This document discusses various metrics and tools for organizing and analyzing academic research, including impact factor, h-index, SNIP, SJR, almetrics, and bibliographic databases like Web of Science, Scopus, and Mendeley. It also covers forming research questions, performing a systematic literature review, and presenting multiple perspectives to maintain objectivity. Key aspects include ranking journals by citation counts, normalizing metrics across fields, transitioning to online research sharing and real-time conferences, using text and data mining tools on vast amounts of information, and choosing topics of personal interest or that need innovation.

1. ADVANCED SEARCH TOPICS
CITING, RANKING,
METRICS,ORGANIZING, REFERENCING,
DATA AND TEXT MINING, FUNDS AND
GRANTS

2. Metrics, ranking, impact factor
We are familiar with page ranking from Google – its founder Larry Page
created a metric ranking the importance of a page by the number of entries.
In the academic world, ISI or the Web of Science database founded by Eric
Garfield, each author is hyperlinked to all the citations received. A
calculation between the number of articles an author has published and
citations received for each of those same articles
The impact factor statistic ranks journals by the number of citations the
journal received by the academic community.
Journals that have the highest impact factor are known as core journals and
academicians will prefer to publish their articles in these journals.
In science and technology there is another specific bibliographic database
called Scopus which has its own ranking system and analytics.
SJR = SCImago Journal Rank is weighted by the prestige of a journal. Subject
field, quality and reputation of the journal have a direct effect on the value
of a citation. SJR also normalizes for differences in citation behavior
between subject fields. IPP = Impact per Publication (IPP) measures the
ratio of citations per article published in the journal.
SNIP = Source Normalized Impact per Paper measures contextual citation
impact by weighting citations based on the total number of citations in a
subject.
Easy to see that these new analytic tools are more subject field related.

3. Next generation metrics
The continuous transition of scholarly work from
textbooks to journals to real-time global conferences(by
various learned societies, IEEE, and others) to
online websites such as Mendeley, blogs, Twitter,
Facebook, social media, etc.. In these online valuable
academic stat-of-the-art information becomes vital for the
progress if a researcher or a research field. Following this
new form of information workflow is a new metric system
called almetrics. These researchers are actually interested
in putting their input out there for the uuse of others and
also for the sharing of knowledge. Months pass before a
Peer reviewed article is actually published.

4. Data mining, text mining and the use of natural language
The necessity in dealing with vast amounts of knowledge and data beyond what is
published in the regular scholarly textbooks and journals, brings about text and data
mining analytics. The power of organizing vast amount of pages, tables, statistics and
data sets and reaching some of conclusion, something hidden in these vast forms of
information. These analytics are needed in all fields of medicine, science, technology,
government, business, and industry.
There are software available for processing this natural language
One is the R software, others are SAS and SPSS.

5. Forming the research question
In choosing a research question, one should think of a subject of personal interest or
passion, or researching a field that needs innovation, optimization, improvement or a
solution to a problem.
In event you need to prepare a reference list or literary search, one needs to review
all the relevant literature. After choosing the topic, look out for material (articles for
example) that support the theory you’ll be presenting in your paper. Also, in order to
observe objectivity, look out for articles with opposing views, and also it may be
worthwhile to compare research done in different countries. The fields of choice can
range from business, academic, commercial, government, aviation, transportation,
medicine, military, systems engineering, and more.
For the literary search use a systematic approach, choice of topic’ review all the
literature making notes of ideas, then presenting the problem and its different aspects,
citing the relevant literature. Make sure for objectivity by presenting more than one
solution, pros and cons, a comparison to what is don in other nations and finally, offer
some sort of solution in he conclusion.

6. MENDELEY
‫המחקר‬ ‫שאלת‬ ‫בחירת‬–‫אותך‬ ‫שמעניין‬ ‫תחום‬ ‫על‬ ‫לחשוב‬ ‫תמיד‬ ‫כדאי‬,‫פתרון‬ ‫להציע‬ ‫שיש‬ ‫תחום‬ ‫או‬
‫מסוימת‬ ‫לבעיה‬,
‫מסוים‬ ‫בפרויקט‬ ‫פתרון‬ ‫להציע‬ ‫כדי‬,‫שלך‬ ‫בגישה‬ ‫שתומכים‬ ‫מאמרים‬ ‫מחפש‬ ‫אתה‬:‫לדוגמא‬:‫שיפור‬
‫בישראל‬ ‫התחבורה‬?‫פתרון‬ ‫הינה‬ ‫הקלה‬ ‫רכבת‬ ‫האם‬?‫לשקף‬ ‫כדי‬ ‫ונגד‬ ‫בעד‬ ‫דוגמאות‬ ‫להביא‬ ‫כדאי‬
‫אובייקטיביות‬,‫שונות‬ ‫במדינות‬ ‫נהוג‬ ‫מה‬ ‫האקדמית‬ ‫בספרות‬ ‫לבדוק‬ ‫אולי‬ ‫כדאי‬.‫להיות‬ ‫יכולים‬ ‫תחומים‬
‫החברה‬ ‫תחומי‬ ‫בכל‬,‫ניהול‬,‫תעופה‬,‫תחבורה‬,‫צבאי‬,‫רפואה‬,‫מכשור‬,‫בטיחותי‬,‫סביבתי‬,‫מע‬'
‫שונות‬ ‫הנדסיות‬,‫וכ‬"‫ו‬.
‫הנושא‬ ‫של‬ ‫סיסטמתי‬ ‫חיפוש‬ ‫ביצוע‬–‫והן‬ ‫בדפוס‬ ‫הן‬ ‫המשאבים‬ ‫מגוון‬ ‫בכל‬ ‫החומר‬ ‫את‬ ‫חיפש‬
‫אלקטרוניים‬(‫קודם‬ ‫עליהם‬ ‫שדיברנו‬ ‫האופציות‬ ‫כל‬)
‫לסיכום‬:‫נושא‬ ‫בחירת‬,‫אובייקטיביות‬-‫הבעיה‬ ‫מכלול‬ ‫הצגת‬–‫בעד‬,‫נגד‬,‫כללי‬ ‫רקע‬,‫יתרונות‬,
‫חסרונות‬,‫מסקנות‬,‫פתרונות‬–‫חדשנית‬ ‫גישה‬ ‫להציג‬ ‫לנסות‬,‫פתרון‬ ‫ואף‬ ‫ייחודית‬ ‫זווית‬.