Knowledge Networking in Scientific Practice

Technology is being incorporated more and more into our daily lives. Social media platforms allow researchers to easily connect with one another and to simply find citations or resources. Artificial intelligence and big data make it relatively easy to obtain the information scientists need to move forward with their project. With the extended push to publish data, large amounts of data can be mined allowing for disparate studies to be combined, bigger patterns to be identified, and potentially further reaching conclusions to be made. With this comes the demand for researchers to, not only stay knowledgeable and on-top-of current research, alongside publishing their own articles. Knowledge networking, a way of compiling and sharing info, can help researchers find their way through the mounds of data and resources in order for these conclusions to be made.

Keywords: open research, collaboration, networking, publishing.
Originally posted on F1000 Blog on 17 July 2017.


Finding information, be it particular facts or a specific citation, is usually associated with finding the right publication – book or journal to reference – containing the needed information. With an internet based search, instead of discovering information, research has become more about filtering and constructing search queries into something useful. Open access makes it easier to obtain and share knowledge, intellectual resources, and data, but being able to parse through and distinguish between relevant and irrelevant information is crucial.

Knowledge networking, a way of compiling and sharing info, can help researchers find their way through the mounds of data and resources in order for these conclusions to be made.

Knowledge networking is a dynamic process in which knowledge is distributed and developed through increasing access to information and augmented by a community. There are a few different types of communities that exist that enable the spread of knowledge, each of which are expanded on below: publishing/networking, academic platforms, and specialist communities.

Publishing and networking

Journal publications are still the standard format for scientific dissertation and discourse. The way content is published has drastically changed over the past decade, where sharing raw data, presentations, and preprints is becoming more common practice.

Many online publication databases like PubMed and Web of Science, though not necessarily exclusively open access, have search functions that allow the tracking citations, parsing metadata, and filter for authorship. Some also allow users to track a certain topic and get email notifications of new publications. Branching out of the model of user based searches and instead using a more metadata approach, Semantic Scholar, an academic search engine, utilizes artificial intelligence with the goal to “connect the dots between disparate studies to identify novel hypotheses and to suggest experiments which would otherwise be missed.” Similarly, F1000Workspace uses algorithms to cater searches and identify important papers within the field as well as way to organize references and share documents with other researchers.

It is important for scientists to track and communicate with each other, especially when trying to establish a collaboration with another research group, as they need to connect personally as well as intellectually. Author IDs, like those from ORCID, aid in tying the work in a publication to a subject specialist and can be valuable in linking projects to people. In addition to ORCID, social media sites like LinkedIn and even Twitter connect researchers together. Even though these platforms are more geared toward job searches and visibility respectively, they can be valuable in easily connecting people.

It is important for scientists to track and communicate with each other, especially when trying to establish a collaboration with another research group, as they need to connect personally as well as intellectually.

Academic community platforms

Within academic spheres, a myriad of software tools are used to connect researchers and to aid in data hosting and paper writing. Universities frequently use internal private services that require authorization, like DropBox, due to their security. Platforms like Figshare and many other repositories host data and large databanks for any discipline. Many open access data banks, like the Protein Data Bank (PDB), which holds structural information on a protein, are required to be used before publishing a paper ensuring that the data is available for future use.

There are community based platforms like ResearchGate, with forum-like spaces to ask research related questions. On it, individuals can be linked together on projects and publications can be linked, and interesting papers that are hidden behind paywalls can be requested for directly from the author. Site members can follow a research interest, in addition to following individual members. ResearchGate indexes self-published information on user profiles to suggest members to connect with others who have similar interests.

Specialist communities

There are highly specific communities/academic platforms available that cater for specialist interests, such as MalariaWorld. These platforms allow all attention to focus on solving a very specific problem. Moreover, with the drive towards collaboration, the identification of experts within a given field is helpful. Such specialist communities allow individuals who have a special skill set to be identified and helps with networking communities.

Connecting the networks

Creating a sufficient knowledge network is a significant undertaking. However, when creating a platform an organization does not have to reinvent the wheel necessarily. Instead of each group defining their own metadata algorithms, their own ways of conducting social media, and inventing new methods of commenting or Q&A sections, perhaps what is needed is the combination of these (micro-)services to incorporate the best of what already exists. A significant resource for knowledge networking in this case would not be a singular organization or software that’s able to do it all, but one that links together the best at each service to get experts disseminating information.

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