| Philosophy | A systematic investigation into any phenomenon. Fundamental principle: Human reasoning and creativity. |
| Science | A systematic investigation into phenomena in the natural world susceptible to physical experimentation. Fundamentally inductive. |
| Technology | Tools and techniques for getting things done. Fundamental principle: Composition. |
| Mathematics | A systematic study of quantity, numbers, patterns, and their relationships. Fundamentally deductive. |
| Theory (isl. kenning) | “A set of statements or principles devised to explain a group of facts or phenomena, especially one that has been repeatedly tested or is widely accepted and can be used to make predictions about natural phenomena.” REF A theory is a relatively big explanation, covering several phenomena, often through a single principle, or a set of simple principles. |
| Hypothesis (isl. tilgáta) | Is a prediction about the relationship between a limited set of phenomena, as explained by a particular theory |
| Data | Typically “raw numbers” – only contain low-level semantics |
| Information | Processed and prepared data. Data organized at more than one level of detail. Data with a purpose. |
| Identification, description and formalization of phenomenon | 1. Observation and description of a phenomenon or group of phenomena. |
| Hypothesis, null-hypothesis | 2. Formulation of an hypothesis to explain the phenomena. In physics, the hypothesis often takes the form of a causal mechanism or a mathematical relation. |
| Creation of experimental setup to test hypothesis | 3. Use of the hypothesis to predict the existence of other phenomena, or to predict quantitatively the results of new observations. |
| Performance of experiment, collection and analysis of results | 4. Performance of experimental tests of the predictions by several independent experimenters and properly performed experiments. Basic assumption: Repeatability Can be repeated by anyone anywhere |
| Repeatability requires formal framework | Detailed description, clear goals, clear (limited) scope, hence the formalities in their execution |
| Key idea: Comparsion | Baseline collected in same experimental setup without any other intervention by experimenter |
| A scientific theory ties up loose ends | A good scientific theory shows how data connects. |
| A scientific theory predicts | A good scientific theory can be used to predict known and unknown results. |
| A scientific theory predicts new things | A good scientific theory enables us to know about the unknown; the more detailed the theory (in some sense “better”) the more detailed its predictions. |
| A scientific theory can produce new hypotheses | A good scientific theory helps us do more experiments by being a source of hypothesis creation. |
| A scientific theory “tells a story” | A good scientific theory explains how data relates. |
| A scientific theory gives us the big picture | A good scientific theory relates together in a coherent way some part of the world – the bigger the part, the better the theory. |
| A scientific theory explains | The more completely and the more simply it explains things, the better the theory is |
| Occam's Razor | A good scientific theory cannot be simplified; it is the shortest and most accurate explanation of a phenomenon. Einstein said: A theory should be as simple as possible, but not simpler. |
| The scientific method is independent of topic… | One can study any phenomenon with the scientific method, including claims of telepathy; selection of topic is independent of science – there is nothing inherently “unscientific” about studying any subject. (Close-mindedness is, however, unscientific.) |
| … yet methodology varies significantly by field | For example: - Illegal to make experiments on living human brains - Difficult to make comparative studies in sociology. |
| Computer Science | Direct testing of applications and programs. Models and simulations. User-driven studies Logical and mathematical proofs. |
| Sorting out variables | Independent variables: These are factors that need to be controlled for the results to be more intelligible. Example: If we want to study the efficiency speedup seen by a new multi-cultural word processor we would want to have all - or at least some (not just one) - of the cultures represented when we do the study. |
| Dependent variables | These are “the things we want to measure”, e.g. the speedup seen with the new word processor. |
| Designing the experiment | How do we measure the dependent variables? How do we control the independent variables? What are the hypotheses? How will we run the experiment? |
| Collecting data, analyzing results | Running experiments. Reading from sensors. Running through statistical methods to separate signal from noise. etc. |
| Writing up of the data | … in scientific papers and technical reports. |
| Submission | to scientific outlets, e.g. journals, conferences, workshops, etc. |
| The currency of Science | The scientific paper appearing in a peer-reviewed publication is the “currency” of science. |
| Date of publication, reception, acceptance | In addition to having a particular date of publication, many journals publish the date a paper was first received by the editors, before the revies and revision process started. |
| Ethics - Misaccreditation (plagiarism) | It is unethical to repeat verbatim from another author without proper accreditation. It is unethical to accredit oneself with work done by others. |
| Authorlist | Either alphabetical or in order of level of contribution. |
| Alphabetical list | All authors contributed at a similar level (at least in theory). |
| First author | This is the main author of the paper, that is, the person who: - is the driving force behind the work presented - is the author of the ideas presented in the paper - did most of the work and implementation. Ideally it is also the person who wrote most of the paper. |
| Reality | First author is often a professor who sticks their name on every paper published by a laboratory or department or group. |
| Second author | This is the “second person in command” for the work presented in the paper |
| Third, fourth, fifth, etc. author | Typically a list of people who did some of the work; sometimes these are also people who had a hand in the writing of the paper, but very often they are not (mostly for practical reasons). |
| Extremely long authorship lists | Becoming increasingly common in group projects |
| Last author | Increasingly advisors/professors are putting themselves at the end of the authors' list on papers describing the work of their students. |
| Acknowledgment vs. author? | If a person is not the authors' list (for whatever reason) but contributed something to the work, it is customary to put in a thank-you note in the Acknowledgment section. |
| Abstract | Short and concise! No extra words! “Like reading the whole paper in 1 minute.” This is the part of your paper that will be most frequently read, by far. |
| Introdution | Please do not copy the abstract and expand it into an introduction. Your readers already read your abstract. Don't make them read it in a more verbose version again! |
| Related work | A concise yet thorough explanation of what others have done and its relation to what you have done. This motivates your work described in this paper. |
| Description of work | Your contribution - What you did. |
| Results | What the measured readings were. |
| Summary or Conclusions | A summary summarizes what has been said. It is different from the abstract in that the motivation is typically not restated. Conclusions describe the conclusions drawn. Some (especially longer) papers have both these sections. |
| Acknowledgments | You probably got some help on your paper. Make sure you thank those who helped you! |
| References | The point of a reference list is to enable the reader to quickly and reliably locate the prior work you refer to in your paper. Make sure you follow the guidelines for how to structure the references. Make sure you include all info (volume numbers, publisher, page numbers, etc.) so that the references can be used for what they are there for! |
Example paper: http://www.aaai.org/ojs/index.php/aimagazine/article/view/1574/1473
| Not very different from standard scientific publications | The scientific paper provides the basic model |
| Authorship | A thesis is supposed to represent an original contribution of its main author, that is, the student's. |
| Co-authorship on papers derived from thesis | Often an advisor co-authors papers with the student based on the thesis work. It is considered beneficial for a student to publish with their advisor because (typically) the advisor is better known than the student. It is not the godsgiven right of the advisor to co-author papers with a student, especially not to be the first author of such work. This needs to be evaluated in every case… |
| Research Proposals | The major method for funding scientific research |
| Sources | Rannís, European Union |
| Form | All the same information that appears in a scientific paper will typically have to appear in a research proposal. Additional material includes researchers' CV, financial plans, names of student researchers, and a description of where and how the research will be conducted. |
| Application process | Find a 'call for proposals'. Carefully read the description. Note the proposal due date. Get the forms. Write the application, fill in the forms. Send everything in before the due date. Cross your fingers. |
| If you get the grant | Congratulations! Now you must do the work and write progress reports, typically once per year. |
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