system weaknesses in many countries are a source of global health insecurity. In an article in the influential New England Journal of Medicine in 2015, Bill Gates said, “There is a significant chance that an epidemic of a substantially more infectious disease (than Ebola) will occur sometime in the next 20 years. In fact, of all the things that could kill more than 10 million people around the world, the most likely is an epidemic stemming from either natural causes or bioterrorism.” In this interconnected world, a threat in one place is a threat everywhere.

Humanitarian action is intended to save lives, alleviate suffering, and maintain human dignity during and after crises and disasters, but often fall short of its lofty ideals in practice. The way it works is that most of the estimated $27.3 billion allocated to international humanitarian response comes from governments, but action is via proxies, the “humanitarian actors” (2017 Global Humanitarian Assistance Report by Development Initiatives). Humanitarian actors come from a plethora of UN agencies, the International Federation of Red Cross and Red Crescent Societies, military branches, non-governmental organizations (NGOs), local institutions and donor agencies.

Operations conference room in Liberia during the Ebola response.

In order for actions to be quick, agile, and impactful, coordination is paramount. Information management is the bedrock of coordination, and it is fair to say that this is one of the most important activities during a crisis response. However, in recent years, networks connecting humanitarians have expanded so quickly, that the volume of data flowing through these pathways — and the number of information sources — have become in and of itself a problem. Data comes fast and hard from many sources, and adoption of ICT applications to improve outcomes has been relatively slow. The innumerable NGOs that are working on international humanitarian issues cannot alone address needs of such magnitude and diversity. To tackle these complex problems requires deeper levels of collaboration between formal humanitarian organizations and tech communities like Data+Creativity.

An Ebola treatment center closes after the last patient is discharged.

Taking the relatively recent Ebola pandemic of 2014-2016 as a case study, nothing prepared the health emergency responders, myself included, for the difficulty of containing the outbreak.  With its many intense “waves of transmission”, dealing with the deadly pandemic challenged assumptions like never before, but at the end established a new nexus of cooperation among traditionally dissimilar groups like – community chiefs, epidemiologists, pastors, imams, hobbyists, doctors, financiers, anthropologists, logisticians, politicians, computer scientists, and technologists.

map_smBetween its start in 2013 in Guinea’s dense forest, and end in 2016, the Ebola pandemic, which originated in a remote village, spread south to Conakry, Freetown and Monrovia, east to Lagos, north to Bamako, northwest to Dakar, and by jet to the United States, Spain, the U.K. and Italy. The virus killed at least 11,315 people in seven countries and caused more than 28,600 known infections. Beyond the immediate horror and loss of life, the usual routines of daily life in the most affected countries came to a halt: population movement was restricted, harvests interrupted, markets closed, and volume of trade contracted. Reduced commercial activity in the surrounding region reversed recent economic gains. An estimated $2.2 billion was lost just in 2015 from the gross domestic product (GDP) of the three most affected countries. This regional economic decline in turn caused a widespread crisis of food security, affecting hundreds of thousands of people and turned into a separate humanitarian situation of itself.

A meeting with several partners, including local health authorities in Lofa County.

Prior to Ebola, I had been active in medical humanitarian assistance and health emergency relief for many years. Having gained experience both in tiny, poor village health centers and at higher strategic levels with responsibility for broader policy decisions. I was already convinced of the effectiveness of tackling complex problems with complementary, cross-cultural and cross-disciplinary teams. The idea is gaining broad acceptance in the humanitarian and global development community, but this model of cooperation is yet lacking a purpose-built Information and Communication Technologies (ICT) tool. During the Ebola outbreak, I served as information management officer in addition to my role as team lead with the World Health Organization. Then and now, a framework for blending local knowledge and expert knowledge is absent. The lack of an effective platform to harness local expertise within the humanitarian affairs coordination framework has brought about a shocking amount of missed opportunities in humanitarian crisis response.

Despite the sorrow and devastation, as Bill Gates has noted, “perhaps the only good news from the tragic epidemic (Ebola) is that it may serve as a wake-up call. We must prepare for future epidemics of diseases that may spread more effectively than Ebola.” The world is at greater risk than ever from global health threats. We may not know what the next epidemic will be, but we know that one is coming. Disease threats can spread faster and more unpredictably than ever before. People are traveling more, food and medical product supply chains stretch across the globe, and biological threats as well as drug-resistant illnesses pose a growing danger to people everywhere.

During crises, professionals tend to avoid novel approaches that have not yet been tried and tested. They instead reach for familiar and trusted ways. As a result, humanitarian relief operations often deploy older technologies. Due to poorly adapted tools, training, and strategies, responders are increasingly ill-prepared to produce useful knowledge from the flow of information and data. There is thus an urgent need for innovative groups to engage early with humanitarian organizations, explore joint projects, and strengthen relationships before crises occur. These sorts of engagement will help both sides better understand each other’s modus operandi. As collaborations start to yield fruit, solutions will be developed and deployed to make all of us safer.

The first celebration of the end of the outbreak. Four days later there was a new case.

For startups and midsize companies, this presents an incredible opportunity and the timing is right. The timing is right because the biggest funding agencies are currently enamored with the idea of private sector engagement (PSE) as a strategic approach to international development and humanitarian crises response (USAID). Furthermore private foundations, traditionally a good source of funding for innovation, are getting more assertive and acting with more ambition. This is a good time for data practitioners, software developers, researchers, creative technologists and thinkers  to build relevant partnerships with humanitarian and international development organizations, who on their part have become more supportive of broader engagement to help forcibly displaced people, respond to natural disasters, and prevent pandemics.

The key to having impact quickly during complex emergencies is through cross-disciplinary collaboration. Funders realize this and are actively seeking for great ideas to get behind. To close with a quote from a popular author, Marianne Williamson: “Success means we go to sleep at night knowing that our talents and abilities were used in a way that served others.”

Dr. Victor Soji Ladele presented at the Data+Creativity Meetup in Oklahoma City, OK, on February 21, 2019. Watch the video archive here.

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