A search for a product parameter returns a long PDF. I still have to open it and search again. Finding the file has done only part of the job.
Even an accurate answer may leave a colleague repeating the search next week. An answer that works in a conversation has not necessarily become part of a team’s capability.
I want to examine knowledge engineering through use: finding material, understanding what it answers, and carrying its conditions into the next task.
Retrieval and resolution are different stages
I maintain separate product and usability references because configuration questions and questions about applicable requirements need different context.
A precise model name or term may suit keyword search. Uncertain natural language can benefit from semantic retrieval of candidates. A relevant passage still needs checking against the actual question.
An old manual may be highly similar but refer to another configuration. A correct methods paragraph may omit conditions explained earlier. I treat retrieval as an entrance to judgment and preserve the route to the source.
“Found” and “applicable” should remain different states.
Splitting documents also sets interpretation boundaries
Long passages still need screening. Short ones can separate qualifications, exceptions, and definitions from the statements they govern.
I want a passage understandable on its own, with its document, section, and version recoverable. Some definitions and exceptions should remain together even if that breaks a preferred chunk size.
Relationships among documents matter too. An update may alter an older manual’s interpretation. A general method may have a task-specific exception. Storing both neatly without preserving their relationship still leaves the user to assemble the answer.
These decisions cannot all be completed on the first day. Real questions reveal poor boundaries and missing connections, which should change the organization.
Preserve a question and its conditions, not only a conclusion
Suppose a paper finds one interaction approach performs better in an experiment. Saving only “A beats B” makes it easy to carry the result into different tasks and populations.
I would retain the research question, participants, task, comparison, main result, limitations, and possible decision implications. An interesting method is not automatically suitable for our project.
Datasheets proposes documenting a dataset’s motivation, composition, collection, and recommended uses. I borrow its attention to conditions of use; it does not validate the team knowledge system proposed here. Datasheets for Datasets
Such records make correction possible. When new findings conflict, we can inspect differences in tasks or samples, or revise the earlier interpretation, instead of merely placing two summaries together.
Access changes whether knowledge is used
A briefing available only inside its author’s conversation, or requiring additional software, has a restricted practical audience.
This is why I care about HTML pages, copyable tables, and content that can be edited and redeployed. A page supports browsing and stable reference; a table supports comparison and further work; the original document supports detailed checking.
A webpage does not establish universal access. Readers’ networks, phones, login requirements, and download conditions need checking. The author opening it successfully is only a starting point, especially across locations.
Presentation should also fit the reader’s task. Researchers need methods and limits; product teams need application conditions and open opportunities. They can enter different layers of the same sources rather than receive unrelated conclusions.
Updates must reach old answers
A knowledge collection looks most successful just after organization. The harder test comes when sources change and old answers remain in circulation.
I would distinguish original sources, interpreted entries, and records of use. A source update should trigger inspection of affected entries. An entry change should explain its difference. Earlier projects should still be able to recover the version they used.
Obsolete does not always mean useless. A historical judgment may explain a previous decision without supporting current advice. Dates and status help more than silently replacing everything with a current version.
Responsibility also needs names or roles. Who notices a change, assesses its effects, updates the entry, and responds to colleagues’ questions? Without that arrangement, the collection may remain a searchable pile of files.
Evaluate the next task
Entry count interests me less than whether colleagues find relevant material, assess its applicability, and avoid unnecessary searching. Where must the author still explain everything again?
Missing answers deserve a record. Is the evidence absent, or is existing material difficult to find? The first needs research; the second needs organization. Confusing them can cause repeated acquisition of information already held, or unrealistic expectations that better filing will create missing facts.
When a project adds a limitation or counterexample, it should have an easy route back into the collection. Maintenance close to ordinary work is less likely to leave learning only in personal memory.
The cycle I want begins with a concrete question, uses sources to support a judgment, checks that judgment in practice, and lets new findings alter the records. It complements reusable research skills: one preserves how to proceed; the other preserves what should be known while proceeding.